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Open Source Computer Vision Library
https://opencv.org/
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55 lines
1.6 KiB
55 lines
1.6 KiB
7 years ago
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from __future__ import print_function
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import cv2 as cv
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import argparse
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max_value = 255
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max_type = 4
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max_binary_value = 255
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trackbar_type = 'Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted'
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trackbar_value = 'Value'
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window_name = 'Threshold Demo'
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## [Threshold_Demo]
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def Threshold_Demo(val):
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#0: Binary
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#1: Binary Inverted
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#2: Threshold Truncated
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#3: Threshold to Zero
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#4: Threshold to Zero Inverted
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threshold_type = cv.getTrackbarPos(trackbar_type, window_name)
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threshold_value = cv.getTrackbarPos(trackbar_value, window_name)
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_, dst = cv.threshold(src_gray, threshold_value, max_binary_value, threshold_type )
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cv.imshow(window_name, dst)
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## [Threshold_Demo]
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parser = argparse.ArgumentParser(description='Code for Basic Thresholding Operations tutorial.')
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parser.add_argument('--input', help='Path to input image.', default='../data/stuff.jpg')
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args = parser.parse_args()
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## [load]
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# Load an image
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src = cv.imread(args.input)
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if src is None:
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print('Could not open or find the image: ', args.input)
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exit(0)
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# Convert the image to Gray
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src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY);
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## [load]
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## [window]
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# Create a window to display results
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cv.namedWindow(window_name)
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## [window]
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## [trackbar]
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# Create Trackbar to choose type of Threshold
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cv.createTrackbar(trackbar_type, window_name , 3, max_type, Threshold_Demo)
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# Create Trackbar to choose Threshold value
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cv.createTrackbar(trackbar_value, window_name , 0, max_value, Threshold_Demo)
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## [trackbar]
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# Call the function to initialize
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Threshold_Demo(0)
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# Wait until user finishes program
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cv.waitKey()
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