import cv2
import numpy as np

# prewitt算子
def prewitt(img):
    img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    kernelx = np.array([[1, 1, 1], [0, 0, 0], [-1, -1, -1]], dtype=int)
    kernely = np.array([[-1, 0, 1], [-1, 0, 1], [-1, 0, 1]], dtype=int)
    x = cv2.filter2D(img, cv2.CV_16S, kernelx)
    y = cv2.filter2D(img, cv2.CV_16S, kernely)
    absX = cv2.convertScaleAbs(x)
    absY = cv2.convertScaleAbs(y)
    Prewitt = cv2.addWeighted(absX, 0.5, absY, 0.5, 0)
    return Prewitt

# sobel算子
def sobel(img):
    img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    img_sobel = cv2.Sobel(img, cv2.CV_64F, 0, 1, ksize=5)
    return img_sobel

# laplacian算子
def laplacian(img):
    img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    img = cv2.GaussianBlur(img, (5, 5), 0, 0)
    img_laplacian = cv2.Laplacian(img, cv2.CV_16S, ksize=3)
    return img_laplacian

# log算子
def log(img):
    img1 = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    image = cv2.copyMakeBorder(img1, 2, 2, 2, 2, borderType=cv2.BORDER_REPLICATE)
    image = cv2.GaussianBlur(image, (3, 3), 0, 0)
    m1 = np.array([[0, 0, -1, 0, 0], [0, -1, -2, -1, 0], [-1, -2, 16, -2, -1], [0, -1, -2, -1, 0], [0, 0, -1, 0, 0]],
                  dtype=int)
    rows, cols = image.shape[: 2]
    image1 = np.ones((rows, cols), dtype=float)
    for i in range(2, rows - 2):
        for j in range(2, cols - 2):
            image1[i, j] = np.sum(m1 * image[i - 2:i + 3, j - 2:j + 3, 1])
    image1 = cv2.convertScaleAbs(image1)
    return image1

# canny
def canny(img):
    blur = cv2.GaussianBlur(img, (3, 3), 0)
    grayImage = cv2.cvtColor(blur, cv2.COLOR_BGR2GRAY)
    gradx = cv2.Sobel(grayImage, cv2.CV_16SC1, 1, 0)
    grady = cv2.Sobel(grayImage, cv2.CV_16SC1, 0, 1)
    dst = cv2.Canny(gradx, grady, 50, 150)
    return dst