Quildra
/
PokeGoalsHelper
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
73 Commits
15 Branches
0 Tags
533 MiB
Tree: 65fadd2060
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from '65fadd2060'
${ noResults }
PokeGoalsHelper/temp/Pokemon_Home_Training.ipynb

8402 lines
5.4 MiB
Raw Normal View History

feat: enhance bottom drawer with multi-column layout and checkbox functionality - Redesigned expanded content with organized sections: * Pokemon Info (Name, Dex #, Gender, Form) * Combat Stats (CP, HP, Level, IV%) * Individual Stats (ATK/DEF/STA if available) * Special Properties (Shiny/Alpha checkboxes) * Technical Info (Processing time, Detection count, Timestamp) - Added multi-column layout helper methods for better space utilization - Implemented checkbox indicators using Unicode symbols (☐/☑) - Enhanced visual hierarchy with blue section headers - Improved data organization and readability 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
5 months ago
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4"
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "99eaa098",
"outputId": "f13272f1-a4ee-47bb-d27c-7b6843aa3b67"
},
"source": [
"!unzip /content/pokemon_yolov8_dataset.zip -d /content/"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Archive: /content/pokemon_yolov8_dataset.zip\n",
" creating: /content/pokemon_yolov8_dataset/\n",
" creating: /content/pokemon_yolov8_dataset/images/\n",
" creating: /content/pokemon_yolov8_dataset/images/train/\n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223229_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223239_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223243_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223246_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223301_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223304_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223309_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223313_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223317_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223321_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223325_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223328_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223331_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223335_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223338_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223342_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223346_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223355_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223358_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223740_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223748_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223752_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223755_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223758_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223801_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223805_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223813_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223816_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223820_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223829_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223836_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223839_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223843_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223847_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223853_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223856_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223900_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223904_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223910_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223914_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223917_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223920_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223932_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223940_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223943_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224039_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224217_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224220_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224223_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224227_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224230_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224233_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224243_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224246_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224249_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224252_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224255_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224258_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224307_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224343_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224346_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224349_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224353_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224355_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224358_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224401_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224410_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224413_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224416_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224422_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224426_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224429_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224431_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224434_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224437_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224440_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224500_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250725_074244_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250725_074425_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222229_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222232_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222236_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222239_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222243_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222246_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222256_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222259_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222301_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222306_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222309_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222314_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222317_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222320_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222325_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222328_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222331_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222334_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222337_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222340_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222343_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222347_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222352_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222354_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222357_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222407_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222409_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222414_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222418_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222422_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222425_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222428_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222431_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222434_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222439_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222442_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222445_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222451_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222453_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222456_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222458_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222501_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222503_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222511_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222514_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222519_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222522_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222525_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222527_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222530_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222532_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222535_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222538_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222544_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222553_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222557_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222559_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222602_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222605_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222608_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222613_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222615_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222628_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222631_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222643_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222647_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222653_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222712_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222717_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222739_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222747_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222754_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222811_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222818_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222852_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222903_Pokmon HOME.jpg \n",
" creating: /content/pokemon_yolov8_dataset/images/val/\n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223222_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223250_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223254_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223257_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223349_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223352_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223736_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223743_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223810_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223823_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223826_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223907_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223923_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223926_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223929_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223935_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224036_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224236_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224239_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224404_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224407_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222249_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222253_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222312_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222400_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222436_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222448_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222506_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222509_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222516_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222542_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222547_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222550_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222610_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222635_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222701_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222722_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222744_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222750_Pokmon HOME.jpg \n",
" inflating: /content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222824_Pokmon HOME.jpg \n",
" creating: /content/pokemon_yolov8_dataset/labels/\n",
" creating: /content/pokemon_yolov8_dataset/labels/train/\n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223229_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223239_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223243_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223246_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223301_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223304_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223309_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223313_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223317_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223321_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223325_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223328_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223331_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223335_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223338_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223342_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223346_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223355_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223358_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223740_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223748_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223752_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223755_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223758_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223801_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223805_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223813_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223816_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223820_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223829_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223836_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223839_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223843_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223847_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223853_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223856_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223900_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223904_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223910_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223914_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223917_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223920_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223932_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223940_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_223943_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224039_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224217_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224220_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224223_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224227_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224230_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224233_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224243_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224246_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224249_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224252_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224255_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224258_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224307_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224343_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224346_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224349_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224353_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224355_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224358_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224401_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224410_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224413_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224416_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224422_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224426_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224429_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224431_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224434_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224437_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224440_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250724_224500_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250725_074244_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250725_074425_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222229_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222232_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222236_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222239_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222243_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222246_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222256_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222259_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222301_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222306_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222309_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222314_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222317_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222320_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222325_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222328_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222331_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222334_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222337_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222340_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222343_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222347_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222352_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222354_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222357_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222407_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222409_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222414_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222418_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222422_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222425_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222428_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222431_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222434_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222439_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222442_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222445_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222451_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222453_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222456_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222458_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222501_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222503_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222511_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222514_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222519_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222522_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222525_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222527_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222530_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222532_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222535_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222538_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222544_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222553_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222557_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222559_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222602_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222605_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222608_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222613_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222615_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222628_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222631_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222643_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222647_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222653_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222712_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222717_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222739_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222747_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222754_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222811_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222818_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222852_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/train/Screenshot_20250726_222903_Pokmon HOME.txt \n",
" creating: /content/pokemon_yolov8_dataset/labels/val/\n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223222_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223250_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223254_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223257_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223349_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223352_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223736_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223743_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223810_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223823_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223826_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223907_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223923_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223926_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223929_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_223935_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_224036_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_224236_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_224239_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_224404_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250724_224407_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222249_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222253_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222312_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222400_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222436_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222448_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222506_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222509_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222516_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222542_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222547_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222550_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222610_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222635_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222701_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222722_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222744_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222750_Pokmon HOME.txt \n",
" inflating: /content/pokemon_yolov8_dataset/labels/val/Screenshot_20250726_222824_Pokmon HOME.txt \n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "8fc7e772"
},
"source": [
"!rm -rf runs __pycache__ pokemon_yolov8_dataset"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "aYIAJKQgqt-z",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"collapsed": true,
"outputId": "9779b70b-3a90-43e9-d022-23b475e51c97"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Requirement already satisfied: ultralytics in /usr/local/lib/python3.11/dist-packages (8.3.170)\n",
"Requirement already satisfied: numpy>=1.23.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.0.2)\n",
"Requirement already satisfied: matplotlib>=3.3.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (3.10.0)\n",
"Requirement already satisfied: opencv-python>=4.6.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (4.12.0.88)\n",
"Requirement already satisfied: pillow>=7.1.2 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (11.3.0)\n",
"Requirement already satisfied: pyyaml>=5.3.1 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (6.0.2)\n",
"Requirement already satisfied: requests>=2.23.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.32.3)\n",
"Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (1.16.0)\n",
"Requirement already satisfied: torch>=1.8.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.6.0+cu124)\n",
"Requirement already satisfied: torchvision>=0.9.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (0.21.0+cu124)\n",
"Requirement already satisfied: tqdm>=4.64.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (4.67.1)\n",
"Requirement already satisfied: psutil in /usr/local/lib/python3.11/dist-packages (from ultralytics) (5.9.5)\n",
"Requirement already satisfied: py-cpuinfo in /usr/local/lib/python3.11/dist-packages (from ultralytics) (9.0.0)\n",
"Requirement already satisfied: pandas>=1.1.4 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.2.2)\n",
"Requirement already satisfied: ultralytics-thop>=2.0.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.0.14)\n",
"Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.3.2)\n",
"Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (0.12.1)\n",
"Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (4.59.0)\n",
"Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.4.8)\n",
"Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (25.0)\n",
"Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (3.2.3)\n",
"Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (2.9.0.post0)\n",
"Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas>=1.1.4->ultralytics) (2025.2)\n",
"Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas>=1.1.4->ultralytics) (2025.2)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests>=2.23.0->ultralytics) (3.4.2)\n",
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests>=2.23.0->ultralytics) (3.10)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests>=2.23.0->ultralytics) (2.5.0)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests>=2.23.0->ultralytics) (2025.7.14)\n",
"Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.18.0)\n",
"Requirement already satisfied: typing-extensions>=4.10.0 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (4.14.1)\n",
"Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.5)\n",
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.1.6)\n",
"Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (2025.3.0)\n",
"Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.4.127)\n",
"Requirement already satisfied: nvidia-cuda-runtime-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.4.127)\n",
"Requirement already satisfied: nvidia-cuda-cupti-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.4.127)\n",
"Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (9.1.0.70)\n",
"Requirement already satisfied: nvidia-cublas-cu12==12.4.5.8 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.4.5.8)\n",
"Requirement already satisfied: nvidia-cufft-cu12==11.2.1.3 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (11.2.1.3)\n",
"Requirement already satisfied: nvidia-curand-cu12==10.3.5.147 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (10.3.5.147)\n",
"Requirement already satisfied: nvidia-cusolver-cu12==11.6.1.9 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (11.6.1.9)\n",
"Requirement already satisfied: nvidia-cusparse-cu12==12.3.1.170 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.3.1.170)\n",
"Requirement already satisfied: nvidia-cusparselt-cu12==0.6.2 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (0.6.2)\n",
"Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (2.21.5)\n",
"Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.4.127)\n",
"Requirement already satisfied: nvidia-nvjitlink-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.4.127)\n",
"Requirement already satisfied: triton==3.2.0 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.2.0)\n",
"Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (1.13.1)\n",
"Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch>=1.8.0->ultralytics) (1.3.0)\n",
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.7->matplotlib>=3.3.0->ultralytics) (1.17.0)\n",
"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch>=1.8.0->ultralytics) (3.0.2)\n",
"Ultralytics 8.3.170 🚀 Python-3.11.13 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB)\n",
