卷积操作-手动计算

import tensorflow as tf
import numpy as np
import  matplotlib.pyplot as plt
class Conv2D(tf.keras.layers.Layer):
    def __init__(self,kernel_size,step_len,kernel):
        super().__init__()
        self.kernel_size=kernel_size
        self.step_len=step_len
        self.kernel=kernel
    def call(self, inputs):
        new_image=[]
        for i in range(inputs.shape[0]-2):
            print(i,inputs.shape[0])
            Line_data=[]
            for j in range(inputs.shape[1]-2):
                Line_data.append(np.mean(inputs[i:i+3,j:j+3]*self.kernel))
            new_image.append(Line_data)
        return np.array(new_image)
Conv2DLayer=Conv2D([3,3],1,kernel=[[-1,0,1],[-2,0,2],[-1,0,1]])
#
image="image.png"
image_data=plt.imread(image)
print(image_data.shape)
input_data=image_data[:,:,0]
# input_data=image_data
# plt.imshow(input_data)
# plt.show()
plt.imshow(Conv2DLayer(input_data))
plt.show()