dataset_utils.py 文件源码

def compute_gradient(img, use_scharr=True):
    if use_scharr:
        norm_factor = 32
        gradx = cv2.Scharr(img, cv2.CV_32F, 1, 0, scale=1.0/norm_factor)
        grady = cv2.Scharr(img, cv2.CV_32F, 0, 1, scale=1.0/norm_factor)
    else:
        kx = cv2.getDerivKernels(1, 0, ksize=1, normalize=True)
        ky = cv2.getDerivKernels(0, 1, ksize=1, normalize=True)
        gradx = cv2.sepFilter2D(img, cv2.CV_32F, kx[0], kx[1])
        grady = cv2.sepFilter2D(img, cv2.CV_32F, ky[0], ky[1])

    gradient = np.dstack([gradx, grady])
    return gradient