result = results[0]
for i in range(1, 8):
result[:] = np.maximum(result, results[i])
return normalize(result).round().astype(np.uint8)
if __name__ == '__main__':
# test = np.asarray([[255, 255, 255, 255, 255, 255, 255, 255],
# [255, 255, 255, 255, 255, 255, 255, 255],
# [255, 255, 0, 0, 0, 0, 255, 255],
# [255, 255, 0, 0, 0, 0, 255, 255],
# [255, 255, 0, 0, 0, 0, 255, 255],
# [255, 255, 0, 0, 0, 0, 255, 255],
# [255, 255, 255, 255, 255, 255, 255, 255],
# [255, 255, 255, 255, 255, 255, 255, 255]])
# sobel(test)
# img = gambar.read('D:\\Kuliah\\pola\\527C868C9284958A22F9E4D448BDDA12.JPG')
img = gambar.read('C:\\Users\\user all\\Downloads\\532fd38d-1.jpg')
gray = gambar.to_gray(img)
# gambar.show(gray)
result = derajat1(gray, 'prewitt')
gambar.show(result)
# kernel = [
# [1, 2, 1],
# [2, 4, 2],
# [1, 2, 1],
# ]
# gray = np.array(kernel)
# convolve(gray, kernel)
