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40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
#!/usr/bin/python
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import sys
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import os
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import cv2
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import numpy as np
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from matplotlib import pyplot as plt
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print('\ndetect_er_chars.py')
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print(' A simple demo script using the Extremal Region Filter algorithm described in:')
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print(' Neumann L., Matas J.: Real-Time Scene Text Localization and Recognition, CVPR 2012\n')
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if (len(sys.argv) < 2):
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print(' (ERROR) You must call this script with an argument (path_to_image_to_be_processed)\n')
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quit()
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pathname = os.path.dirname(sys.argv[0])
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img = cv2.imread(str(sys.argv[1]))
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gray = cv2.imread(str(sys.argv[1]),0)
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erc1 = cv2.text.loadClassifierNM1(pathname+'/trained_classifierNM1.xml')
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er1 = cv2.text.createERFilterNM1(erc1)
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erc2 = cv2.text.loadClassifierNM2(pathname+'/trained_classifierNM2.xml')
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er2 = cv2.text.createERFilterNM2(erc2)
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regions = cv2.text.detectRegions(gray,er1,er2)
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#Visualization
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rects = [cv2.boundingRect(p.reshape(-1, 1, 2)) for p in regions]
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for rect in rects:
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cv2.rectangle(img, rect[0:2], (rect[0]+rect[2],rect[1]+rect[3]), (0, 0, 255), 2)
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img = img[:,:,::-1] #flip the colors dimension from BGR to RGB
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plt.imshow(img)
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plt.xticks([]), plt.yticks([]) # to hide tick values on X and Y axis
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plt.show()
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