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43 lines
1006 B
Python
43 lines
1006 B
Python
import cv2 as cv
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import matplotlib.pyplot as plt
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import numpy as np
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img = cv.imread('Photos/cats.jpg')
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blank = np.zeros(img.shape[:2], dtype='uint8')
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gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
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cv.imshow('Gray', gray)
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mask = cv.circle(blank, (img.shape[1]//2, img.shape[0]//2), 100, 255, -1)
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# mask = cv.bitwise_and(gray,gray,mask=circle)
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masked = cv.bitwise_and(img,img,mask=mask)
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cv.imshow('Mask', masked)
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# Grayscale histogram
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# gray_hist = cv.calcHist([gray], [0], mask, [256], [0,256])
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# plt.figure()
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# plt.title('Grayscale Histogram') # distribution of pixels (intensity) in the image
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# plt.xlabel('Bins')
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# plt.ylabel('# of pixels')
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# plt.plot(gray_hist)
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# plt.xlim([0,256])
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# plt.show()
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# Color histogram
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plt.figure()
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plt.title('Colour Histogram')
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plt.xlabel('Bins')
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plt.ylabel('# of pixels')
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colors = ('b', 'g', 'r')
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for i,col in enumerate(colors):
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hist = cv.calcHist([img], [i], mask, [256], [0,256])
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plt.plot(hist, color = col)
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plt.xlim(0, 256)
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plt.show()
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cv.waitKey(0) |