PokeGoalsHelper/tools/debug_scripts

Debug Scripts for YOLO ONNX Detection

This directory contains debugging tools for troubleshooting YOLO object detection issues.

Setup

1. Create a Python virtual environment:

python -m venv debug_env
source debug_env/bin/activate  # On Windows: debug_env\Scripts\activate

2. Install dependencies:

pip install -r requirements.txt

Scripts

debug_model_comparison.py

Compares .pt model predictions with ONNX model outputs on the same static test image.

• Tests both PyTorch and ONNX models side-by-side
• Provides detailed debug output including preprocessing steps
• Useful for identifying model export issues

test_static_onnx.py

Tests ONNX model against static images to isolate Android capture issues.

• Bypasses Android screen capture pipeline
• Tests multiple ONNX model variants
• Good for validating model functionality

export_model_variants.py

Exports YOLO model variants with different NMS settings.

• Creates models with different confidence/IoU thresholds
• Useful for debugging detection sensitivity issues

inspect_onnx_model.py

Inspects ONNX model structure and metadata.

• Verifies class mappings and model architecture
• Helpful for debugging model export problems

Usage

Place test images in ../../test_images/ and ensure model files are in ../../raw_models/.

Example:

cd tools/debug_scripts
source debug_env/bin/activate
python debug_model_comparison.py