Computer Vision: image Histograms and contrast stretching using OpenCV Python 




import numpy as np

import cv2 as cv

from matplotlib import pyplot as plt

img = cv.imread("lena.jpg")

#img = np.zeros((200,200), np.uint8)

#cv.rectangle(img, (0, 100), (200, 200), (255), -1)

#cv.rectangle(img, (0, 50), (100, 100), (127), -1)

b, g, r = cv.split(img)

cv.imshow("img", img)

cv.imshow("b", b)

cv.imshow("g", g)

cv.imshow("r", r)


plt.hist(b.ravel(), 256, [0, 256])

plt.hist(g.ravel(), 256, [0, 256])

plt.hist(r.ravel(), 256, [0, 256])


hist = cv.calcHist([img], [0], None, [256], [0, 256])

plt.plot(hist)

plt.show()

cv.waitKey(0)

cv.destroyAllWindows()

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Data used in this video


 

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