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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
TomTomMapsofEurope9456175RetailNAViGON
https://documenter.getpostman.com/view/21840331/Uzdv2Tfw
https://documenter.getpostman.com/view/21883628/Uzdv2Tbd
https://documenter.getpostman.com/view/21867673/Uzdv2Tbc
https://documenter.getpostman.com/view/21885581/Uzdv2Tbb
https://documenter.getpostman.com/view/21901492/Uzdv2Tba
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04/18/2012 14:06:31 - ViewAll >> Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
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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
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