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118 lines
3.7 KiB
118 lines
3.7 KiB
import cv2
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from PIL import Image
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import pytesseract
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from wand.image import Image as WandImage
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card_name_roi = { 'x':44, 'y':32, 'w':360, 'h':40 }
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def grayscale(image):
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return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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def noise_removal(image):
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import numpy as np
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kernel = np.ones((1, 1), np.uint8)
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image = cv2.dilate(image, kernel, iterations=1)
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kernel = np.ones((1, 1), np.uint8)
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image = cv2.erode(image, kernel, iterations=1)
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image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel)
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image = cv2.medianBlur(image, 3)
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return (image)
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def thin_font(image):
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import numpy as np
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image = cv2.bitwise_not(image)
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kernel = np.ones((2,2),np.uint8)
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image = cv2.erode(image, kernel, iterations=1)
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image = cv2.bitwise_not(image)
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return (image)
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def thick_font(image):
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import numpy as np
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image = cv2.bitwise_not(image)
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kernel = np.ones((2,2),np.uint8)
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image = cv2.dilate(image, kernel, iterations=1)
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image = cv2.bitwise_not(image)
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return (image)
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file_path = "data/WTR/WTR003.png"
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with WandImage(filename=file_path) as img2:
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width = img2.width
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height = img2.height
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img2.resize(width*4, height*4)
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img2.save(filename="temp/big.jpg")
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big_file_path = "temp/big.jpg"
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img = cv2.imread(big_file_path)
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inverted_image = cv2.bitwise_not(img)
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cv2.imwrite("temp/inverted.jpg", inverted_image)
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gray_image = grayscale(img)
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cv2.imwrite("temp/gray.jpg", gray_image)
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thresh, im_bw = cv2.threshold(gray_image, 210, 230, cv2.THRESH_BINARY)
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cv2.imwrite("temp/bw_image.jpg", im_bw)
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no_noise = noise_removal(im_bw)
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cv2.imwrite("temp/no_noise.jpg", no_noise)
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eroded_image = thin_font(no_noise)
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cv2.imwrite("temp/eroded_image.jpg", eroded_image)
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dilated_image = thick_font(no_noise)
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cv2.imwrite("temp/dilated_image.jpg", dilated_image)
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im = Image.open(file_path)
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ocr_result = pytesseract.image_to_string(im, config='psm 11')
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print("Unaltered:")
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print (ocr_result)
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print("===========================")
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inverted_im = Image.open("temp/inverted.jpg")
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inverted_image_ocr = pytesseract.image_to_string(inverted_im)
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print("Inverted:")
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print (inverted_image_ocr)
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print("===========================")
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greyscale_im = Image.open("temp/gray.jpg")
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greyscale_im_ocr = pytesseract.image_to_string(greyscale_im)
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print("Greyscale:")
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print (greyscale_im_ocr)
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print("===========================")
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bw_im = Image.open("temp/bw_image.jpg")
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bw_im_ocr = pytesseract.image_to_string(bw_im)
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print("Black and White:")
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print (bw_im_ocr)
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print("===========================")
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no_noise_im = Image.open("temp/no_noise.jpg")
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no_noise_im_ocr = pytesseract.image_to_string(no_noise_im)
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print("No Noise:")
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print (no_noise_im_ocr)
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print("===========================")
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eroded_image_im = Image.open("temp/eroded_image.jpg")
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eroded_image_im_ocr = pytesseract.image_to_string(eroded_image_im)
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print("Eroded:")
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print (eroded_image_im_ocr)
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print("===========================")
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dilated_image_im = Image.open("temp/dilated_image.jpg")
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dilated_image_im_ocr = pytesseract.image_to_string(dilated_image_im)
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print("Dilated:")
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print (dilated_image_im_ocr)
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print("===========================")
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def testArea(image, x,y,w,h):
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roi = image[y:y+h, x:x+w]
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inverted_image = cv2.bitwise_not(roi)
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cv2.imwrite("temp/inverted.jpg", inverted_image)
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gray_image = grayscale(roi)
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cv2.imwrite("temp/gray.jpg", gray_image)
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cv2.rectangle(image, (x, y), (x+w, y+h), (36, 255, 12), 2)
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ocr_result = pytesseract.image_to_string(gray_image)
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print(ocr_result)
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testArea(img, card_name_roi['x']*4, card_name_roi['y']*4, card_name_roi['w']*4, card_name_roi['h']*4)
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cv2.imwrite("temp/markup.jpg", img)
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