展平与全连接得到特征值
import numpy as np
# 1、定义输入图片：4x4的图片，0表示白色，1表示黑色
image = np.array([
[0, 0, 1, 1],
[0, 0, 1, 1],
[1, 1, 0, 0],
[1, 1, 0, 0]
])
print('输入图片: \n', image)
# 2、卷积：用2x2滤波找对角特征
filter_simple = np.array([
[1, 0],
[0, 1]
])
print('滤波器: \n', filter_simple)
# 计算卷积结果
con[......]矩阵是图像在计算机中的一种表示方式
import numpy as np
import matplotlib.pyplot as plt
image = np.array([
[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0],
])
print('图片矩阵：\n', image)
plt.imshow(image, cmap='gray')
plt.title('Simple Image')
plt.axis('off')
plt.[......]池化的目的是采样，减少计算量
import numpy as np
feature_map = np.array([
[1, 1, 1, 1],
[1, 1, 1, 1],
[2, 2, 2, 2],
[2, 2, 2, 2]
])
print('特征图：\n', feature_map)
pooled = np.zeros((2, 2))
for i in range(0, 4, 2):
for j in range(0, 4, 2):
pooled[i // 2, j // 2] = np.max(feature_map[i[......]卷积是为了提取特征
import numpy as np
image = np.array([
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[1, 1, 1, 1, 1],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]
])
filter_vertical = np.array([
[-1, 0, 1],
[-1, 0, 1],
[-1, 0, 1],
])
filter_horizontal = np.array([
[0, 1, 0],
[0, 1, 0],[......]
This extension is ‘appindicators’ from ubuntu, renamed ‘top indicator app’ under the terms of the GPL v2 +. it is the extension itself that Ubuntu offers as a native experience on your system, but so you can install it in other distros since the current one in gnome-extensions is empty.I will offe[……]