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56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
import cv2
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from matplotlib import pyplot as plt
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import numpy as np
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import easyocr
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import imutils
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import random
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img = cv2.imread("Test5.jpg") #read image
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plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
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plt.title('Original Image')
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plt.show()
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #convert image to gray
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bfilter = cv2.bilateralFilter(gray, 11, 17, 17) #Noise reduction
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plt.imshow(cv2.cvtColor(bfilter, cv2.COLOR_BGR2RGB)) #show processed image
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plt.title('Processed Image')
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plt.show()
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edged = cv2.Canny(bfilter, 30, 200) #Edge detection
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plt.imshow(cv2.cvtColor(edged, cv2.COLOR_BGR2RGB))
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plt.title('Edged Processed Image')
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plt.show()
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keypoints = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) #Find contours
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contours = imutils.grab_contours(keypoints) #Grab contours
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contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10] #Sort contours
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#Loop over our contours to find the best possible approximate contour of 10 contours
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location = None
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for contour in contours:
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approx = cv2.approxPolyDP(contour, 10, True)
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if len(approx) == 4:
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location = approx
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break
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print("Location: ", location)
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mask = np.zeros(gray.shape, np.uint8) #create blank image with same dimensions as the original image
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new_image = cv2.drawContours(mask, [location], 0,255, -1) #Draw contours on the mask image
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new_image = cv2.bitwise_and(img, img, mask=mask) #Take bitwise AND between the original image and mask image
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plt.imshow(cv2.cvtColor(new_image, cv2.COLOR_BGR2RGB)) #show the final image
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plt.show()
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(x,y) = np.where(mask==255) #Find the co-ordinates of the four corners of the document
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(x1, y1) = (np.min(x), np.min(y)) #Find the top left corner
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(x2, y2) = (np.max(x), np.max(y)) #Find the bottom right corner
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cropped_image = gray[x1:x2+1, y1:y2+1] #Crop the image using the co-ordinates
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plt.imshow(cv2.cvtColor(cropped_image, cv2.COLOR_BGR2RGB)) #show the cropped image
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plt.show()
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reader = easyocr.Reader(['en']) #create an easyocr reader object with english as the language
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result = reader.readtext(cropped_image) #read text from the cropped image
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print(result)
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