如下卷积核具有边缘检测的作用，举例说明：
[[-1,-1,-1],
[-1,8,-1],
[-1,-1,-1]]

import cv2
import numpy as np
import tensorflow as tf

input_data = cv2.imread('zxc.jpg')
weights_data = [[[-1,-1,-1],[-1,-1,-1],[-1,-1,-1]],
		[[-1,-1,-1],[8,8,8],[-1,-1,-1]],
		[[-1,-1,-1],[-1,-1,-1],[-1,-1,-1]]]

def tf_conv2d(input,weights):
	conv = tf.nn.conv2d(input, weights, strides=[1, 1, 1, 1], padding='SAME')
	return conv

def main(): 
	const_input = tf.constant(input_data , tf.float32)
	input = tf.Variable(const_input,name="input")
	# [1500,1000,3]-->[1,1500,1000,3]
	input=tf.expand_dims(input,0)

	const_weights = tf.constant(weights_data , tf.float32 )
	weights = tf.Variable(const_weights,name="weights")
	#[3,3,3]-->[3,3,3,1]
	weights=tf.expand_dims(weights,3) 

	#[b,h,w,c]
	conv=tf_conv2d(input,weights)

	init=tf.global_variables_initializer()

	with tf.Session() as sess:
		sess.run(init)
		imgs = sess.run(conv)
		cv2.imwrite('zxcl.jpg', imgs[0])

if __name__ == '__main__':
	main()

zxc.jpg如下：

zxcl.jpg如下：