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import sys
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import cv2
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import numpy as np
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import matplotlib.pyplot as plt
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def Differentiation(img_path, T):
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img = cv2.imread(img_path,0) # 读取图片
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m, n = img.shape[0], img.shape[1]
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ans = np.zeros((m, n), dtype=np.uint8)
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kernelx = np.array([[-1, 0], [0, 1]], dtype=int)
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kernely = np.array([[0, -1], [1, 0]], dtype=int)
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x = cv2.filter2D(img, cv2.CV_16S, kernelx)
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y = cv2.filter2D(img, cv2.CV_16S, kernely)
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absX = cv2.convertScaleAbs(x)
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absY = cv2.convertScaleAbs(y)
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Roberts = cv2.addWeighted(absX, 0.5, absY, 0.5, 0)
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# 背景保留
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for i in range(m):
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for j in range(n):
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if Roberts[i, j] >= T:
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ans[i, j] = Roberts[i, j]
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else:
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ans[i, j] = img[i, j]
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cv2.imwrite('./output/Differentiation.jpg', ans)
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'''
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输入：img_path:图片地址
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T：阈值
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输出：微分法的结果
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'''
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if __name__ == '__main__':
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Differentiation(sys.argv[1], eval(sys.argv[2]))
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