import cv2
from PIL import Image
import pytesseract
from wand.image import Image as WandImage

card_name_roi = { 'x':44, 'y':32, 'w':360, 'h':40 }

def grayscale(image):
    return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

def noise_removal(image):
    import numpy as np
    kernel = np.ones((1, 1), np.uint8)
    image = cv2.dilate(image, kernel, iterations=1)
    kernel = np.ones((1, 1), np.uint8)
    image = cv2.erode(image, kernel, iterations=1)
    image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel)
    image = cv2.medianBlur(image, 3)
    return (image)

def thin_font(image):
    import numpy as np
    image = cv2.bitwise_not(image)
    kernel = np.ones((2,2),np.uint8)
    image = cv2.erode(image, kernel, iterations=1)
    image = cv2.bitwise_not(image)
    return (image)

def thick_font(image):
    import numpy as np
    image = cv2.bitwise_not(image)
    kernel = np.ones((2,2),np.uint8)
    image = cv2.dilate(image, kernel, iterations=1)
    image = cv2.bitwise_not(image)
    return (image)

file_path = "data/WTR/WTR003.png"

with WandImage(filename=file_path) as img2:
    width = img2.width
    height = img2.height
    img2.resize(width*4, height*4)
    img2.save(filename="temp/big.jpg")

big_file_path = "temp/big.jpg"
img = cv2.imread(big_file_path)
inverted_image = cv2.bitwise_not(img)
cv2.imwrite("temp/inverted.jpg", inverted_image)

gray_image = grayscale(img)
cv2.imwrite("temp/gray.jpg", gray_image)

thresh, im_bw = cv2.threshold(gray_image, 210, 230, cv2.THRESH_BINARY)
cv2.imwrite("temp/bw_image.jpg", im_bw)

no_noise = noise_removal(im_bw)
cv2.imwrite("temp/no_noise.jpg", no_noise)

eroded_image = thin_font(no_noise)
cv2.imwrite("temp/eroded_image.jpg", eroded_image)

dilated_image = thick_font(no_noise)
cv2.imwrite("temp/dilated_image.jpg", dilated_image)

im = Image.open(file_path)
ocr_result = pytesseract.image_to_string(im, config='psm 11')
print("Unaltered:")
print (ocr_result)
print("===========================")

inverted_im = Image.open("temp/inverted.jpg")
inverted_image_ocr = pytesseract.image_to_string(inverted_im)
print("Inverted:")
print (inverted_image_ocr)
print("===========================")

greyscale_im = Image.open("temp/gray.jpg")
greyscale_im_ocr = pytesseract.image_to_string(greyscale_im)
print("Greyscale:")
print (greyscale_im_ocr)
print("===========================")

bw_im = Image.open("temp/bw_image.jpg")
bw_im_ocr = pytesseract.image_to_string(bw_im)
print("Black and White:")
print (bw_im_ocr)
print("===========================")

no_noise_im = Image.open("temp/no_noise.jpg")
no_noise_im_ocr = pytesseract.image_to_string(no_noise_im)
print("No Noise:")
print (no_noise_im_ocr)
print("===========================")

eroded_image_im = Image.open("temp/eroded_image.jpg")
eroded_image_im_ocr = pytesseract.image_to_string(eroded_image_im)
print("Eroded:")
print (eroded_image_im_ocr)
print("===========================")

dilated_image_im = Image.open("temp/dilated_image.jpg")
dilated_image_im_ocr = pytesseract.image_to_string(dilated_image_im)
print("Dilated:")
print (dilated_image_im_ocr)
print("===========================")

def testArea(image, x,y,w,h):
    roi = image[y:y+h, x:x+w]
    inverted_image = cv2.bitwise_not(roi)
    cv2.imwrite("temp/inverted.jpg", inverted_image)
    gray_image = grayscale(roi)
    cv2.imwrite("temp/gray.jpg", gray_image)
    cv2.rectangle(image, (x, y), (x+w, y+h), (36, 255, 12), 2)
    ocr_result = pytesseract.image_to_string(gray_image)
    print(ocr_result)

testArea(img, card_name_roi['x']*4, card_name_roi['y']*4, card_name_roi['w']*4, card_name_roi['h']*4)
cv2.imwrite("temp/markup.jpg", img)