"\u001b[34m\u001b[1mengine/trainer: \u001b[0magnostic_nms=False, amp=True, augment=True, auto_augment=randaugment, batch=16, bgr=0.0, box=7.5, cache=True, cfg=None, classes=None, close_mosaic=10, cls=0.5, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/content/dataset.yaml, degrees=0.0, deterministic=True, device=None, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=100, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, int8=False, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=yolov8m.pt, momentum=0.937, mosaic=1.0, multi_scale=False, name=train, nbs=64, nms=False, opset=None, optimize=False, optimizer=auto, overlap_mask=True, patience=50, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=None, rect=False, resume=False, retina_masks=False, save=True, save_conf=False, save_crop=False, save_dir=runs/detect/train, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=train, stream_buffer=False, task=detect, time=None, tracker=botsort.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=8, workspace=None\n",
"Overriding model.yaml nc=80 with nc=96\n",
"\n",
" from n params module arguments \n",
" 0 -1 1 1392 ultralytics.nn.modules.conv.Conv [3, 48, 3, 2] \n",
" 1 -1 1 41664 ultralytics.nn.modules.conv.Conv [48, 96, 3, 2] \n",
" 2 -1 2 111360 ultralytics.nn.modules.block.C2f [96, 96, 2, True] \n",
" 3 -1 1 166272 ultralytics.nn.modules.conv.Conv [96, 192, 3, 2] \n",
" 4 -1 4 813312 ultralytics.nn.modules.block.C2f [192, 192, 4, True] \n",
" 5 -1 1 664320 ultralytics.nn.modules.conv.Conv [192, 384, 3, 2] \n",
" 6 -1 4 3248640 ultralytics.nn.modules.block.C2f [384, 384, 4, True] \n",
" 7 -1 1 1991808 ultralytics.nn.modules.conv.Conv [384, 576, 3, 2] \n",
" 8 -1 2 3985920 ultralytics.nn.modules.block.C2f [576, 576, 2, True] \n",
" 9 -1 1 831168 ultralytics.nn.modules.block.SPPF [576, 576, 5] \n",
" 10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n",
" 11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
" 12 -1 2 1993728 ultralytics.nn.modules.block.C2f [960, 384, 2] \n",
" 13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n",
" 14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
" 15 -1 2 517632 ultralytics.nn.modules.block.C2f [576, 192, 2] \n",
" 16 -1 1 332160 ultralytics.nn.modules.conv.Conv [192, 192, 3, 2] \n",
" 17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
" 18 -1 2 1846272 ultralytics.nn.modules.block.C2f [576, 384, 2] \n",
" 19 -1 1 1327872 ultralytics.nn.modules.conv.Conv [384, 384, 3, 2] \n",
" 20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
" 21 -1 2 4207104 ultralytics.nn.modules.block.C2f [960, 576, 2] \n",
" 22 [15, 18, 21] 1 3831280 ultralytics.nn.modules.head.Detect [96, [192, 384, 576]] \n",
"Model summary: 169 layers, 25,911,904 parameters, 25,911,888 gradients, 79.4 GFLOPs\n",
"\n",
"Transferred 469/475 items from pretrained weights\n",
"Freezing layer 'model.22.dfl.conv.weight'\n",
"\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks...\n",
"\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n",
"\u001b[34m\u001b[1mtrain: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 2613.5±267.4 MB/s, size: 532.3 KB)\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/pokemon_yolov8_dataset/labels/train... 155 images, 0 backgrounds, 0 corrupt: 100%|██████████| 155/155 [00:05<00:00, 30.14it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223229_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223239_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223243_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223246_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223301_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223304_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223309_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223313_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223317_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223321_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223325_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223328_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223331_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223335_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223338_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223342_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223346_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223355_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223358_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223740_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223748_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223752_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223755_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223758_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223801_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223805_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223813_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223816_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223820_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223829_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223836_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223839_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223843_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223847_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223853_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223856_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223900_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223904_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223910_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223914_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223917_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223920_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223932_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223940_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223943_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224039_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224217_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224220_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224223_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224227_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224230_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224233_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224243_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224246_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224249_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224252_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224255_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224258_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224307_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224343_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224346_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224349_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224353_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224355_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224358_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224401_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224410_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224413_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224416_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224422_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224426_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224429_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224431_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224434_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224437_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224440_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224500_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250725_074244_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250725_074425_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222229_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222232_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222236_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222239_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222243_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222246_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222256_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222259_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222301_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222306_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222309_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222314_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222317_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222320_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222325_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222328_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222331_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222334_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222337_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222340_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222343_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222347_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222352_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222354_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222357_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222407_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222409_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222414_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222418_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222422_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222425_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222428_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222431_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222434_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222439_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222442_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222445_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222451_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222453_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222456_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222458_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222501_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222503_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222511_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222514_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222519_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222522_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222525_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222527_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222530_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222532_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222535_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222538_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222544_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222553_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222557_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222559_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222602_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222605_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222608_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222613_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222615_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222628_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222631_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222643_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222647_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222653_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222712_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222717_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222739_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222747_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222754_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222811_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222818_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222852_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222903_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/pokemon_yolov8_dataset/labels/train.cache\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"WARNING ⚠️ cache='ram' may produce non-deterministic training results. Consider cache='disk' as a deterministic alternative if your disk space allows.\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mtrain: \u001b[0mCaching images (0.1GB RAM): 100%|██████████| 155/155 [00:03<00:00, 51.13it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 1082.9±922.8 MB/s, size: 505.5 KB)\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mScanning /content/pokemon_yolov8_dataset/labels/val... 40 images, 0 backgrounds, 0 corrupt: 100%|██████████| 40/40 [00:02<00:00, 18.62it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223222_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223250_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223254_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223257_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223349_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223352_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223736_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223743_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223810_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223823_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223826_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223907_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223923_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223926_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223929_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_223935_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224036_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224236_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224239_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224404_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250724_224407_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222249_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222253_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222312_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222400_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222436_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222448_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222506_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222509_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222516_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222542_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222547_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222550_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222610_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222635_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222701_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222722_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222744_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222750_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_yolov8_dataset/images/val/Screenshot_20250726_222824_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/pokemon_yolov8_dataset/labels/val.cache\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"WARNING ⚠️ cache='ram' may produce non-deterministic training results. Consider cache='disk' as a deterministic alternative if your disk space allows.\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mCaching images (0.0GB RAM): 100%|██████████| 40/40 [00:01<00:00, 38.89it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Plotting labels to runs/detect/train/labels.jpg... \n",
"\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n",
"\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.0001, momentum=0.9) with parameter groups 77 weight(decay=0.0), 84 weight(decay=0.0005), 83 bias(decay=0.0)\n",
"Image sizes 640 train, 640 val\n",
"Using 2 dataloader workers\n",
"Logging results to \u001b[1mruns/detect/train\u001b[0m\n",
"Starting training for 100 epochs...\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 1/100 6.63G 2.516 6.378 1.338 409 640: 100%|██████████| 10/10 [00:06<00:00, 1.52it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.76it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.00458 0.0529 0.00754 0.00613\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 2/100 6.86G 2.01 5.568 1.134 491 640: 100%|██████████| 10/10 [00:05<00:00, 1.68it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.36it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.011 0.121 0.0214 0.0142\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 3/100 6.9G 1.751 4.557 0.9988 400 640: 100%|██████████| 10/10 [00:05<00:00, 1.76it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.05it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.667 0.0709 0.0567 0.0293\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 4/100 6.96G 1.584 3.396 0.9371 569 640: 100%|██████████| 10/10 [00:05<00:00, 1.78it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 3.63it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.544 0.105 0.14 0.081\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 5/100 7.03G 1.463 2.513 0.9152 505 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.84it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.603 0.183 0.243 0.157\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 6/100 7.1G 1.365 1.945 0.8876 546 640: 100%|██████████| 10/10 [00:05<00:00, 1.77it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.89it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.572 0.323 0.368 0.245\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 7/100 7.26G 1.281 1.622 0.8784 412 640: 100%|██████████| 10/10 [00:05<00:00, 1.85it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.20it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.594 0.402 0.417 0.283\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 8/100 7.43G 1.212 1.348 0.8689 408 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.17it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.694 0.457 0.507 0.355\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 9/100 6.67G 1.152 1.158 0.8564 501 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.59it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.718 0.509 0.543 0.399\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 10/100 6.77G 1.11 1.04 0.8603 334 640: 100%|██████████| 10/10 [00:05<00:00, 1.85it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.32it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.727 0.564 0.563 0.424\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 11/100 6.78G 1.011 0.9037 0.8519 505 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.50it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.778 0.551 0.603 0.455\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 12/100 6.95G 1.071 0.8901 0.8488 457 640: 100%|██████████| 10/10 [00:05<00:00, 1.79it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.19it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.752 0.558 0.637 0.481\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 13/100 7.11G 1.082 0.8414 0.8521 602 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.34it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.77 0.568 0.638 0.471\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 14/100 7.28G 1.06 0.8139 0.8515 343 640: 100%|██████████| 10/10 [00:05<00:00, 1.74it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.38it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.641 0.638 0.664 0.503\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 15/100 7.44G 1.068 0.7719 0.846 488 640: 100%|██████████| 10/10 [00:05<00:00, 1.83it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.51it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.66 0.729 0.679 0.501\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 16/100 6.78G 1.043 0.7631 0.8485 454 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.45it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.688 0.709 0.699 0.535\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 17/100 6.78G 1.029 0.7287 0.8378 515 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.33it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.685 0.703 0.712 0.541\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 18/100 6.8G 0.9602 0.7002 0.8366 567 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.35it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.686 0.703 0.718 0.559\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 19/100 6.96G 0.9184 0.6748 0.8334 470 640: 100%|██████████| 10/10 [00:05<00:00, 1.88it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.56it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.769 0.709 0.731 0.572\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 20/100 7.12G 0.9386 0.6681 0.8371 470 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.46it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.757 0.705 0.734 0.579\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 21/100 7.29G 0.9178 0.6452 0.831 614 640: 100%|██████████| 10/10 [00:05<00:00, 1.87it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.43it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.732 0.701 0.74 0.577\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 22/100 7.36G 0.8752 0.6135 0.8344 397 640: 100%|██████████| 10/10 [00:05<00:00, 1.79it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.41it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.737 0.714 0.754 0.59\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 23/100 6.64G 0.879 0.6015 0.8283 406 640: 100%|██████████| 10/10 [00:05<00:00, 1.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.42it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.736 0.705 0.764 0.606\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 24/100 6.87G 0.8993 0.6033 0.825 581 640: 100%|██████████| 10/10 [00:05<00:00, 1.79it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.44it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.756 0.758 0.781 0.617\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 25/100 6.87G 0.8675 0.5945 0.8231 566 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.65it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.77 0.772 0.789 0.631\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 26/100 6.93G 0.8672 0.5797 0.8223 508 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.38it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.757 0.756 0.818 0.655\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 27/100 6.99G 0.8416 0.5691 0.8237 391 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.57it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.796 0.752 0.812 0.651\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 28/100 7.16G 0.8339 0.5637 0.8252 483 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.55it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.789 0.741 0.823 0.661\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 29/100 7.22G 0.8288 0.55 0.8199 403 640: 100%|██████████| 10/10 [00:05<00:00, 1.78it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.64it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.754 0.754 0.827 0.664\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 30/100 7.39G 0.8312 0.5494 0.8282 399 640: 100%|██████████| 10/10 [00:05<00:00, 1.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.57it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.739 0.834 0.842 0.678\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 31/100 6.86G 0.8072 0.5248 0.8231 552 640: 100%|██████████| 10/10 [00:05<00:00, 1.77it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.55it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.779 0.838 0.859 0.692\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 32/100 6.87G 0.8007 0.5179 0.8187 520 640: 100%|██████████| 10/10 [00:05<00:00, 1.83it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.42it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.781 0.84 0.859 0.692\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 33/100 6.93G 0.8248 0.5145 0.8287 378 640: 100%|██████████| 10/10 [00:05<00:00, 1.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.55it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.785 0.842 0.872 0.697\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 34/100 7G 0.7728 0.5103 0.8221 432 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.47it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.799 0.823 0.872 0.712\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 35/100 7.16G 0.7775 0.5006 0.8192 507 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.52it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.782 0.843 0.886 0.718\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 36/100 7.23G 0.8079 0.4959 0.8255 398 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.02it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.779 0.838 0.886 0.726\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 37/100 7.39G 0.7651 0.4965 0.819 451 640: 100%|██████████| 10/10 [00:05<00:00, 1.87it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.48it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.78 0.836 0.872 0.715\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 38/100 6.62G 0.7845 0.4937 0.8122 527 640: 100%|██████████| 10/10 [00:05<00:00, 1.79it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.56it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.795 0.832 0.88 0.718\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 39/100 6.82G 0.765 0.4906 0.818 442 640: 100%|██████████| 10/10 [00:05<00:00, 1.87it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.65it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.849 0.789 0.884 0.722\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 40/100 6.85G 0.7669 0.4788 0.8164 434 640: 100%|██████████| 10/10 [00:05<00:00, 1.79it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.47it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.799 0.834 0.883 0.726\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 41/100 6.91G 0.7797 0.4825 0.8226 560 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.50it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.8 0.84 0.878 0.715\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 42/100 7.08G 0.7813 0.4875 0.8203 474 640: 100%|██████████| 10/10 [00:05<00:00, 1.78it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.56it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.854 0.824 0.887 0.73\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 43/100 7.24G 0.7813 0.4856 0.8151 574 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.54it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.854 0.816 0.891 0.728\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 44/100 7.41G 0.7859 0.4763 0.8148 386 640: 100%|██████████| 10/10 [00:05<00:00, 1.85it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.55it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.879 0.787 0.887 0.732\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 45/100 6.92G 0.7893 0.4695 0.815 426 640: 100%|██████████| 10/10 [00:05<00:00, 1.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.37it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.885 0.777 0.886 0.727\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 46/100 6.92G 0.7611 0.4665 0.809 509 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.87it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.815 0.832 0.885 0.728\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 47/100 6.97G 0.7525 0.4599 0.8199 503 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.43it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.864 0.809 0.885 0.736\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 48/100 7.04G 0.7524 0.4546 0.8136 491 640: 100%|██████████| 10/10 [00:05<00:00, 1.79it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.25it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.808 0.856 0.887 0.735\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 49/100 7.11G 0.7734 0.4531 0.8193 386 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.47it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.814 0.855 0.885 0.732\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 50/100 7.27G 0.7541 0.4483 0.8136 519 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.60it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.813 0.854 0.885 0.734\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 51/100 7.44G 0.7216 0.4434 0.8139 512 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.51it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.81 0.849 0.886 0.733\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 52/100 6.67G 0.7424 0.4475 0.8091 510 640: 100%|██████████| 10/10 [00:05<00:00, 1.79it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.48it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.81 0.848 0.878 0.725\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 53/100 6.67G 0.7311 0.441 0.8147 607 640: 100%|██████████| 10/10 [00:05<00:00, 1.87it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.23it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.865 0.8 0.879 0.73\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 54/100 6.87G 0.7343 0.4371 0.8058 500 640: 100%|██████████| 10/10 [00:05<00:00, 1.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.63it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.877 0.795 0.878 0.726\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 55/100 6.94G 0.7137 0.4354 0.8087 448 640: 100%|██████████| 10/10 [00:05<00:00, 1.87it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.29it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.905 0.787 0.877 0.728\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 56/100 7.11G 0.7248 0.4366 0.8076 490 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.59it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.821 0.845 0.876 0.725\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 57/100 7.27G 0.7129 0.4215 0.8158 411 640: 100%|██████████| 10/10 [00:05<00:00, 1.87it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.35it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.823 0.853 0.875 0.725\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 58/100 7.44G 0.7234 0.4322 0.8121 418 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.70it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.824 0.853 0.874 0.721\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 59/100 6.85G 0.7065 0.4188 0.8105 481 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.65it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.826 0.852 0.875 0.728\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 60/100 6.85G 0.7647 0.4373 0.8082 558 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.47it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.843 0.841 0.877 0.728\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 61/100 6.92G 0.7252 0.4317 0.8086 512 640: 100%|██████████| 10/10 [00:05<00:00, 1.85it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.63it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.84 0.852 0.878 0.739\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 62/100 6.99G 0.7319 0.4329 0.8062 475 640: 100%|██████████| 10/10 [00:05<00:00, 1.