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TomTomMapsofEurope9456175RetailNAViGON

TomTomMapsofEurope9456175RetailNAViGON

Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â 04/18/2012 14:06:31 – ViewAll >> Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â

TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON TomTomMapsofEurope9456175RetailNAViGON e79caf774b

– TomTomMapsofEurope9456175RetailNAViGON A: You can use this code : For OCR : import pytesseract import cv2 from PIL import Image text = tesseract.image_to_string(Image.open(“d:/test.tif”)) print(text) For Segmentation : import cv2 import numpy as np # read in the image img = cv2.imread(‘d:/test.tif’) # detect the boundaries img = np.array(img.copy()) edges = np.dstack((-img, img, img)) edges = cv2.blur(edges, (3, 3)) # keep the edges edges = cv2.erode(edges, None, 10) edges = cv2.dilate(edges, None, 20) edges = cv2.cvtColor(edges, cv2.COLOR_BGR2GRAY) # do the segmentation levels, hierarchy = cv2.threshold(edges, 0, 255, cv2.THRESH_BINARY) edges = cv2.dilate(levels, None, 20) edges = cv2.erode(edges, None, 20) edges = cv2.threshold(edges, 0, 255, cv2.THRESH_BINARY) edges = cv2.watershed(edges) # show the result cv2.imshow(‘edges’, edges) cv2.waitKey(0) cv2.destroyAllWindows() Finally You can merge them : import cv2 import numpy as np red, green, blue = cv2.split(img) gray = np.zeros_like(img) #threshold for black background for i in range(img.shape[0]): for j in range(img.shape[1]): if img[i, j] > 200: gray

25th July 2022
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TomTomMapsofEurope9456175RetailNAViGON