用Python实现二维卷积

import numpy as np

def convolve2d(image, kernel):
    # 获取图像和卷积核的尺寸
    image_height, image_width = image.shape
    kernel_height, kernel_width = kernel.shape

    # 计算卷积结果的尺寸
    output_height = image_height - kernel_height + 1
    output_width = image_width - kernel_width + 1

    # 创建一个与输出尺寸相同的零矩阵
    output = np.zeros((output_height, output_width))

    # 对图像进行卷积运算
    for i in range(output_height):
        for j in range(output_width):
            output[i, j] = np.sum(image[i:i+kernel_height, j:j+kernel_width] * kernel)

    return output

image = np.array([[1, 2, 3, 4, 5],
                  [6, 7, 8, 9, 10],
                  [11, 12, 13, 14, 15],
                  [16, 17, 18, 19, 20],
                  [21, 22, 23, 24, 25]])

kernel = np.array([[-1, -1, -1],
                   [-1, 8, -1],
                   [-1, -1, -1]])

output = convolve2d(image, kernel)
print(output)

[[ 13.  20.  17.]
 [ 33.  40.  37.]
 [ 53.  60.  57.]]