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.21it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.874 0.807 0.878 0.736\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 63/100 7.15G 0.6818 0.4115 0.8064 329 640: 100%|██████████| 10/10 [00:05<00:00, 1.83it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.70it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.876 0.807 0.878 0.73\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 64/100 7.31G 0.7225 0.4292 0.8092 390 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.42it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.866 0.811 0.882 0.73\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 65/100 7.38G 0.7043 0.4244 0.8054 448 640: 100%|██████████| 10/10 [00:05<00:00, 1.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.69it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.807 0.864 0.882 0.73\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 66/100 6.71G 0.7314 0.4332 0.8093 418 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.54it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.873 0.831 0.882 0.733\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 67/100 6.71G 0.7042 0.4146 0.8052 483 640: 100%|██████████| 10/10 [00:05<00:00, 1.83it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.51it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.858 0.844 0.882 0.734\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 68/100 6.82G 0.7136 0.4229 0.805 461 640: 100%|██████████| 10/10 [00:05<00:00, 1.85it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.43it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.873 0.847 0.882 0.736\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 69/100 6.98G 0.7253 0.4267 0.8097 535 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.55it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.869 0.844 0.879 0.735\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 70/100 7.15G 0.7144 0.4214 0.8036 524 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.34it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.866 0.843 0.879 0.737\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 71/100 7.21G 0.7251 0.4203 0.8039 770 640: 100%|██████████| 10/10 [00:05<00:00, 1.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.55it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.846 0.852 0.879 0.738\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 72/100 7.38G 0.6805 0.4056 0.7998 457 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.62it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.856 0.833 0.885 0.739\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 73/100 6.94G 0.6937 0.4106 0.8085 498 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.23it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.892 0.814 0.879 0.738\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 74/100 6.94G 0.6856 0.4039 0.8049 543 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.72it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.872 0.832 0.883 0.736\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 75/100 7G 0.679 0.3991 0.798 400 640: 100%|██████████| 10/10 [00:05<00:00, 1.83it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.71it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.869 0.832 0.886 0.74\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 76/100 7.07G 0.6878 0.3994 0.8134 304 640: 100%|██████████| 10/10 [00:05<00:00, 1.85it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.98it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.865 0.851 0.883 0.733\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 77/100 7.14G 0.6891 0.4045 0.811 481 640: 100%|██████████| 10/10 [00:05<00:00, 1.83it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.62it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.86 0.851 0.883 0.737\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 78/100 7.3G 0.6849 0.399 0.8088 525 640: 100%|██████████| 10/10 [00:05<00:00, 1.83it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.61it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.852 0.844 0.88 0.732\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 79/100 7.47G 0.6805 0.4019 0.808 534 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.73it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.854 0.845 0.884 0.737\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 80/100 6.6G 0.6812 0.4012 0.8101 386 640: 100%|██████████| 10/10 [00:05<00:00, 1.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.41it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.864 0.844 0.879 0.732\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 81/100 6.7G 0.6879 0.3974 0.7999 577 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.66it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.866 0.849 0.886 0.736\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 82/100 6.83G 0.6772 0.3925 0.8066 493 640: 100%|██████████| 10/10 [00:05<00:00, 1.80it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.63it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.866 0.848 0.885 0.738\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 83/100 6.99G 0.6764 0.3955 0.8033 467 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.43it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.872 0.849 0.886 0.738\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 84/100 7.15G 0.688 0.3996 0.8079 547 640: 100%|██████████| 10/10 [00:05<00:00, 1.79it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.59it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.87 0.849 0.885 0.742\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 85/100 7.22G 0.6856 0.4011 0.8055 418 640: 100%|██████████| 10/10 [00:05<00:00, 1.87it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.64it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.888 0.828 0.885 0.743\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 86/100 7.46G 0.6934 0.401 0.8055 499 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.54it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.892 0.836 0.886 0.744\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 87/100 6.69G 0.6765 0.4031 0.8083 330 640: 100%|██████████| 10/10 [00:05<00:00, 1.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.66it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.871 0.833 0.886 0.742\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 88/100 6.69G 0.6956 0.402 0.8063 338 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.40it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.848 0.851 0.885 0.743\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 89/100 6.84G 0.6897 0.3954 0.8051 548 640: 100%|██████████| 10/10 [00:05<00:00, 1.82it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 4.89it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.847 0.85 0.884 0.745\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 90/100 7.01G 0.6834 0.3944 0.8027 487 640: 100%|██████████| 10/10 [00:05<00:00, 1.85it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.43it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.847 0.85 0.885 0.743\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Closing dataloader mosaic\n",
"\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 91/100 7.07G 0.7066 0.4322 0.8064 258 640: 100%|██████████| 10/10 [00:06<00:00, 1.62it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.47it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.854 0.843 0.886 0.741\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 92/100 7.14G 0.6953 0.4292 0.8056 243 640: 100%|██████████| 10/10 [00:05<00:00, 1.90it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.38it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.869 0.841 0.881 0.735\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 93/100 7.3G 0.6925 0.4265 0.8107 245 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.59it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.882 0.845 0.881 0.731\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 94/100 7.47G 0.6677 0.4092 0.8071 245 640: 100%|██████████| 10/10 [00:05<00:00, 1.90it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.66it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.867 0.835 0.881 0.727\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 95/100 6.72G 0.6685 0.4041 0.8117 237 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.66it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.868 0.834 0.883 0.727\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 96/100 6.72G 0.6579 0.4025 0.8055 247 640: 100%|██████████| 10/10 [00:05<00:00, 1.91it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.66it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.802 0.881 0.886 0.731\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 97/100 6.78G 0.6656 0.4049 0.8075 242 640: 100%|██████████| 10/10 [00:05<00:00, 1.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.69it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.821 0.884 0.883 0.729\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 98/100 6.84G 0.6629 0.4016 0.8054 247 640: 100%|██████████| 10/10 [00:05<00:00, 1.90it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.60it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.824 0.883 0.883 0.729\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 99/100 7.01G 0.6711 0.4068 0.8075 243 640: 100%|██████████| 10/10 [00:05<00:00, 1.89it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.71it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.825 0.883 0.883 0.729\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 100/100 7.07G 0.6348 0.3898 0.8027 248 640: 100%|██████████| 10/10 [00:05<00:00, 1.90it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:00<00:00, 5.60it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.824 0.882 0.886 0.73\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"100 epochs completed in 0.203 hours.\n",
"Optimizer stripped from runs/detect/train/weights/last.pt, 52.1MB\n",
"Optimizer stripped from runs/detect/train/weights/best.pt, 52.1MB\n",
"\n",
"Validating runs/detect/train/weights/best.pt...\n",
"Ultralytics 8.3.170 🚀 Python-3.11.13 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB)\n",
"Model summary (fused): 92 layers, 25,895,344 parameters, 0 gradients, 79.0 GFLOPs\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.30it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 40 949 0.87 0.858 0.888 0.706\n",
" ball_icon_pokeball 16 16 0.828 1 0.988 0.767\n",
" ball_icon_greatball 3 3 1 0.692 0.995 0.813\n",
" ball_icon_ultraball 5 5 0.973 1 0.995 0.78\n",
" ball_icon_masterball 1 1 0 0 0 0\n",
" ball_icon_lureball 1 1 0 0 0 0\n",
" ball_icon_timerball 1 1 1 0 0.995 0.796\n",
" ball_icon_netball 1 1 1 0 0 0\n",
" ball_icon_quickball 2 2 0.41 1 0.995 0.846\n",
" ball_icon_cherishball 9 9 0.876 1 0.995 0.733\n",
" pokemon_nickname 40 40 0.989 1 0.995 0.789\n",
" gender_icon_male 16 16 0.965 1 0.995 0.821\n",
" gender_icon_female 9 9 0.965 1 0.995 0.85\n",
" pokemon_level 39 40 0.897 0.95 0.961 0.405\n",
" language 39 40 0.965 0.975 0.971 0.811\n",
" last_game_stamp_home 1 1 1 0 0 0\n",
" last_game_stamp_sh 9 9 0.957 1 0.995 0.873\n",
" last_game_stamp_bank 13 13 0.9 1 0.962 0.824\n",
" last_game_stamp_pla 1 1 0.618 1 0.995 0.895\n",
" last_game_stamp_sc 13 13 0.898 1 0.941 0.797\n",
" last_game_stamp_vi 1 1 0.757 1 0.995 0.995\n",
" national_dex_number 40 40 0.99 1 0.995 0.795\n",
" pokemon_species 40 40 0.991 1 0.995 0.772\n",
" type_1 40 40 0.992 1 0.995 0.739\n",
" type_2 18 18 0.978 1 0.995 0.745\n",
" shiny_icon 4 4 0.934 1 0.995 0.847\n",
" origin_icon_vc 1 1 0.758 1 0.995 0.796\n",
" origin_icon_xyoras 9 9 0.951 1 0.995 0.818\n",
" origin_icon_smusum 4 4 0.942 1 0.995 0.717\n",
" origin_icon_swsh 11 11 0.973 1 0.995 0.753\n",
" origin_icon_pla 1 1 0.754 1 0.995 0.895\n",
" origin_icon_sv 14 14 0.974 1 0.995 0.892\n",
" hp_value 40 40 0.99 1 0.995 0.682\n",
" attack_value 40 40 0.992 1 0.995 0.759\n",
" defense_value 40 40 0.753 1 0.995 0.792\n",
" sp_atk_value 40 40 0.986 1 0.995 0.656\n",
" sp_def_value 40 40 0.948 1 0.995 0.799\n",
" speed_value 40 40 0.803 1 0.925 0.638\n",
" ability_name 39 39 0.965 0.974 0.973 0.735\n",
" nature_name 40 40 0.994 1 0.995 0.661\n",
" move_name 40 130 0.998 1 0.995 0.776\n",
" original_trainer_name 40 40 0.997 1 0.995 0.607\n",
"original_trainder_number 40 40 0.99 1 0.995 0.839\n",
" tera_water 4 4 0.974 1 0.995 0.718\n",
" tera_fairy 1 1 0.77 1 0.995 0.895\n",
" tera_ghost 1 1 0.765 1 0.995 0.597\n",
" tera_steel 1 1 0.806 1 0.995 0.895\n",
" tera_grass 2 2 0.839 1 0.995 0.796\n",
" tera_normal 3 3 0.913 1 0.995 0.93\n",
" tera_fire 1 1 0.752 1 0.995 0.895\n",
" tera_fighting 1 1 0.768 1 0.995 0.895\n",
" tera_ground 1 1 1 0 0.497 0.448\n",
"ball_icon_pokeball_hisui 1 1 1 0 0.142 0.128\n",
"Speed: 0.1ms preprocess, 29.8ms inference, 0.0ms loss, 2.0ms postprocess per image\n",
"Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
"Ultralytics 8.3.170 🚀 Python-3.11.13 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB)\n",
"Model summary (fused): 92 layers, 25,895,344 parameters, 0 gradients, 79.0 GFLOPs\n",
"\u001b[34m\u001b[1mval: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 3007.2±1192.5 MB/s, size: 776.8 KB)\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mScanning /content/pokemon_yolov8_dataset/labels/train.cache... 155 images, 0 backgrounds, 0 corrupt: 100%|██████████| 155/155 [00:00<?, ?it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223229_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223239_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223243_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223246_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223301_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223304_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223309_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223313_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223317_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223321_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223325_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223328_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223331_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223335_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223338_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223342_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223346_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223355_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223358_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223740_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223748_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223752_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223755_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223758_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223801_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223805_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223813_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223816_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223820_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223829_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223836_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223839_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223843_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223847_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223853_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223856_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223900_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223904_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223910_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223914_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223917_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223920_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223932_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223940_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_223943_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224039_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224217_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224220_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224223_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224227_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224230_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224233_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224243_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224246_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224249_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224252_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224255_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224258_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224307_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224343_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224346_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224349_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224353_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224355_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224358_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224401_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224410_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224413_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224416_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224422_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224426_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224429_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224431_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224434_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224437_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224440_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250724_224500_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250725_074244_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250725_074425_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222229_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222232_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222236_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222239_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222243_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222246_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222256_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222259_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222301_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222306_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222309_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222314_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222317_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222320_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222325_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222328_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222331_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222334_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222337_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222340_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222343_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222347_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222352_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222354_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222357_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222407_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222409_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222414_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222418_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222422_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222425_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222428_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222431_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222434_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222439_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222442_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222445_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222451_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222453_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222456_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222458_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222501_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222503_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222511_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222514_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222519_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222522_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222525_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222527_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222530_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222532_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222535_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222538_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222544_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222553_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222557_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222559_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222602_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222605_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222608_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222613_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222615_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222628_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222631_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222643_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222647_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222653_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222712_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222717_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222739_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222747_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222754_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222811_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222818_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222852_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_yolov8_dataset/images/train/Screenshot_20250726_222903_Pokmon HOME.jpg: corrupt JPEG restored and saved\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"WARNING ⚠️ cache='ram' may produce non-deterministic training results. Consider cache='disk' as a deterministic alternative if your disk space allows.\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mCaching images (0.1GB RAM): 100%|██████████| 155/155 [00:03<00:00, 43.38it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 10/10 [00:08<00:00, 1.13it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 155 3686 0.902 0.883 0.949 0.785\n",
" ball_icon_pokeball 75 75 0.981 1 0.995 0.806\n",
" ball_icon_greatball 5 5 0.661 1 0.766 0.504\n",
" ball_icon_ultraball 19 19 0.815 1 0.986 0.755\n",
" ball_icon_friendball 1 1 1 0 0.497 0.448\n",
" ball_icon_heavyball 4 4 1 0.661 0.995 0.821\n",
" ball_icon_premierball 1 1 1 0 0.995 0.895\n",
" ball_icon_repeatball 1 1 1 0 0.995 0.796\n",
" ball_icon_timerball 1 1 0.94 1 0.995 0.796\n",
" ball_icon_diveball 1 1 1 0 0.497 0.348\n",
" ball_icon_quickball 14 14 0.744 1 0.978 0.698\n",
" ball_icon_duskball 1 1 1 0 0.995 0.895\n",
" ball_icon_cherishball 20 20 0.933 1 0.995 0.77\n",
" pokemon_nickname 155 155 0.997 1 0.995 0.86\n",
" gender_icon_male 69 69 0.968 1 0.995 0.844\n",
" gender_icon_female 50 50 1 0.991 0.995 0.801\n",
" pokemon_level 154 154 0.867 0.981 0.981 0.577\n",
" language 155 155 0.992 1 0.995 0.902\n",
" last_game_stamp_sh 28 28 0.981 1 0.995 0.858\n",
" last_game_stamp_bank 41 41 0.986 1 0.995 0.893\n",
" last_game_stamp_pla 16 16 0.914 1 0.995 0.903\n",
" last_game_stamp_sc 61 61 0.983 1 0.995 0.873\n",
" last_game_stamp_vi 6 6 0.926 1 0.995 0.902\n",
" last_game_stamp_go 3 4 1 0.974 0.995 0.739\n",
" national_dex_number 155 155 0.997 1 0.995 0.913\n",
" pokemon_species 155 155 0.996 1 0.995 0.866\n",
" type_1 153 153 0.986 0.993 0.994 0.791\n",
" type_2 73 73 1 0.968 0.995 0.815\n",
" shiny_icon 22 22 0.989 1 0.995 0.735\n",
" origin_icon_vc 9 9 1 0.949 0.995 0.938\n",
" origin_icon_xyoras 24 24 0.919 0.947 0.973 0.792\n",
" origin_icon_smusum 12 12 0.901 1 0.989 0.832\n",
" origin_icon_swsh 29 29 0.967 1 0.995 0.734\n",
" origin_icon_go 2 2 0.602 1 0.995 0.796\n",
" origin_icon_pla 16 16 0.923 1 0.991 0.889\n",
" origin_icon_sv 61 61 0.993 1 0.995 0.811\n",
" hp_value 155 155 0.997 1 0.995 0.698\n",
" attack_value 153 153 0.983 1 0.992 0.731\n",
" defense_value 155 155 0.954 1 0.995 0.829\n",
" sp_atk_value 153 153 0.983 1 0.989 0.642\n",
" sp_def_value 154 154 0.978 1 0.993 0.772\n",
" speed_value 153 153 0.644 1 0.934 0.674\n",
" ability_name 138 138 0.997 1 0.995 0.774\n",
" nature_name 155 155 0.999 1 0.995 0.662\n",
" move_name 155 482 1 0.996 0.995 0.828\n",
" original_trainer_name 155 155 0.986 0.987 0.987 0.641\n",
"original_trainder_number 155 155 0.997 1 0.995 0.896\n",
" alpha_mark 8 8 0.937 1 0.995 0.835\n",
" tera_water 3 3 0.686 0.667 0.913 0.716\n",
" tera_psychic 2 2 0.811 1 0.995 0.946\n",
" tera_ice 8 8 0.927 1 0.995 0.838\n",
" tera_fairy 5 5 0.878 1 0.995 0.903\n",
" tera_poison 3 3 0.82 1 0.995 0.689\n",
" tera_ghost 5 5 0.9 1 0.995 0.883\n",
" ball_icon_originball 1 1 1 0 0.0663 0.0597\n",
" tera_dragon 2 2 0.813 1 0.995 0.796\n",
" tera_steel 4 4 0.87 1 0.995 0.921\n",
" tera_grass 2 2 0.805 1 0.995 0.895\n",
" tera_normal 5 5 0.882 1 0.995 0.787\n",
" tera_fire 10 10 0.927 1 0.995 0.898\n",
" tera_electric 3 3 0.773 1 0.995 0.909\n",
" tera_fighting 2 2 0.859 1 0.995 0.946\n",
" tera_ground 1 1 0.454 1 0.995 0.995\n",
" tera_flying 3 3 0.556 1 0.995 0.962\n",
" tera_bug 4 4 0.88 1 0.995 0.908\n",
" tera_rock 1 1 0.75 1 0.995 0.895\n",
" tera_dark 2 2 0.8 1 0.995 0.895\n",
"ball_icon_pokeball_hisui 2 2 1 0 0.497 0.411\n",
"ball_icon_ultraball_husui 9 9 0.548 0.943 0.735 0.549\n",
"Speed: 0.1ms preprocess, 26.3ms inference, 0.0ms loss, 7.3ms postprocess per image\n",
"Results saved to \u001b[1mruns/detect/train2\u001b[0m\n",
"\n",
"image 1/1 /content/Screenshot_20250726_222514_Pokmon HOME.jpg: 640x320 1 ball_icon_pokeball, 1 pokemon_nickname, 1 gender_icon_male, 2 pokemon_levels, 1 language, 1 last_game_stamp_sc, 1 national_dex_number, 1 pokemon_species, 1 type_1, 1 origin_icon_sv, 1 hp_value, 1 attack_value, 1 defense_value, 1 sp_atk_value, 1 sp_def_value, 1 speed_value, 1 ability_name, 1 nature_name, 2 move_names, 1 original_trainer_name, 1 original_trainder_number, 1 tera_dragon, 65.7ms\n",
"Speed: 3.4ms preprocess, 65.7ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 320)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<PIL.Image.Image image mode=RGB size=1080x2340>"
],
"image/png": "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
"image/jpeg": "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
},
"metadata": {}
}
],
"source": [
"# 1. Install Ultralytics\n",
"%pip install ultralytics\n",
"\n",
"# 2. Import YOLO\n",
"from ultralytics import YOLO\n",
"import os\n",
"\n",
"# 3. Mount Google Drive (if your dataset is there)\n",
"# from google.colab import drive\n",
"# drive.mount('/content/drive')\n",
"# If using Drive, adjust paths below to /content/drive/MyDrive/path/to/your/dataset\n",
"\n",
"# 4. Define dataset paths (adjust if you uploaded to /content directly)\n",
"# Assuming your dataset is in /content/pokemon_home_dataset\n",
"dataset_path = '/content/pokemon_yolov8_dataset'\n",
"\n",
"# Create dummy dataset.yaml in /content for simplicity, or upload yours\n",
"# You MUST replace the content below with your actual classes and nc\n",
"\n",
"#with open(os.path.join(dataset_path, 'dataset.yaml'), 'w') as f:\n",
"# f.write(dataset_yaml_content)\n",
"\n",
"# 5. Load a pre-trained YOLOv8 model (e.g., yolov8n.pt for nano, or yolov8s.pt for small)\n",
"# 'n' for nano (smallest, fastest, less accurate)\n",
"# 's' for small (good balance)\n",
"# 'm' for medium (more accurate, slower)\n",
"model = YOLO('yolov8m.pt')\n",
"\n",
"# 6. Train the model\n",
"# data: path to your dataset.yaml file\n",
"# epochs: number of training iterations. Start with 50-100, then increase if needed.\n",
"# imgsz: image size for training. 640 is common. Can go higher for small objects.\n",
"# batch: batch size. Adjust based on GPU memory (e.g., 16, 32). Lower if out of memory.\n",
"# patience: Stop training if validation metrics don't improve for this many epochs\n",
"results = model.train(data='/content/dataset.yaml',\n",
" epochs=100,\n",
" imgsz=640,\n",
" batch=16, # Adjust based on your GPU memory\n",
" patience=50, # Stop if no improvement in 50 epochs\n",
" cache=True, # Cache images for faster training\n",
" augment=True, # Data augmentation\n",
" # resume=True # Use if training was interrupted and you want to continue\n",
" split='train')\n",
"\n",
"# 7. Validate the model (optional, happens during train, but you can re-run)\n",
"results = model.val()\n",
"\n",
"# 8. Run inference on a test image (optional)\n",
"results = model('/content/Screenshot_20250726_222514_Pokmon HOME.jpg')\n",
"for r in results:\n",
" r.save_txt('results.txt') # Save results to a file if needed\n",
" r.show() # Display the image with bounding boxes (requires matplotlib)\n",
"\n",
"# The trained model will be saved in `runs/detect/trainX/weights/best.pt`\n",
"# You can download it from Colab's file browser."
