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| def gradient_integral_map(img, angle_step):
H, W = img.shape[:2] # 梯度积分图
angle_feature_channel_num = 360 // angle_step
hog_matrix = np.zeros([H+1, W+1, angle_feature_channel_num], dtype='float32')
hog_gra_matrix = np.zeros([H, W, angle_feature_channel_num], dtype='float32') gx = cv2.Sobel(img, cv2.CV_32F, 1, 0, ksize=1)
gy = cv2.Sobel(img, cv2.CV_32F, 0, 1, ksize=1) mag, angle = cv2.cartToPolar(gx, gy, angleInDegrees=True)
angle = np.clip(angle, None, 359.99999)
angle_index = angle // angle_step for channel_index in range(angle_feature_channel_num):
temp_map = mag * (angle_index == channel_index)
hog_gra_matrix[:,:,channel_index] = temp_map
sum_map = cv2.integral(temp_map)
hog_matrix[:,:,channel_index] = sum_map return hog_matrix, hog_gra_matrix
|
