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import numpy as np import cv2 img_Up = cv2.imread("circle.jpeg",0) f = np.fft.fft2(img_Up) fshift = np.fft.fftshift(f) img_magnitude_spectrum = 20*np.log(np.abs(fshift)) cv2.imwrite("img_magnitude_spectrum_circle.jpg", img_magnitude_spectrum) # # more

import numpy as np import cv2 img = cv2.imread("img_.jpg",0) # Creat a binary image threshold = 0 for i in range(0, img.shape[0]): for j in range(0, img.shape[1]): threshold += img[i][j] threshold = int(threshold / (img.shape[0] * img.shape[1]

import cv2 import numpy as np img = np.array([[52, 55, 61, 66, 70, 61, 64, 73], [63, 59, 55, 90, 109, 85, 69, 72], [62, 59, 68, 113, 144, 104, 66, 73], [63, 58, 71, 122, 154, 106, 70, 69], [6

Python实现基于canny算子的EdgeDetection(边缘提取) Python 语言实现