]
},
{
"cell_type": "code",
"source": [
"%pip install ultralytics"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "dGYLGqBrKaKa",
"outputId": "c8c50724-d340-4ffa-b299-3b4f116ff905"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting ultralytics\n",
" Downloading ultralytics-8.3.170-py3-none-any.whl.metadata (37 kB)\n",
"Requirement already satisfied: numpy>=1.23.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.0.2)\n",
"Requirement already satisfied: matplotlib>=3.3.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (3.10.0)\n",
"Requirement already satisfied: opencv-python>=4.6.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (4.12.0.88)\n",
"Requirement already satisfied: pillow>=7.1.2 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (11.3.0)\n",
"Requirement already satisfied: pyyaml>=5.3.1 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (6.0.2)\n",
"Requirement already satisfied: requests>=2.23.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.32.3)\n",
"Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (1.16.0)\n",
"Requirement already satisfied: torch>=1.8.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.6.0+cu124)\n",
"Requirement already satisfied: torchvision>=0.9.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (0.21.0+cu124)\n",
"Requirement already satisfied: tqdm>=4.64.0 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (4.67.1)\n",
"Requirement already satisfied: psutil in /usr/local/lib/python3.11/dist-packages (from ultralytics) (5.9.5)\n",
"Requirement already satisfied: py-cpuinfo in /usr/local/lib/python3.11/dist-packages (from ultralytics) (9.0.0)\n",
"Requirement already satisfied: pandas>=1.1.4 in /usr/local/lib/python3.11/dist-packages (from ultralytics) (2.2.2)\n",
"Collecting ultralytics-thop>=2.0.0 (from ultralytics)\n",
" Downloading ultralytics_thop-2.0.14-py3-none-any.whl.metadata (9.4 kB)\n",
"Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.3.2)\n",
"Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (0.12.1)\n",
"Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (4.59.0)\n",
"Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.4.8)\n",
"Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (25.0)\n",
"Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (3.2.3)\n",
"Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.11/dist-packages (from matplotlib>=3.3.0->ultralytics) (2.9.0.post0)\n",
"Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas>=1.1.4->ultralytics) (2025.2)\n",
"Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas>=1.1.4->ultralytics) (2025.2)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests>=2.23.0->ultralytics) (3.4.2)\n",
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests>=2.23.0->ultralytics) (3.10)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests>=2.23.0->ultralytics) (2.5.0)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests>=2.23.0->ultralytics) (2025.7.14)\n",
"Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.18.0)\n",
"Requirement already satisfied: typing-extensions>=4.10.0 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (4.14.1)\n",
"Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.5)\n",
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.1.6)\n",
"Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (2025.3.0)\n",
"Collecting nvidia-cuda-nvrtc-cu12==12.4.127 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
"Collecting nvidia-cuda-runtime-cu12==12.4.127 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
"Collecting nvidia-cuda-cupti-cu12==12.4.127 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
"Collecting nvidia-cudnn-cu12==9.1.0.70 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
"Collecting nvidia-cublas-cu12==12.4.5.8 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
"Collecting nvidia-cufft-cu12==11.2.1.3 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
"Collecting nvidia-curand-cu12==10.3.5.147 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
"Collecting nvidia-cusolver-cu12==11.6.1.9 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
"Collecting nvidia-cusparse-cu12==12.3.1.170 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
"Requirement already satisfied: nvidia-cusparselt-cu12==0.6.2 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (0.6.2)\n",
"Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (2.21.5)\n",
"Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.4.127)\n",
"Collecting nvidia-nvjitlink-cu12==12.4.127 (from torch>=1.8.0->ultralytics)\n",
" Downloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
"Requirement already satisfied: triton==3.2.0 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (3.2.0)\n",
"Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (1.13.1)\n",
"Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch>=1.8.0->ultralytics) (1.3.0)\n",
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.7->matplotlib>=3.3.0->ultralytics) (1.17.0)\n",
"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch>=1.8.0->ultralytics) (3.0.2)\n",
"Downloading ultralytics-8.3.170-py3-none-any.whl (1.0 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m67.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl (363.4 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m3.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (13.8 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.8/13.8 MB\u001b[0m \u001b[31m107.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (24.6 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.6/24.6 MB\u001b[0m \u001b[31m73.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (883 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m883.7/883.7 kB\u001b[0m \u001b[31m64.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl (664.8 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.8/664.8 MB\u001b[0m \u001b[31m2.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl (211.5 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.5/211.5 MB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl (56.3 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.3/56.3 MB\u001b[0m \u001b[31m12.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl (127.9 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m127.9/127.9 MB\u001b[0m \u001b[31m8.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl (207.5 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.5/207.5 MB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (21.1 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m43.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hDownloading ultralytics_thop-2.0.14-py3-none-any.whl (26 kB)\n",
"Installing collected packages: nvidia-nvjitlink-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, ultralytics-thop, ultralytics\n",
" Attempting uninstall: nvidia-nvjitlink-cu12\n",
" Found existing installation: nvidia-nvjitlink-cu12 12.5.82\n",
" Uninstalling nvidia-nvjitlink-cu12-12.5.82:\n",
" Successfully uninstalled nvidia-nvjitlink-cu12-12.5.82\n",
" Attempting uninstall: nvidia-curand-cu12\n",
" Found existing installation: nvidia-curand-cu12 10.3.6.82\n",
" Uninstalling nvidia-curand-cu12-10.3.6.82:\n",
" Successfully uninstalled nvidia-curand-cu12-10.3.6.82\n",
" Attempting uninstall: nvidia-cufft-cu12\n",
" Found existing installation: nvidia-cufft-cu12 11.2.3.61\n",
" Uninstalling nvidia-cufft-cu12-11.2.3.61:\n",
" Successfully uninstalled nvidia-cufft-cu12-11.2.3.61\n",
" Attempting uninstall: nvidia-cuda-runtime-cu12\n",
" Found existing installation: nvidia-cuda-runtime-cu12 12.5.82\n",
" Uninstalling nvidia-cuda-runtime-cu12-12.5.82:\n",
" Successfully uninstalled nvidia-cuda-runtime-cu12-12.5.82\n",
" Attempting uninstall: nvidia-cuda-nvrtc-cu12\n",
" Found existing installation: nvidia-cuda-nvrtc-cu12 12.5.82\n",
" Uninstalling nvidia-cuda-nvrtc-cu12-12.5.82:\n",
" Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.5.82\n",
" Attempting uninstall: nvidia-cuda-cupti-cu12\n",
" Found existing installation: nvidia-cuda-cupti-cu12 12.5.82\n",
" Uninstalling nvidia-cuda-cupti-cu12-12.5.82:\n",
" Successfully uninstalled nvidia-cuda-cupti-cu12-12.5.82\n",
" Attempting uninstall: nvidia-cublas-cu12\n",
" Found existing installation: nvidia-cublas-cu12 12.5.3.2\n",
" Uninstalling nvidia-cublas-cu12-12.5.3.2:\n",
" Successfully uninstalled nvidia-cublas-cu12-12.5.3.2\n",
" Attempting uninstall: nvidia-cusparse-cu12\n",
" Found existing installation: nvidia-cusparse-cu12 12.5.1.3\n",
" Uninstalling nvidia-cusparse-cu12-12.5.1.3:\n",
" Successfully uninstalled nvidia-cusparse-cu12-12.5.1.3\n",
" Attempting uninstall: nvidia-cudnn-cu12\n",
" Found existing installation: nvidia-cudnn-cu12 9.3.0.75\n",
" Uninstalling nvidia-cudnn-cu12-9.3.0.75:\n",
" Successfully uninstalled nvidia-cudnn-cu12-9.3.0.75\n",
" Attempting uninstall: nvidia-cusolver-cu12\n",
" Found existing installation: nvidia-cusolver-cu12 11.6.3.83\n",
" Uninstalling nvidia-cusolver-cu12-11.6.3.83:\n",
" Successfully uninstalled nvidia-cusolver-cu12-11.6.3.83\n",
"Successfully installed nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nvjitlink-cu12-12.4.127 ultralytics-8.3.170 ultralytics-thop-2.0.14\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"from ultralytics import YOLO\n",
"# Load your trained model\n",
"model = YOLO('/content/best.pt')\n",
"\n",
"# Export to TensorFlow Lite (this preserves all your training settings)\n",
"model.export(format='tflite', imgsz=640, int8=False,\n",
" dynamic=False)\n",
"\n",
"print(\"✅ Model exported to pokemon_model.tflite\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "bTgP5_MLKhM0",
"outputId": "b06239e3-7919-4794-a8f4-57b0807870e2"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Creating new Ultralytics Settings v0.0.6 file ✅ \n",
"View Ultralytics Settings with 'yolo settings' or at '/root/.config/Ultralytics/settings.json'\n",
"Update Settings with 'yolo settings key=value', i.e. 'yolo settings runs_dir=path/to/dir'. For help see https://docs.ultralytics.com/quickstart/#ultralytics-settings.\n",
"Ultralytics 8.3.170 🚀 Python-3.11.13 torch-2.6.0+cu124 CPU (Intel Xeon 2.20GHz)\n",
"💡 ProTip: Export to OpenVINO format for best performance on Intel hardware. Learn more at https://docs.ultralytics.com/integrations/openvino/\n",
"Model summary (fused): 92 layers, 25,895,344 parameters, 0 gradients, 79.0 GFLOPs\n",
"\n",
"\u001b[34m\u001b[1mPyTorch:\u001b[0m starting from '/content/best.pt' with input shape (1, 3, 640, 640) BCHW and output shape(s) (1, 100, 8400) (49.7 MB)\n",
"\u001b[31m\u001b[1mrequirements:\u001b[0m Ultralytics requirements ['sng4onnx>=1.0.1', 'onnx_graphsurgeon>=0.3.26', 'ai-edge-litert>=1.2.0,<1.4.0', 'onnx>=1.12.0,<1.18.0', 'onnx2tf>=1.26.3', 'onnxslim>=0.1.59', 'onnxruntime'] not found, attempting AutoUpdate...\n",
"\n",
"\u001b[31m\u001b[1mrequirements:\u001b[0m AutoUpdate success ✅ 4.6s\n",
"WARNING ⚠️ \u001b[31m\u001b[1mrequirements:\u001b[0m \u001b[1mRestart runtime or rerun command for updates to take effect\u001b[0m\n",
"\n",
"\n",
"\u001b[34m\u001b[1mTensorFlow SavedModel:\u001b[0m starting export with tensorflow 2.18.0...\n",
"Downloading https://github.com/ultralytics/assets/releases/download/v8.3.0/calibration_image_sample_data_20x128x128x3_float32.npy.zip to 'calibration_image_sample_data_20x128x128x3_float32.npy.zip'...\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 1.11M/1.11M [00:00<00:00, 103MB/s]\n",
"Unzipping calibration_image_sample_data_20x128x128x3_float32.npy.zip to /content/calibration_image_sample_data_20x128x128x3_float32.npy...: 100%|██████████| 1/1 [00:00<00:00, 39.21file/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"\u001b[34m\u001b[1mONNX:\u001b[0m starting export with onnx 1.17.0 opset 19...\n",
"\u001b[34m\u001b[1mONNX:\u001b[0m slimming with onnxslim 0.1.61...\n",
"\u001b[34m\u001b[1mONNX:\u001b[0m export success ✅ 8.6s, saved as '/content/best.onnx' (99.1 MB)\n",
"\u001b[34m\u001b[1mTensorFlow SavedModel:\u001b[0m starting TFLite export with onnx2tf 1.28.2...\n",
"Saved artifact at '/content/best_saved_model'. The following endpoints are available:\n",
"\n",
"* Endpoint 'serving_default'\n",
" inputs_0 (POSITIONAL_ONLY): TensorSpec(shape=(1, 640, 640, 3), dtype=tf.float32, name='images')\n",
"Output Type:\n",
" TensorSpec(shape=(1, 100, 8400), dtype=tf.float32, name=None)\n",
"Captures:\n",
" 133943829477904: TensorSpec(shape=(4, 2), dtype=tf.int32, name=None)\n",
" 133943829476176: TensorSpec(shape=(3, 3, 3, 48), dtype=tf.float32, name=None)\n",
" 133943829478288: TensorSpec(shape=(48,), dtype=tf.float32, name=None)\n",
" 133943818849168: TensorSpec(shape=(4, 2), dtype=tf.int32, name=None)\n",
" 133943829478096: TensorSpec(shape=(3, 3, 48, 96), dtype=tf.float32, name=None)\n",
" 133943818848784: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943818849744: TensorSpec(shape=(1, 1, 96, 96), dtype=tf.float32, name=None)\n",
" 133943818850128: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943818850704: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818850512: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818853008: TensorSpec(shape=(3, 3, 48, 48), dtype=tf.float32, name=None)\n",
" 133943818853392: TensorSpec(shape=(48,), dtype=tf.float32, name=None)\n",
" 133943818850320: TensorSpec(shape=(3, 3, 48, 48), dtype=tf.float32, name=None)\n",
" 133943818849936: TensorSpec(shape=(48,), dtype=tf.float32, name=None)\n",
" 133943818853776: TensorSpec(shape=(3, 3, 48, 48), dtype=tf.float32, name=None)\n",
" 133943818853584: TensorSpec(shape=(48,), dtype=tf.float32, name=None)\n",
" 133943818851664: TensorSpec(shape=(3, 3, 48, 48), dtype=tf.float32, name=None)\n",
" 133943818852240: TensorSpec(shape=(48,), dtype=tf.float32, name=None)\n",
" 133943818850896: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818851088: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818853968: TensorSpec(shape=(1, 1, 192, 96), dtype=tf.float32, name=None)\n",
" 133943818854544: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943818854736: TensorSpec(shape=(4, 2), dtype=tf.int32, name=None)\n",
" 133943818854160: TensorSpec(shape=(3, 3, 96, 192), dtype=tf.float32, name=None)\n",
" 133943818852048: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943818854928: TensorSpec(shape=(1, 1, 192, 192), dtype=tf.float32, name=None)\n",
" 133943818855312: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943818855888: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818855696: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818856656: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943818858000: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943818855504: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943818855120: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943829479056: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943829466576: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943829470800: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943829471952: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943829473680: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943829474064: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943829471568: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943829473488: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943829473104: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943829473872: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943829477328: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943829472912: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943818856080: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818856272: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943829470608: TensorSpec(shape=(1, 1, 576, 192), dtype=tf.float32, name=None)\n",
" 133943829473296: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943867197584: TensorSpec(shape=(4, 2), dtype=tf.int32, name=None)\n",
" 133943829474256: TensorSpec(shape=(3, 3, 192, 384), dtype=tf.float32, name=None)\n",
" 133943867197392: TensorSpec(shape=(384,), dtype=tf.float32, name=None)\n",
" 133943867196048: TensorSpec(shape=(1, 1, 384, 384), dtype=tf.float32, name=None)\n",
" 133943867196240: TensorSpec(shape=(384,), dtype=tf.float32, name=None)\n",
