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Opencv中已经封装好了API用于处理图像的梯度,因此了解其调用方式。
#13,图像梯度
import cv2 as cv
import numpy as np
def sobel_demo(image):
#使用sobel算子计算梯度
grad_x = cv.Sobel(image, cv.CV_32F, 1, 0)
grad_y = cv.Sobel(image, cv.CV_32F, 0, 1)
#因为求出来的有正有负,所以需要对其绝对值处理。
gradx = cv.convertScaleAbs(grad_x)
grady = cv.convertScaleAbs(grad_y)
cv.imshow("GradientX", gradx)
cv.imshow("GradientY", grady)
#将X和Y方向的梯度进行加权合并
gradxy = cv.addWeighted(gradx, 0.5, grady, 0.5, 0)
cv.imshow("Gradient", gradxy)
def lapalian_demo(image):
#dst = cv.Laplacian(image, cv.CV_32F)
#lpls = cv.convertScaleAbs(dst)
kernel = np.array([[1, 1, 1], [1, -8, 1], [1, 1, 1]])
dst = cv.filter2D(image, cv.CV_32F, kernel=kernel)
lpls = cv.convertScaleAbs(dst)
cv.imshow("lapalian_demo", lpls)
src=cv.imread('F:\OutputResult\SrcImage\saber18.jpg')
print(src.shape)
cv.imshow("Saber",src)
sobel_demo(src)
cv.waitKey(0)
cv.destroyAllWindows()
函数:
cv.Sobel(src, ddepth, dx, dy[, dst[, ksize[, scale[, delta[, borderType]]]]])
运行结果: