EdgeDetection.py 文件源码

def EdgeDetection(img):
    # img = cv2.medianBlur(img,5)
    img = cv2.fastNlMeansDenoising(img,None,3,7,21)
    _,img = cv2.threshold(img,30,255,cv2.THRESH_TOZERO)
    denoise_img = img
    # print(img)
    # cv2.imwrite("Denoise.jpg",img)
    # cv2.waitKey(0)
    # cv2.destroyAllWindows()

    # convolute with proper kernels
    laplacian = cv2.Laplacian(img,cv2.CV_64F)
    sobelx = cv2.Sobel(img,cv2.CV_64F,1,0,ksize=5)  # x
    sobely = cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3)  # y
    # sobel2y = cv2.Sobel(sobely,cv2.CV_64F,0,1,ksize=3)
    # sobelxy = cv2.Sobel(img,cv2.CV_64F,1,1,ksize=5)  # y
    canny = cv2.Canny(img,100,200)
    contour_image, contours, hierarchy = cv2.findContours(img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    # print(canny)
    # cv2.imwrite('laplacian.jpg',laplacian)
    # cv2.imwrite('sobelx.jpg',sobelx)
    # cv2.imwrite('sobely.jpg',sobely)
    # cv2.imwrite('sobelxy.jpg',sobelxy)
    # cv2.imwrite('canny.jpg',canny)

    # plt.subplot(3,2,1),plt.imshow(img,cmap = 'gray')
    # plt.title('Original'), plt.xticks([]), plt.yticks([])

    # plt.subplot(3,2,2),plt.imshow(laplacian,cmap = 'gray')
    # plt.title('Laplacian'), plt.xticks([]), plt.yticks([])

    # plt.subplot(3,2,3),plt.imshow(sobelx,cmap = 'gray')
    # plt.title('Sobel X'), plt.xticks([]), plt.yticks([])

    # plt.subplot(3,2,4),plt.imshow(sobely,cmap = 'gray')
    # plt.title('Sobel Y'), plt.xticks([]), plt.yticks([])

    # plt.subplot(3,2,4),plt.imshow(sobelxy,cmap = 'gray')
    # plt.title('Sobel XY'), plt.xticks([]), plt.yticks([])

    # plt.subplot(3,2,5),plt.imshow(canny,cmap = 'gray')
    # plt.title('Canny'), plt.xticks([]), plt.yticks([])

    # plt.show()
    # return {"denoise":img}
    return {"denoise":denoise_img,"laplacian":laplacian,"canny":canny,"sobely":sobely,"sobelx":sobelx,"contour":contour_image}