" 133943818846288: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818858192: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943867196816: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943867195664: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943867196624: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943867196432: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943818859152: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943818858960: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943818858768: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943818856848: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943818859536: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943818859728: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943818846480: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943818859920: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943818860304: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943818860496: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943818859344: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943818860688: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943867195856: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943867829776: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818861264: TensorSpec(shape=(1, 1, 1152, 384), dtype=tf.float32, name=None)\n",
" 133943818861072: TensorSpec(shape=(384,), dtype=tf.float32, name=None)\n",
" 133943818861456: TensorSpec(shape=(4, 2), dtype=tf.int32, name=None)\n",
" 133943818860112: TensorSpec(shape=(3, 3, 384, 576), dtype=tf.float32, name=None)\n",
" 133943818860880: TensorSpec(shape=(576,), dtype=tf.float32, name=None)\n",
" 133943818861648: TensorSpec(shape=(1, 1, 576, 576), dtype=tf.float32, name=None)\n",
" 133943818862032: TensorSpec(shape=(576,), dtype=tf.float32, name=None)\n",
" 133943819584912: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819583568: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943818862224: TensorSpec(shape=(3, 3, 288, 288), dtype=tf.float32, name=None)\n",
" 133943818861840: TensorSpec(shape=(288,), dtype=tf.float32, name=None)\n",
" 133943818862416: TensorSpec(shape=(3, 3, 288, 288), dtype=tf.float32, name=None)\n",
" 133943819585680: TensorSpec(shape=(288,), dtype=tf.float32, name=None)\n",
" 133943819586064: TensorSpec(shape=(3, 3, 288, 288), dtype=tf.float32, name=None)\n",
" 133943819585872: TensorSpec(shape=(288,), dtype=tf.float32, name=None)\n",
" 133943819584336: TensorSpec(shape=(3, 3, 288, 288), dtype=tf.float32, name=None)\n",
" 133943819585104: TensorSpec(shape=(288,), dtype=tf.float32, name=None)\n",
" 133943819583760: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819583952: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819586640: TensorSpec(shape=(1, 1, 1152, 576), dtype=tf.float32, name=None)\n",
" 133943819586448: TensorSpec(shape=(576,), dtype=tf.float32, name=None)\n",
" 133943819584528: TensorSpec(shape=(1, 1, 576, 288), dtype=tf.float32, name=None)\n",
" 133943819586832: TensorSpec(shape=(288,), dtype=tf.float32, name=None)\n",
" 133943819587216: TensorSpec(shape=(1, 1, 1152, 576), dtype=tf.float32, name=None)\n",
" 133943819587024: TensorSpec(shape=(576,), dtype=tf.float32, name=None)\n",
" 133943819587408: TensorSpec(shape=(1, 1, 960, 384), dtype=tf.float32, name=None)\n",
" 133943819587600: TensorSpec(shape=(384,), dtype=tf.float32, name=None)\n",
" 133943819588176: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819587984: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819588944: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943819590288: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819587792: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943819586256: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819589520: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943819590672: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819590480: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943819589712: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819588368: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819588560: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819591248: TensorSpec(shape=(1, 1, 768, 384), dtype=tf.float32, name=None)\n",
" 133943819590864: TensorSpec(shape=(384,), dtype=tf.float32, name=None)\n",
" 133943819589136: TensorSpec(shape=(1, 1, 576, 192), dtype=tf.float32, name=None)\n",
" 133943819591824: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819592016: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819591632: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819592784: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943819594128: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943819591056: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943819591440: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943819593360: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943819594512: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943819594320: TensorSpec(shape=(3, 3, 96, 96), dtype=tf.float32, name=None)\n",
" 133943819593552: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943819592208: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819592400: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819594896: TensorSpec(shape=(1, 1, 384, 192), dtype=tf.float32, name=None)\n",
" 133943819594704: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819595280: TensorSpec(shape=(4, 2), dtype=tf.int32, name=None)\n",
" 133943819595088: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943819592976: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819597008: TensorSpec(shape=(1, 1, 576, 384), dtype=tf.float32, name=None)\n",
" 133943819597200: TensorSpec(shape=(384,), dtype=tf.float32, name=None)\n",
" 133943819598544: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819598160: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819599504: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943819598352: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819599312: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943819598736: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943837491664: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943837492624: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943837493008: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943837493584: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819598928: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943819599120: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943837492816: TensorSpec(shape=(1, 1, 768, 384), dtype=tf.float32, name=None)\n",
" 133943837492240: TensorSpec(shape=(384,), dtype=tf.float32, name=None)\n",
" 133943837493200: TensorSpec(shape=(4, 2), dtype=tf.int32, name=None)\n",
" 133943837493776: TensorSpec(shape=(3, 3, 384, 384), dtype=tf.float32, name=None)\n",
" 133943837492432: TensorSpec(shape=(384,), dtype=tf.float32, name=None)\n",
" 133943837495312: TensorSpec(shape=(1, 1, 960, 576), dtype=tf.float32, name=None)\n",
" 133943837495504: TensorSpec(shape=(576,), dtype=tf.float32, name=None)\n",
" 133943837496848: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943837496464: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943837497040: TensorSpec(shape=(3, 3, 288, 288), dtype=tf.float32, name=None)\n",
" 133943837500304: TensorSpec(shape=(288,), dtype=tf.float32, name=None)\n",
" 133943837498384: TensorSpec(shape=(3, 3, 288, 288), dtype=tf.float32, name=None)\n",
" 133943837499728: TensorSpec(shape=(288,), dtype=tf.float32, name=None)\n",
" 133943837498000: TensorSpec(shape=(3, 3, 288, 288), dtype=tf.float32, name=None)\n",
" 133943837499152: TensorSpec(shape=(288,), dtype=tf.float32, name=None)\n",
" 133943837496656: TensorSpec(shape=(3, 3, 288, 288), dtype=tf.float32, name=None)\n",
" 133943837499536: TensorSpec(shape=(288,), dtype=tf.float32, name=None)\n",
" 133943837497232: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943837497424: TensorSpec(shape=(4,), dtype=tf.int64, name=None)\n",
" 133943837499920: TensorSpec(shape=(1, 1, 1152, 576), dtype=tf.float32, name=None)\n",
" 133943837497808: TensorSpec(shape=(576,), dtype=tf.float32, name=None)\n",
" 133943837500496: TensorSpec(shape=(3, 3, 576, 192), dtype=tf.float32, name=None)\n",
" 133943837498576: TensorSpec(shape=(3, 3, 576, 64), dtype=tf.float32, name=None)\n",
" 133943837494160: TensorSpec(shape=(3, 3, 384, 192), dtype=tf.float32, name=None)\n",
" 133943837493392: TensorSpec(shape=(3, 3, 384, 64), dtype=tf.float32, name=None)\n",
" 133943819595856: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943819595472: TensorSpec(shape=(3, 3, 192, 64), dtype=tf.float32, name=None)\n",
" 133943837499344: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943837500112: TensorSpec(shape=(64,), dtype=tf.float32, name=None)\n",
" 133943837494352: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943837493968: TensorSpec(shape=(64,), dtype=tf.float32, name=None)\n",
" 133943819596048: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819595664: TensorSpec(shape=(64,), dtype=tf.float32, name=None)\n",
" 133943837500688: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943837501072: TensorSpec(shape=(3, 3, 64, 64), dtype=tf.float32, name=None)\n",
" 133943837494544: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943837494736: TensorSpec(shape=(3, 3, 64, 64), dtype=tf.float32, name=None)\n",
" 133943819596240: TensorSpec(shape=(3, 3, 192, 192), dtype=tf.float32, name=None)\n",
" 133943819596432: TensorSpec(shape=(3, 3, 64, 64), dtype=tf.float32, name=None)\n",
" 133943837500880: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943837501264: TensorSpec(shape=(64,), dtype=tf.float32, name=None)\n",
" 133943837494928: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943837495120: TensorSpec(shape=(64,), dtype=tf.float32, name=None)\n",
" 133943819596624: TensorSpec(shape=(192,), dtype=tf.float32, name=None)\n",
" 133943819596816: TensorSpec(shape=(64,), dtype=tf.float32, name=None)\n",
" 133943837501456: TensorSpec(shape=(1, 1, 192, 96), dtype=tf.float32, name=None)\n",
" 133943837501840: TensorSpec(shape=(1, 1, 64, 64), dtype=tf.float32, name=None)\n",
" 133943837495696: TensorSpec(shape=(1, 1, 192, 96), dtype=tf.float32, name=None)\n",
" 133943837496080: TensorSpec(shape=(1, 1, 64, 64), dtype=tf.float32, name=None)\n",
" 133943819597392: TensorSpec(shape=(1, 1, 192, 96), dtype=tf.float32, name=None)\n",
" 133943819597968: TensorSpec(shape=(1, 1, 64, 64), dtype=tf.float32, name=None)\n",
" 133943837502032: TensorSpec(shape=(64,), dtype=tf.float32, name=None)\n",
" 133943837501648: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943837496272: TensorSpec(shape=(64,), dtype=tf.float32, name=None)\n",
" 133943837495888: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943819597584: TensorSpec(shape=(64,), dtype=tf.float32, name=None)\n",
" 133943819597776: TensorSpec(shape=(96,), dtype=tf.float32, name=None)\n",
" 133943837503568: TensorSpec(shape=(3,), dtype=tf.int64, name=None)\n",
" 133943837502800: TensorSpec(shape=(3,), dtype=tf.int64, name=None)\n",
" 133943837505872: TensorSpec(shape=(1, 1, 16, 1), dtype=tf.float32, name=None)\n",
" 133943837505296: TensorSpec(shape=(3,), dtype=tf.int64, name=None)\n",
" 133943837504336: TensorSpec(shape=(3,), dtype=tf.int64, name=None)\n",
" 133943837504144: TensorSpec(shape=(3,), dtype=tf.int64, name=None)\n",
" 133943837504720: TensorSpec(shape=(3,), dtype=tf.int64, name=None)\n",
" 133943837502608: TensorSpec(shape=(1, 2, 8400), dtype=tf.float32, name=None)\n",
" 133943837503952: TensorSpec(shape=(1, 2, 8400), dtype=tf.float32, name=None)\n",
" 133943837503184: TensorSpec(shape=(3,), dtype=tf.int64, name=None)\n",
" 133943837503376: TensorSpec(shape=(3,), dtype=tf.int64, name=None)\n",
"\u001b[34m\u001b[1mTensorFlow SavedModel:\u001b[0m export success ✅ 65.6s, saved as '/content/best_saved_model' (247.9 MB)\n",
"\n",
"\u001b[34m\u001b[1mTensorFlow Lite:\u001b[0m starting export with tensorflow 2.18.0...\n",
"\u001b[34m\u001b[1mTensorFlow Lite:\u001b[0m export success ✅ 0.0s, saved as '/content/best_saved_model/best_float32.tflite' (99.0 MB)\n",
"\n",
"Export complete (69.8s)\n",
"Results saved to \u001b[1m/content\u001b[0m\n",
"Predict: yolo predict task=detect model=/content/best_saved_model/best_float32.tflite imgsz=640 \n",
"Validate: yolo val task=detect model=/content/best_saved_model/best_float32.tflite imgsz=640 data=/content/dataset.yaml \n",
"Visualize: https://netron.app\n",
"✅ Model exported to pokemon_model.tflite\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"from ultralytics import YOLO\n",
"model = YOLO('/content/best.pt')\n",
"model.export(format='onnx', imgsz=640, opset=11, nms=True)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "9XOKqrADggul",
"outputId": "5592c993-0b21-4d1a-8328-c97e35d9d183"
},
"execution_count": null,
"outputs": [
{
"output_type": "error",
"ename": "SyntaxError",
"evalue": "'\u001b[31m\u001b[1mNMS\u001b[0m' is not a valid YOLO argument. \n\n Arguments received: ['yolo', '-f', '/root/.local/share/jupyter/runtime/kernel-885097ea-eb66-4d24-8292-f730c2210699.json']. Ultralytics 'yolo' commands use the following syntax:\n\n yolo TASK MODE ARGS\n\n Where TASK (optional) is one of ['classify', 'segment', 'detect', 'pose', 'obb']\n MODE (required) is one of ['predict', 'val', 'export', 'track', 'train', 'benchmark']\n ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.\n See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg'\n\n 1. Train a detection model for 10 epochs with an initial learning_rate of 0.01\n yolo train data=coco8.yaml model=yolo11n.pt epochs=10 lr0=0.01\n\n 2. Predict a YouTube video using a pretrained segmentation model at image size 320:\n yolo predict model=yolo11n-seg.pt source='https://youtu.be/LNwODJXcvt4' imgsz=320\n\n 3. Val a pretrained detection model at batch-size 1 and image size 640:\n yolo val model=yolo11n.pt data=coco8.yaml batch=1 imgsz=640\n\n 4. Export a YOLO11n classification model to ONNX format at image size 224 by 128 (no TASK required)\n yolo export model=yolo11n-cls.pt format=onnx imgsz=224,128\n\n 5. Ultralytics solutions usage\n yolo solutions count or in ['crop', 'blur', 'workout', 'heatmap', 'isegment', 'visioneye', 'speed', 'queue', 'analytics', 'inference', 'trackzone'] source=\"path/to/video.mp4\"\n\n 6. Run special commands:\n yolo help\n yolo checks\n yolo version\n yolo settings\n yolo copy-cfg\n yolo cfg\n yolo solutions help\n\n Docs: https://docs.ultralytics.com\n Solutions: https://docs.ultralytics.com/solutions/\n Community: https://community.ultralytics.com\n GitHub: https://github.com/ultralytics/ultralytics\n (<string>)",
"traceback": [
"Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
" File \u001b[1;32m\"/usr/local/lib/python3.11/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m3553\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n exec(code_obj, self.user_global_ns, self.user_ns)\n",
" File \u001b[1;32m\"/tmp/ipython-input-3-1893694433.py\"\u001b[0m, line \u001b[1;32m3\u001b[0m, in \u001b[1;35m<cell line: 0>\u001b[0m\n model.export(format='onnx', imgsz=640, opset=11, NMS=True)\n",
" File \u001b[1;32m\"/usr/local/lib/python3.11/dist-packages/ultralytics/engine/model.py\"\u001b[0m, line \u001b[1;32m734\u001b[0m, in \u001b[1;35mexport\u001b[0m\n return Exporter(overrides=args, _callbacks=self.callbacks)(model=self.model)\n",
" File \u001b[1;32m\"/usr/local/lib/python3.11/dist-packages/ultralytics/engine/exporter.py\"\u001b[0m, line \u001b[1;32m263\u001b[0m, in \u001b[1;35m__init__\u001b[0m\n self.args = get_cfg(cfg, overrides)\n",
" File \u001b[1;32m\"/usr/local/lib/python3.11/dist-packages/ultralytics/cfg/__init__.py\"\u001b[0m, line \u001b[1;32m305\u001b[0m, in \u001b[1;35mget_cfg\u001b[0m\n check_dict_alignment(cfg, overrides)\n",
"\u001b[0;36m File \u001b[0;32m\"/usr/local/lib/python3.11/dist-packages/ultralytics/cfg/__init__.py\"\u001b[0;36m, line \u001b[0;32m498\u001b[0;36m, in \u001b[0;35mcheck_dict_alignment\u001b[0;36m\u001b[0m\n\u001b[0;31m raise SyntaxError(string + CLI_HELP_MSG) from e\u001b[0m\n",
