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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

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04/18/2012 14:06:31 – ViewAll >>                Â
50b96ab0b6


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

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