basics

.gitignore

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+temp/**
+data/**
+.idea/**

OCR.py

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+import cv2
+from PIL import Image
+import pytesseract
+
+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"
+
+img = cv2.imread(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)
+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'], card_name_roi['y'], card_name_roi['w'], card_name_roi['h'])
+cv2.imwrite("temp/markup.jpg", img)