"\u001b[0;36m File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32munknown\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m '\u001b[31m\u001b[1mNMS\u001b[0m' is not a valid YOLO argument. \n\n Arguments received: ['yolo', '-f', '/root/.local/share/jupyter/runtime/kernel-885097ea-eb66-4d24-8292-f730c2210699.json']. Ultralytics 'yolo' commands use the following syntax:\n\n yolo TASK MODE ARGS\n\n Where TASK (optional) is one of ['classify', 'segment', 'detect', 'pose', 'obb']\n MODE (required) is one of ['predict', 'val', 'export', 'track', 'train', 'benchmark']\n ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.\n See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg'\n\n 1. Train a detection model for 10 epochs with an initial learning_rate of 0.01\n yolo train data=coco8.yaml model=yolo11n.pt epochs=10 lr0=0.01\n\n 2. Predict a YouTube video using a pretrained segmentation model at image size 320:\n yolo predict model=yolo11n-seg.pt source='https://youtu.be/LNwODJXcvt4' imgsz=320\n\n 3. Val a pretrained detection model at batch-size 1 and image size 640:\n yolo val model=yolo11n.pt data=coco8.yaml batch=1 imgsz=640\n\n 4. Export a YOLO11n classification model to ONNX format at image size 224 by 128 (no TASK required)\n yolo export model=yolo11n-cls.pt format=onnx imgsz=224,128\n\n 5. Ultralytics solutions usage\n yolo solutions count or in ['crop', 'blur', 'workout', 'heatmap', 'isegment', 'visioneye', 'speed', 'queue', 'analytics', 'inference', 'trackzone'] source=\"path/to/video.mp4\"\n\n 6. Run special commands:\n yolo help\n yolo checks\n yolo version\n yolo settings\n yolo copy-cfg\n yolo cfg\n yolo solutions help\n\n Docs: https://docs.ultralytics.com\n Solutions: https://docs.ultralytics.com/solutions/\n Community: https://community.ultralytics.com\n GitHub: https://github.com/ultralytics/ultralytics\n \n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "62db4a4c"
},
"source": [
"dataset_yaml_content = \"\"\"\n",
"train: /content/pokemon_home_dataset/images/train\n",
"val: /content/pokemon_home_dataset/images/val\n",
"nc: 73\n",
"\n",
"# Class names (must be in the same order as LabelImg assigned them internally)\n",
"names: [\n",
" 'ball_icon_pokeball', 'ball_icon_greatball', 'ball_icon_ultraball', 'ball_icon_masterball',\n",
" 'ball_icon_safariball', 'ball_icon_levelball', 'ball_icon_lureball', 'ball_icon_moonball',\n",
" 'ball_icon_friendball', 'ball_icon_loveball', 'ball_icon_heavyball', 'ball_icon_fastball',\n",
" 'ball_icon_sportball', 'ball_icon_premierball', 'ball_icon_repeatball', 'ball_icon_timerball',\n",
" 'ball_icon_nestball', 'ball_icon_netball', 'ball_icon_diveball', 'ball_icon_luxuryball',\n",
" 'ball_icon_healball', 'ball_icon_quickball', 'ball_icon_duskball', 'ball_icon_cherishball',\n",
" 'ball_icon_dreamball', 'ball_icon_beastball', 'ball_icon_strangeparts', 'ball_icon_parkball',\n",
" 'ball_icon_gsball', 'pokemon_nickname', 'gender_icon_male', 'gender_icon_female',\n",
" 'pokemon_level', 'language', 'last_game_stamp_home', 'last_game_stamp_lgp',\n",
" 'last_game_stamp_lge', 'last_game_stamp_sw', 'last_game_stamp_sh', 'last_game_stamp_bank',\n",
" 'last_game_stamp_bd', 'last_game_stamp_sp', 'last_game_stamp_pla', 'last_game_stamp_sc',\n",
" 'last_game_stamp_vi', 'last_game_stamp_go', 'national_dex_number', 'pokemon_species',\n",
" 'type_1', 'type_2', 'shiny_icon', 'origin_icon_vc', 'origin_icon_xyoras',\n",
" 'origin_icon_smusum', 'origin_icon_lg', 'origin_icon_swsh', 'origin_icon_go',\n",
" 'origin_icon_bdsp', 'origin_icon_pla', 'origin_icon_sv', 'pokerus_infected_icon',\n",
" 'pokerus_cured_icon', 'hp_value', 'attack_value', 'defense_value', 'sp_atk_value',\n",
" 'sp_def_value', 'speed_value', 'ability_name', 'nature_name', 'move_name',\n",
" 'original_trainer_name', 'original_trainder_number'\n",
"]\n",
"\"\"\"\n",
"\n",
"with open('/content/dataset.yaml', 'w') as f:\n",
" f.write(dataset_yaml_content)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "7d1d723a"
},
"source": [
"## 2. Train Model\n",
"Now, we'll train the YOLOv8 model on our dataset. We are using data augmentation to help the model generalize better and avoid overfitting."
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "776b2fe4",
"outputId": "87aeb656-01ce-482c-8f84-4930da5b0d92",
"collapsed": true
},
"source": [
"from ultralytics import YOLO\n",
"\n",
"# Load a pre-trained YOLOv8 model\n",
"model = YOLO('yolov8n.pt')\n",
"\n",
"# Train the model\n",
"results = model.train(\n",
" data='/content/dataset.yaml',\n",
" epochs=100,\n",
" imgsz=640,\n",
" batch=16,\n",
" patience=50,\n",
" cache=True,\n",
" augment=True, # Enable data augmentation\n",
" split='train'\n",
")"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Ultralytics 8.3.169 🚀 Python-3.11.13 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB)\n",
"\u001b[34m\u001b[1mengine/trainer: \u001b[0magnostic_nms=False, amp=True, augment=True, auto_augment=randaugment, batch=16, bgr=0.0, box=7.5, cache=True, cfg=None, classes=None, close_mosaic=10, cls=0.5, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/content/dataset.yaml, degrees=0.0, deterministic=True, device=None, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=100, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, int8=False, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=yolov8n.pt, momentum=0.937, mosaic=1.0, multi_scale=False, name=train8, nbs=64, nms=False, opset=None, optimize=False, optimizer=auto, overlap_mask=True, patience=50, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=None, rect=False, resume=False, retina_masks=False, save=True, save_conf=False, save_crop=False, save_dir=runs/detect/train8, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=train, stream_buffer=False, task=detect, time=None, tracker=botsort.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=8, workspace=None\n",
"Overriding model.yaml nc=80 with nc=73\n",
"\n",
" from n params module arguments \n",
" 0 -1 1 464 ultralytics.nn.modules.conv.Conv [3, 16, 3, 2] \n",
" 1 -1 1 4672 ultralytics.nn.modules.conv.Conv [16, 32, 3, 2] \n",
" 2 -1 1 7360 ultralytics.nn.modules.block.C2f [32, 32, 1, True] \n",
" 3 -1 1 18560 ultralytics.nn.modules.conv.Conv [32, 64, 3, 2] \n",
" 4 -1 2 49664 ultralytics.nn.modules.block.C2f [64, 64, 2, True] \n",
" 5 -1 1 73984 ultralytics.nn.modules.conv.Conv [64, 128, 3, 2] \n",
" 6 -1 2 197632 ultralytics.nn.modules.block.C2f [128, 128, 2, True] \n",
" 7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2] \n",
" 8 -1 1 460288 ultralytics.nn.modules.block.C2f [256, 256, 1, True] \n",
" 9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5] \n",
" 10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n",
" 11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
" 12 -1 1 148224 ultralytics.nn.modules.block.C2f [384, 128, 1] \n",
" 13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n",
" 14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
" 15 -1 1 37248 ultralytics.nn.modules.block.C2f [192, 64, 1] \n",
" 16 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2] \n",
" 17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
" 18 -1 1 123648 ultralytics.nn.modules.block.C2f [192, 128, 1] \n",
" 19 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2] \n",
" 20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
" 21 -1 1 493056 ultralytics.nn.modules.block.C2f [384, 256, 1] \n",
" 22 [15, 18, 21] 1 837205 ultralytics.nn.modules.head.Detect [73, [64, 128, 256]] \n",
"Model summary: 129 layers, 3,096,741 parameters, 3,096,725 gradients, 8.6 GFLOPs\n",
"\n",
"Transferred 319/355 items from pretrained weights\n",
"Freezing layer 'model.22.dfl.conv.weight'\n",
"\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks...\n",
"\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n",
"\u001b[34m\u001b[1mtrain: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 3120.7±375.0 MB/s, size: 859.4 KB)\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/pokemon_home_dataset/labels/train.cache... 8 images, 0 backgrounds, 0 corrupt: 100%|██████████| 8/8 [00:00<?, ?it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_home_dataset/images/train/Screenshot_20250724_223222_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_home_dataset/images/train/Screenshot_20250724_223229_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_home_dataset/images/train/Screenshot_20250724_223239_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_home_dataset/images/train/Screenshot_20250724_223246_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_home_dataset/images/train/Screenshot_20250724_223250_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_home_dataset/images/train/Screenshot_20250724_223257_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_home_dataset/images/train/Screenshot_20250724_223301_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mtrain: \u001b[0m/content/pokemon_home_dataset/images/train/Screenshot_20250724_223304_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"WARNING ⚠️ cache='ram' may produce non-deterministic training results. Consider cache='disk' as a deterministic alternative if your disk space allows.\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n",
"\u001b[34m\u001b[1mtrain: \u001b[0mCaching images (0.0GB RAM): 100%|██████████| 8/8 [00:00<00:00, 51.66it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 768.8±23.4 MB/s, size: 809.4 KB)\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mScanning /content/pokemon_home_dataset/labels/val.cache... 2 images, 0 backgrounds, 0 corrupt: 100%|██████████| 2/2 [00:00<?, ?it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_home_dataset/images/val/Screenshot_20250724_223243_Pokmon HOME.jpg: corrupt JPEG restored and saved\n",
"\u001b[34m\u001b[1mval: \u001b[0m/content/pokemon_home_dataset/images/val/Screenshot_20250724_223254_Pokmon HOME.jpg: corrupt JPEG restored and saved\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"WARNING ⚠️ cache='ram' may produce non-deterministic training results. Consider cache='disk' as a deterministic alternative if your disk space allows.\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mCaching images (0.0GB RAM): 100%|██████████| 2/2 [00:00<00:00, 22.36it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Plotting labels to runs/detect/train8/labels.jpg... \n",
"\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n",
"\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.00013, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n",
"Image sizes 640 train, 640 val\n",
"Using 2 dataloader workers\n",
"Logging results to \u001b[1mruns/detect/train8\u001b[0m\n",
"Starting training for 100 epochs...\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 1/100 1.28G 2.701 5.839 1.333 297 640: 100%|██████████| 1/1 [00:00<00:00, 5.10it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.15it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 2/100 1.42G 3.084 5.879 1.348 434 640: 100%|██████████| 1/1 [00:00<00:00, 3.47it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 20.02it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 3/100 1.42G 2.708 5.865 1.391 396 640: 100%|██████████| 1/1 [00:00<00:00, 6.92it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.59it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 4/100 1.42G 2.542 5.87 1.3 312 640: 100%|██████████| 1/1 [00:00<00:00, 6.50it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.42it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 5/100 1.42G 2.853 5.856 1.356 380 640: 100%|██████████| 1/1 [00:00<00:00, 6.93it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 32.04it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 6/100 1.42G 2.782 5.917 1.34 417 640: 100%|██████████| 1/1 [00:00<00:00, 6.54it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.24it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 7/100 1.42G 2.561 5.852 1.301 334 640: 100%|██████████| 1/1 [00:00<00:00, 7.39it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 25.87it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 8/100 1.42G 2.735 5.859 1.278 384 640: 100%|██████████| 1/1 [00:00<00:00, 6.15it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 26.60it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 9/100 1.42G 2.678 5.867 1.308 321 640: 100%|██████████| 1/1 [00:00<00:00, 6.43it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.57it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 10/100 1.42G 2.141 5.814 1.216 203 640: 100%|██████████| 1/1 [00:00<00:00, 7.07it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.13it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 11/100 1.42G 2.357 5.815 1.251 260 640: 100%|██████████| 1/1 [00:00<00:00, 5.40it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 12.33it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 12/100 1.42G 2.467 5.798 1.229 329 640: 100%|██████████| 1/1 [00:00<00:00, 3.76it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 25.95it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 13/100 1.42G 2.529 5.821 1.237 378 640: 100%|██████████| 1/1 [00:00<00:00, 4.02it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 19.57it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 14/100 1.42G 2.68 5.81 1.301 391 640: 100%|██████████| 1/1 [00:00<00:00, 4.14it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.96it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 15/100 1.44G 2.221 5.756 1.149 295 640: 100%|██████████| 1/1 [00:00<00:00, 5.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 30.74it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 16/100 1.45G 2.299 5.785 1.169 357 640: 100%|██████████| 1/1 [00:00<00:00, 5.51it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 16.02it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 17/100 1.45G 2.078 5.74 1.115 348 640: 100%|██████████| 1/1 [00:00<00:00, 6.38it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 29.50it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 18/100 1.46G 2.108 5.739 1.128 316 640: 100%|██████████| 1/1 [00:00<00:00, 8.89it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.47it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 19/100 1.48G 2.612 5.761 1.254 401 640: 100%|██████████| 1/1 [00:00<00:00, 6.01it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.87it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 20/100 1.49G 2.285 5.673 1.128 320 640: 100%|██████████| 1/1 [00:00<00:00, 7.50it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.88it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 21/100 1.5G 2.156 5.7 1.081 346 640: 100%|██████████| 1/1 [00:00<00:00, 6.77it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.50it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 22/100 1.5G 2.345 5.743 1.147 408 640: 100%|██████████| 1/1 [00:00<00:00, 8.08it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.89it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 23/100 1.5G 2.108 5.672 1.066 342 640: 100%|██████████| 1/1 [00:00<00:00, 6.63it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 32.31it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 24/100 1.51G 2.232 5.71 1.101 390 640: 100%|██████████| 1/1 [00:00<00:00, 8.01it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 19.80it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 25/100 1.53G 2.034 5.67 1.081 332 640: 100%|██████████| 1/1 [00:00<00:00, 6.91it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.90it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 26/100 1.53G 2.08 5.673 1.086 378 640: 100%|██████████| 1/1 [00:00<00:00, 8.53it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 26.13it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 27/100 1.54G 1.663 5.654 1.008 252 640: 100%|██████████| 1/1 [00:00<00:00, 6.89it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 32.01it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 28/100 1.54G 1.801 5.565 1.02 299 640: 100%|██████████| 1/1 [00:00<00:00, 7.11it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 30.49it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 29/100 1.54G 1.776 5.614 1.01 254 640: 100%|██████████| 1/1 [00:00<00:00, 6.31it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.47it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 30/100 1.54G 1.997 5.628 1.043 405 640: 100%|██████████| 1/1 [00:00<00:00, 8.21it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.07it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 31/100 1.54G 1.989 5.616 1.066 400 640: 100%|██████████| 1/1 [00:00<00:00, 6.07it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.89it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 32/100 1.54G 2.073 5.613 1.063 421 640: 100%|██████████| 1/1 [00:00<00:00, 8.14it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 27.16it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 33/100 1.54G 1.831 5.582 1.037 318 640: 100%|██████████| 1/1 [00:00<00:00, 6.58it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.09it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 34/100 1.54G 1.922 5.556 1.004 384 640: 100%|██████████| 1/1 [00:00<00:00, 8.55it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 23.58it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 35/100 1.54G 1.771 5.564 0.9735 293 640: 100%|██████████| 1/1 [00:00<00:00, 6.86it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 32.07it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 36/100 1.54G 1.656 5.53 0.9636 308 640: 100%|██████████| 1/1 [00:00<00:00, 7.03it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 30.17it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 37/100 1.54G 1.68 5.484 0.9951 325 640: 100%|██████████| 1/1 [00:00<00:00, 6.37it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.12it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 38/100 1.54G 1.829 5.504 0.9899 337 640: 100%|██████████| 1/1 [00:00<00:00, 8.25it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 18.04it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 39/100 1.54G 1.817 5.459 0.9962 405 640: 100%|██████████| 1/1 [00:00<00:00, 4.93it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 20.30it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 40/100 1.54G 1.824 5.426 1.009 388 640: 100%|██████████| 1/1 [00:00<00:00, 5.06it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 16.98it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 41/100 1.54G 1.714 5.426 0.9888 377 640: 100%|██████████| 1/1 [00:00<00:00, 3.77it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 19.67it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 42/100 1.54G 1.495 5.409 0.9382 231 640: 100%|██████████| 1/1 [00:00<00:00, 7.67it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.41it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 43/100 1.54G 1.985 5.461 1.001 428 640: 100%|██████████| 1/1 [00:00<00:00, 6.52it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 26.19it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 44/100 1.54G 1.607 5.39 0.9532 336 640: 100%|██████████| 1/1 [00:00<00:00, 7.17it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.12it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 45/100 1.54G 1.647 5.443 0.9449 280 640: 100%|██████████| 1/1 [00:00<00:00, 6.39it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 30.92it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 46/100 1.54G 1.771 5.353 0.9602 333 640: 100%|██████████| 1/1 [00:00<00:00, 8.46it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 18.04it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 47/100 1.54G 1.587 5.324 0.9284 332 640: 100%|██████████| 1/1 [00:00<00:00, 6.57it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 27.54it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 48/100 1.54G 1.368 5.23 0.8779 245 640: 100%|██████████| 1/1 [00:00<00:00, 7.47it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 28.30it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 49/100 1.63G 2.024 5.398 0.9967 486 640: 100%|██████████| 1/1 [00:00<00:00, 6.45it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.45it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 50/100 1.63G 2 5.275 0.9715 426 640: 100%|██████████| 1/1 [00:00<00:00, 8.41it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 26.66it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 51/100 1.63G 1.833 5.298 0.9607 428 640: 100%|██████████| 1/1 [00:00<00:00, 6.49it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.57it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 52/100 1.63G 1.562 5.259 0.9288 312 640: 100%|██████████| 1/1 [00:00<00:00, 6.91it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 27.64it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 53/100 1.63G 1.851 5.312 0.9838 438 640: 100%|██████████| 1/1 [00:00<00:00, 7.63it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 19.54it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 54/100 1.63G 1.656 5.191 0.9269 324 640: 100%|██████████| 1/1 [00:00<00:00, 6.53it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.98it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 55/100 1.63G 1.637 5.175 0.9084 395 640: 100%|██████████| 1/1 [00:00<00:00, 8.12it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 26.93it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 56/100 1.63G 1.55 5.208 0.9047 265 640: 100%|██████████| 1/1 [00:00<00:00, 7.64it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 23.70it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 57/100 1.63G 1.55 5.163 0.9096 260 640: 100%|██████████| 1/1 [00:00<00:00, 7.16it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 29.40it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 58/100 1.63G 1.801 5.212 0.9317 296 640: 100%|██████████| 1/1 [00:00<00:00, 8.37it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.23it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 59/100 1.63G 1.709 5.216 0.9342 351 640: 100%|██████████| 1/1 [00:00<00:00, 7.63it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 29.79it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 60/100 1.63G 1.412 5.08 0.8985 248 640: 100%|██████████| 1/1 [00:00<00:00, 7.00it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 28.93it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 61/100 1.63G 1.575 5.133 0.9197 372 640: 100%|██████████| 1/1 [00:00<00:00, 8.43it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 23.69it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 62/100 1.63G 1.251 5.013 0.8789 234 640: 100%|██████████| 1/1 [00:00<00:00, 6.84it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 29.13it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 63/100 1.63G 1.538 5.022 0.8917 287 640: 100%|██████████| 1/1 [00:00<00:00, 6.54it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 30.25it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 64/100 1.63G 1.905 5.087 0.9456 390 640: 100%|██████████| 1/1 [00:00<00:00, 6.22it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 23.71it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 65/100 1.63G 1.741 5.096 0.9266 421 640: 100%|██████████| 1/1 [00:00<00:00, 5.57it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 20.91it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 66/100 1.63G 1.418 5.017 0.9073 230 640: 100%|██████████| 1/1 [00:00<00:00, 3.49it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 19.57it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 67/100 1.63G 1.53 4.993 0.9008 293 640: 100%|██████████| 1/1 [00:00<00:00, 5.67it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.25it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 68/100 1.63G 1.555 5.043 0.9133 353 640: 100%|██████████| 1/1 [00:00<00:00, 7.72it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 30.24it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 69/100 1.63G 1.824 4.997 0.9379 405 640: 100%|██████████| 1/1 [00:00<00:00, 6.56it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.06it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 70/100 1.63G 1.633 4.908 0.8957 361 640: 100%|██████████| 1/1 [00:00<00:00, 6.94it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 27.73it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 71/100 1.63G 1.562 4.977 0.9201 303 640: 100%|██████████| 1/1 [00:00<00:00, 8.24it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 26.14it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 72/100 1.63G 1.391 4.842 0.8666 269 640: 100%|██████████| 1/1 [00:00<00:00, 6.92it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 31.08it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 73/100 1.63G 1.589 4.946 0.9194 270 640: 100%|██████████| 1/1 [00:00<00:00, 9.03it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 19.17it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 74/100 1.63G 1.67 4.934 0.9016 314 640: 100%|██████████| 1/1 [00:00<00:00, 8.37it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.30it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 75/100 1.63G 1.378 4.927 0.8773 225 640: 100%|██████████| 1/1 [00:00<00:00, 6.63it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 30.13it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 76/100 1.63G 1.632 4.962 0.9108 407 640: 100%|██████████| 1/1 [00:00<00:00, 7.93it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 33.23it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 77/100 1.63G 1.563 4.914 0.9003 391 640: 100%|██████████| 1/1 [00:00<00:00, 8.77it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 23.90it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 78/100 1.63G 1.625 4.883 0.891 345 640: 100%|██████████| 1/1 [00:00<00:00, 6.79it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 26.87it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 79/100 1.63G 1.627 4.88 0.8899 326 640: 100%|██████████| 1/1 [00:00<00:00, 8.59it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 24.67it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 80/100 1.63G 1.604 4.986 0.9032 415 640: 100%|██████████| 1/1 [00:00<00:00, 8.57it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 28.13it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0 0 0 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 81/100 1.63G 1.645 4.903 0.9016 350 640: 100%|██████████| 1/1 [00:00<00:00, 4.30it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.99it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0417 0.00521 0.0234 0.0187\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 82/100 1.63G 1.588 4.774 0.8798 296 640: 100%|██████████| 1/1 [00:00<00:00, 4.31it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 23.38it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0417 0.00521 0.0234 0.0187\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 83/100 1.63G 1.489 4.78 0.8784 260 640: 100%|██████████| 1/1 [00:00<00:00, 4.39it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.37it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0417 0.00521 0.0234 0.0187\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 84/100 1.63G 1.561 4.891 0.8893 324 640: 100%|██████████| 1/1 [00:00<00:00, 4.81it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 18.72it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0312 0.0156 0.0254 0.0196\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 85/100 1.63G 1.515 4.845 0.8898 353 640: 100%|██████████| 1/1 [00:00<00:00, 7.97it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 18.09it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0312 0.0156 0.0254 0.0196\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 86/100 1.63G 1.38 4.834 0.9037 372 640: 100%|██████████| 1/1 [00:00<00:00, 8.34it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 20.01it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0312 0.0156 0.0254 0.0196\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 87/100 1.63G 1.579 4.806 0.8939 356 640: 100%|██████████| 1/1 [00:00<00:00, 8.14it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 24.46it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0312 0.0156 0.0254 0.0196\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 88/100 1.63G 1.386 4.909 0.8842 303 640: 100%|██████████| 1/1 [00:00<00:00, 6.71it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 28.38it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0312 0.0156 0.0254 0.0203\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 89/100 1.63G 1.598 4.749 0.9245 324 640: 100%|██████████| 1/1 [00:00<00:00, 6.88it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 27.41it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0312 0.0156 0.0254 0.0203\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 90/100 1.63G 1.69 4.862 0.9403 394 640: 100%|██████████| 1/1 [00:00<00:00, 7.83it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 18.57it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0312 0.0156 0.0254 0.0203\n",
"Closing dataloader mosaic\n",
"\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n",
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 91/100 1.63G 1.314 4.574 0.8447 174 640: 100%|██████████| 1/1 [00:00<00:00, 3.25it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 10.59it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0312 0.0156 0.0254 0.0203\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 92/100 1.63G 1.509 4.562 0.8561 176 640: 100%|██████████| 1/1 [00:00<00:00, 6.46it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 16.82it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0333 0.0208 0.0281 0.0225\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 93/100 1.63G 1.385 4.541 0.8649 167 640: 100%|██████████| 1/1 [00:00<00:00, 8.44it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 16.56it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0333 0.0208 0.0281 0.0225\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 94/100 1.63G 1.699 4.634 0.8993 184 640: 100%|██████████| 1/1 [00:00<00:00, 7.62it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 24.56it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0333 0.0208 0.0281 0.0225\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 95/100 1.63G 1.402 4.566 0.8552 174 640: 100%|██████████| 1/1 [00:00<00:00, 8.21it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.84it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0333 0.0208 0.0281 0.0225\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 96/100 1.63G 1.684 4.546 0.8693 185 640: 100%|██████████| 1/1 [00:00<00:00, 7.06it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 25.88it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0278 0.0312 0.0325 0.0243\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 97/100 1.63G 1.495 4.595 0.8552 180 640: 100%|██████████| 1/1 [00:00<00:00, 8.66it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.43it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0278 0.0312 0.0325 0.0243\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 98/100 1.63G 1.772 4.61 0.8904 185 640: 100%|██████████| 1/1 [00:00<00:00, 9.48it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 20.57it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0278 0.0312 0.0325 0.0243\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 99/100 1.63G 1.323 4.565 0.8469 175 640: 100%|██████████| 1/1 [00:00<00:00, 8.12it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 19.76it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0278 0.0312 0.0325 0.0243\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
" Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" 100/100 1.63G 1.518 4.508 0.8848 170 640: 100%|██████████| 1/1 [00:00<00:00, 7.19it/s]\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 25.97it/s]"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.0227 0.0312 0.031 0.0243\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"100 epochs completed in 0.022 hours.\n",
"Optimizer stripped from runs/detect/train8/weights/last.pt, 6.4MB\n",
"Optimizer stripped from runs/detect/train8/weights/best.pt, 6.4MB\n",
"\n",
"Validating runs/detect/train8/weights/best.pt...\n",
"Ultralytics 8.3.169 🚀 Python-3.11.13 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB)\n",
"Model summary (fused): 72 layers, 3,091,487 parameters, 0 gradients, 8.5 GFLOPs\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 19.23it/s]\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
" all 2 48 0.025 0.0312 0.0321 0.0246\n",
" ball_icon_pokeball 1 1 0 0 0 0\n",
" ball_icon_cherishball 1 1 0 0 0 0\n",
" pokemon_nickname 2 2 0 0 0 0\n",
" gender_icon_male 1 1 0 0 0 0\n",
" pokemon_level 2 3 0 0 0 0\n",
" language 1 1 0 0 0 0\n",
" last_game_stamp_bank 2 2 0 0 0 0\n",
" national_dex_number 2 2 0 0 0 0\n",
" pokemon_species 2 2 0 0 0 0\n",
" type_1 2 2 0 0 0 0\n",
" type_2 1 1 0 0 0 0\n",
" origin_icon_vc 1 1 0 0 0 0\n",
" origin_icon_xyoras 1 1 0 0 0 0\n",
" hp_value 2 2 0 0 0 0\n",
" attack_value 2 2 0 0 0 0\n",
" defense_value 2 2 0 0 0 0\n",
" sp_atk_value 2 2 0 0 0 0\n",
" sp_def_value 2 2 0 0 0 0\n",
" speed_value 2 2 0 0 0 0\n",
" ability_name 2 2 0 0 0 0\n",
" nature_name 2 2 0 0 0 0\n",
" move_name 2 8 0.6 0.75 0.77 0.589\n",
" original_trainer_name 2 2 0 0 0 0\n",
"original_trainder_number 2 2 0 0 0 0\n",
"Speed: 0.5ms preprocess, 16.9ms inference, 0.0ms loss, 1.1ms postprocess per image\n",
"Results saved to \u001b[1mruns/detect/train8\u001b[0m\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ae347b97"
},
"source": [
"## 3. Verify Model\n",
"Now, we'll test the trained model on one of the images from the training set. We expect it to correctly identify objects in this image."
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "5e3aad61",
"outputId": "1a6b9ee3-0fb8-4d86-8077-20ae33b51862"
},
"source": [
"from ultralytics import YOLO\n",
"from PIL import Image\n",
"\n",
"# Load the trained model\n",
"model = YOLO('/content/best.pt')\n",
"\n",
"# Run inference on a training image\n",
"results = model('/content/Screenshot_20250724_223222_Pokmon HOME.jpg')\n",
"\n",
"# Display the results\n",
"for r in results:\n",
" im_array = r.plot() # plot a BGR numpy array of predictions\n",
" im = Image.fromarray(im_array[..., ::-1]) # RGB PIL image\n",
" display(im)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"image 1/1 /content/Screenshot_20250724_223222_Pokmon HOME.jpg: 640x320 1 ball_icon_cherishball, 1 pokemon_nickname, 1 pokemon_level, 1 language, 1 national_dex_number, 1 pokemon_species, 1 type_1, 1 shiny_icon, 1 origin_icon_swsh, 1 hp_value, 1 attack_value, 1 defense_value, 1 sp_atk_value, 1 sp_def_value, 1 speed_value, 1 ability_name, 1 nature_name, 4 move_names, 1 original_trainer_name, 1 original_trainder_number, 815.7ms\n",
"Speed: 15.0ms preprocess, 815.7ms inference, 30.1ms postprocess per image at shape (1, 3, 640, 320)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<PIL.Image.Image image mode=RGB size=1080x2340>"
],
"image/png": "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
"image/jpeg": "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
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"from ultralytics import YOLO\n",
"from PIL import Image\n",
"# from IPython.display import display # This line might be needed if 'display' isn't implicitly available\n",
"\n",
"# Load the trained model\n",
"# IMPORTANT: Adjust 'train8' to match your actual run folder name if it's different (e.g., train, train2, train7)\n",
"model = YOLO('/content/runs/detect/train/weights/best.pt')\n",
"\n",
"# Run inference on a training image\n",
"# This is currently pointing to a specific image.\n",
"# For better inspection, you'll want to test on VALIDATION or NEW/UNSEEN images.\n",
"test_image_path = '/content/Screenshot_20250726_222229_Pokmon HOME.jpg'\n",
"# Or, if you want to test on a validation image from your dataset:\n",
"# test_image_path = '/content/pokemon_yolov8_dataset/images/val/some_validation_image.jpg'\n",
"\n",
"results = model(test_image_path) # This runs the actual detection\n",
"\n",
"# Display the results\n",
"for r in results: # 'results' can contain results for multiple images if you passed a list\n",
" im_array = r.plot() # plot() generates a NumPy array with bounding boxes and labels drawn\n",
" # Ultralytics plot() returns BGR (Blue, Green, Red) format.\n",
" # PIL Image expects RGB (Red, Green, Blue). [..., ::-1] reverses the color channels.\n",
" im = Image.fromarray(im_array[..., ::-1])\n",
" display(im) # In Colab, this will render the PIL image directly in the output cell"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "JLavtdiZUb5q",
"outputId": "50beee34-b979-435a-fb8a-170d106aedc7",
"collapsed": true
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"image 1/1 /content/Screenshot_20250726_222229_Pokmon HOME.jpg: 640x320 1 pokemon_nickname, 1 gender_icon_male, 1 language, 1 last_game_stamp_sc, 1 national_dex_number, 1 pokemon_species, 1 type_1, 1 origin_icon_sv, 1 hp_value, 1 defense_value, 1 sp_atk_value, 1 sp_def_value, 1 ability_name, 1 nature_name, 2 move_names, 1 original_trainer_name, 1 original_trainder_number, 1 tera_ghost, 25.3ms\n",
"Speed: 2.3ms preprocess, 25.3ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 320)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<PIL.Image.Image image mode=RGB size=1080x2340>"
],
"image/png": "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
"image/jpeg": "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
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"#!/usr/bin/env python3\n",
"\"\"\"\n",
"Convert YOLO .pt model to ONNX format for Android integration\n",
"\"\"\"\n",
"%pip install onnx\n",
"%pip install onnxruntime\n",
"\n",
"import torch\n",
"from ultralytics import YOLO\n",
"import onnx\n",
"import onnxruntime as ort\n",
"import numpy as np\n",
"\n",
"def convert_yolo_to_onnx(model_path, output_path=None, img_size=640):\n",
" \"\"\"\n",
" Convert YOLO .pt model to ONNX format\n",
"\n",
" Args:\n",
" model_path (str): Path to your .pt model file\n",
" output_path (str): Output path for .onnx file (optional)\n",
" img_size (int): Input image size (default 640)\n",
" \"\"\"\n",
"\n",
" print(f\"🔄 Loading YOLO model: {model_path}\")\n",
"\n",
" # Load the model\n",
" model = YOLO(model_path)\n",
"\n",
" # Set output path if not provided\n",
" if output_path is None:\n",
" output_path = model_path.replace('.pt', '.onnx')\n",
"\n",
" print(f\"📤 Converting to ONNX format...\")\n",
" print(f\" Input size: {img_size}x{img_size}\")\n",
" print(f\" Output path: {output_path}\")\n",
"\n",
" # Export to ONNX\n",
" success = model.export(\n",
" format='onnx',\n",
" imgsz=img_size,\n",
" half=False, # Use FP32 for better compatibility\n",
" simplify=True, # Simplify the model\n",
" opset=11, # ONNX opset version (11 is widely supported)\n",
" )\n",
"\n",
" if success:\n",
" print(f\"✅ Conversion successful!\")\n",
" print(f\"📁 ONNX model saved to: {output_path}\")\n",
"\n",
" # Verify the converted model\n",
" verify_onnx_model(output_path, img_size)\n",
"\n",
" else:\n",
" print(\"❌ Conversion failed!\")\n",
" return None\n",
"\n",
" return output_path\n",
"\n",
"def verify_onnx_model(onnx_path, img_size=640):\n",
" \"\"\"\n",
" Verify the converted ONNX model works correctly\n",
" \"\"\"\n",
" print(f\"\\n🔍 Verifying ONNX model...\")\n",
"\n",
" try:\n",
" # Load ONNX model\n",
" onnx_model = onnx.load(onnx_path)\n",
" onnx.checker.check_model(onnx_model)\n",
" print(\"✅ ONNX model structure is valid\")\n",
"\n",
" # Test inference\n",
" session = ort.InferenceSession(onnx_path)\n",
"\n",
" # Get input/output info\n",
" input_info = session.get_inputs()[0]\n",
" output_info = session.get_outputs()\n",
"\n",
" print(f\"📊 Model Information:\")\n",
" print(f\" Input shape: {input_info.shape}\")\n",
" print(f\" Input type: {input_info.type}\")\n",
" print(f\" Number of outputs: {len(output_info)}\")\n",
"\n",
" for i, output in enumerate(output_info):\n",
" print(f\" Output {i} shape: {output.shape}\")\n",
"\n",
" # Test with dummy input\n",
" dummy_input = np.random.randn(1, 3, img_size, img_size).astype(np.float32)\n",
"\n",
" print(f\"\\n🧪 Testing inference with dummy input...\")\n",
" outputs = session.run(None, {input_info.name: dummy_input})\n",
"\n",
" print(f\"✅ Inference successful!\")\n",
" print(f\" Output 0 shape: {outputs[0].shape}\")\n",
"\n",
" # Analyze output format for your integration\n",
" output_shape = outputs[0].shape\n",
" if len(output_shape) == 3: # [batch, detections, features]\n",
" num_detections = output_shape[1]\n",
" num_features = output_shape[2]\n",
"\n",
" print(f\"\\n📋 Detection Format Analysis:\")\n",
" print(f\" Max detections per image: {num_detections}\")\n",
" print(f\" Features per detection: {num_features}\")\n",
" print(f\" Expected format: [x, y, w, h, confidence, class_scores...]\")\n",
"\n",
" # Calculate number of classes\n",
" num_classes = num_features - 5 # subtract x,y,w,h,confidence\n",
" print(f\" Number of classes: {num_classes}\")\n",
"\n",
" print(f\"\\n💡 For Android integration:\")\n",
" print(f\" 1. Copy {onnx_path} to app/src/main/assets/\")\n",
" print(f\" 2. Use OpenCV DNN to load: cv2.dnn.readNetFromONNX()\")\n",
" print(f\" 3. Input preprocessing: resize to {img_size}x{img_size}, normalize to [0,1]\")\n",
" print(f\" 4. Output postprocessing: apply NMS to filter detections\")\n",
"\n",
" except Exception as e:\n",
" print(f\"❌ Verification failed: {str(e)}\")\n",
"\n",
"def print_class_names(model_path):\n",
" \"\"\"\n",
" Print the class names from your model for reference\n",
" \"\"\"\n",
" try:\n",
" model = YOLO(model_path)\n",
" print(f\"\\n📝 Class Names ({len(model.names)} classes):\")\n",
" for i, name in model.names.items():\n",
" print(f\" {i}: {name}\")\n",
" except Exception as e:\n",
" print(f\"❌ Could not extract class names: {str(e)}\")\n",
"\n",
"#if __name__ == \"__main__\":\n",
"import sys\n",
"\n",
"# Default model path - change this to your .pt file\n",
"model_path = \"/content/runs/detect/train/weights/best.pt\" # Change to your model path\n",
"\n",
"print(\"🎯 YOLO to ONNX Converter\")\n",
"print(\"=\" * 50)\n",
"\n",
"# Convert the model\n",
"onnx_path = convert_yolo_to_onnx(model_path)\n",
"\n",
"if onnx_path:\n",
" # Print class names for reference\n",
" print_class_names(model_path)\n",
"\n",
" print(f\"\\n🎉 Conversion Complete!\")\n",
" print(f\"📁 Your ONNX model: {onnx_path}\")\n",
" print(f\"📱 Ready for Android integration!\")\n",
"\n",
"else:\n",
" print(\"❌ Conversion failed. Please check your model path and try again.\")\n",
"\n",
"# Example usage:\n",
"# python convert_yolo.py path/to/your/best.pt"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "wjQT8d46KzOg",
"outputId": "acac4919-682e-4062-db60-79917f797fc0"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Requirement already satisfied: onnx in /usr/local/lib/python3.11/dist-packages (1.17.0)\n",
"Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.11/dist-packages (from onnx) (2.0.2)\n",
"Requirement already satisfied: protobuf>=3.20.2 in /usr/local/lib/python3.11/dist-packages (from onnx) (5.29.5)\n",
"Requirement already satisfied: onnxruntime in /usr/local/lib/python3.11/dist-packages (1.22.1)\n",
"Requirement already satisfied: coloredlogs in /usr/local/lib/python3.11/dist-packages (from onnxruntime) (15.0.1)\n",
"Requirement already satisfied: flatbuffers in /usr/local/lib/python3.11/dist-packages (from onnxruntime) (25.2.10)\n",
"Requirement already satisfied: numpy>=1.21.6 in /usr/local/lib/python3.11/dist-packages (from onnxruntime) (2.0.2)\n",
"Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from onnxruntime) (25.0)\n",
"Requirement already satisfied: protobuf in /usr/local/lib/python3.11/dist-packages (from onnxruntime) (5.29.5)\n",
"Requirement already satisfied: sympy in /usr/local/lib/python3.11/dist-packages (from onnxruntime) (1.14.0)\n",
"Requirement already satisfied: humanfriendly>=9.1 in /usr/local/lib/python3.11/dist-packages (from coloredlogs->onnxruntime) (10.0)\n",
"Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy->onnxruntime) (1.3.0)\n",
"🎯 YOLO to ONNX Converter\n",
"==================================================\n",
"🔄 Loading YOLO model: /content/runs/detect/train/weights/best.pt\n",
"📤 Converting to ONNX format...\n",
" Input size: 640x640\n",
" Output path: /content/runs/detect/train/weights/best.onnx\n",
"Ultralytics 8.3.170 🚀 Python-3.11.13 torch-2.6.0+cu124 CPU (Intel Xeon 2.20GHz)\n",
"Model summary (fused): 92 layers, 25,895,344 parameters, 0 gradients, 79.0 GFLOPs\n",
"\n",
"\u001b[34m\u001b[1mPyTorch:\u001b[0m starting from '/content/runs/detect/train/weights/best.pt' with input shape (1, 3, 640, 640) BCHW and output shape(s) (1, 100, 8400) (49.7 MB)\n",
"\n",
"\u001b[34m\u001b[1mONNX:\u001b[0m starting export with onnx 1.18.0 opset 11...\n",
"\u001b[34m\u001b[1mONNX:\u001b[0m slimming with onnxslim 0.1.61...\n",
"\u001b[34m\u001b[1mONNX:\u001b[0m export success ✅ 4.2s, saved as '/content/runs/detect/train/weights/best.onnx' (99.0 MB)\n",
"\n",
"Export complete (7.2s)\n",
"Results saved to \u001b[1m/content/runs/detect/train/weights\u001b[0m\n",
"Predict: yolo predict task=detect model=/content/runs/detect/train/weights/best.onnx imgsz=640 \n",
"Validate: yolo val task=detect model=/content/runs/detect/train/weights/best.onnx imgsz=640 data=/content/dataset.yaml \n",
"Visualize: https://netron.app\n",
"✅ Conversion successful!\n",
"📁 ONNX model saved to: /content/runs/detect/train/weights/best.onnx\n",
"\n",
"🔍 Verifying ONNX model...\n",
"✅ ONNX model structure is valid\n",
"📊 Model Information:\n",
" Input shape: [1, 3, 640, 640]\n",
" Input type: tensor(float)\n",
" Number of outputs: 1\n",
" Output 0 shape: [1, 100, 8400]\n",
"\n",
"🧪 Testing inference with dummy input...\n",
"✅ Inference successful!\n",
" Output 0 shape: (1, 100, 8400)\n",
"\n",
"📋 Detection Format Analysis:\n",
" Max detections per image: 100\n",
" Features per detection: 8400\n",
" Expected format: [x, y, w, h, confidence, class_scores...]\n",
" Number of classes: 8395\n",
"\n",
"💡 For Android integration:\n",
" 1. Copy /content/runs/detect/train/weights/best.onnx to app/src/main/assets/\n",
" 2. Use OpenCV DNN to load: cv2.dnn.readNetFromONNX()\n",
" 3. Input preprocessing: resize to 640x640, normalize to [0,1]\n",
" 4. Output postprocessing: apply NMS to filter detections\n",
"\n",
"📝 Class Names (96 classes):\n",
" 0: ball_icon_pokeball\n",
" 1: ball_icon_greatball\n",
" 2: ball_icon_ultraball\n",
" 3: ball_icon_masterball\n",
" 4: ball_icon_safariball\n",
" 5: ball_icon_levelball\n",
" 6: ball_icon_lureball\n",
" 7: ball_icon_moonball\n",
" 8: ball_icon_friendball\n",
" 9: ball_icon_loveball\n",
" 10: ball_icon_heavyball\n",
" 11: ball_icon_fastball\n",
" 12: ball_icon_sportball\n",
" 13: ball_icon_premierball\n",
" 14: ball_icon_repeatball\n",
" 15: ball_icon_timerball\n",
" 16: ball_icon_nestball\n",
" 17: ball_icon_netball\n",
" 18: ball_icon_diveball\n",
" 19: ball_icon_luxuryball\n",
" 20: ball_icon_healball\n",
" 21: ball_icon_quickball\n",
" 22: ball_icon_duskball\n",
" 23: ball_icon_cherishball\n",
" 24: ball_icon_dreamball\n",
" 25: ball_icon_beastball\n",
" 26: ball_icon_strangeparts\n",
" 27: ball_icon_parkball\n",
" 28: ball_icon_gsball\n",
" 29: pokemon_nickname\n",
" 30: gender_icon_male\n",
" 31: gender_icon_female\n",
" 32: pokemon_level\n",
" 33: language\n",
" 34: last_game_stamp_home\n",
" 35: last_game_stamp_lgp\n",
" 36: last_game_stamp_lge\n",
" 37: last_game_stamp_sw\n",
" 38: last_game_stamp_sh\n",
" 39: last_game_stamp_bank\n",
" 40: last_game_stamp_bd\n",
" 41: last_game_stamp_sp\n",
" 42: last_game_stamp_pla\n",
" 43: last_game_stamp_sc\n",
" 44: last_game_stamp_vi\n",
" 45: last_game_stamp_go\n",
" 46: national_dex_number\n",
" 47: pokemon_species\n",
" 48: type_1\n",
" 49: type_2\n",
" 50: shiny_icon\n",
" 51: origin_icon_vc\n",
" 52: origin_icon_xyoras\n",
" 53: origin_icon_smusum\n",
" 54: origin_icon_lg\n",
" 55: origin_icon_swsh\n",
" 56: origin_icon_go\n",
" 57: origin_icon_bdsp\n",
" 58: origin_icon_pla\n",
" 59: origin_icon_sv\n",
" 60: pokerus_infected_icon\n",
" 61: pokerus_cured_icon\n",
" 62: hp_value\n",
" 63: attack_value\n",
" 64: defense_value\n",
" 65: sp_atk_value\n",
" 66: sp_def_value\n",
" 67: speed_value\n",
" 68: ability_name\n",
" 69: nature_name\n",
" 70: move_name\n",
" 71: original_trainer_name\n",
" 72: original_trainder_number\n",
" 73: alpha_mark\n",
" 74: tera_water\n",
" 75: tera_psychic\n",
" 76: tera_ice\n",
" 77: tera_fairy\n",
" 78: tera_poison\n",
" 79: tera_ghost\n",
" 80: ball_icon_originball\n",
" 81: tera_dragon\n",
" 82: tera_steel\n",
" 83: tera_grass\n",
" 84: tera_normal\n",
" 85: tera_fire\n",
" 86: tera_electric\n",
" 87: tera_fighting\n",
" 88: tera_ground\n",
" 89: tera_flying\n",
" 90: tera_bug\n",
" 91: tera_rock\n",
" 92: tera_dark\n",
" 93: low_confidence\n",
" 94: ball_icon_pokeball_hisui\n",
" 95: ball_icon_ultraball_husui\n",
"\n",
"🎉 Conversion Complete!\n",
"📁 Your ONNX model: /content/runs/detect/train/weights/best.onnx\n",
"📱 Ready for Android integration!\n"
]
}
]
}
]
}