深度学习 Day21——J1ResNet-50算法实战与解析

发布时间:2023年12月21日


前言

关键字:CNN算法发展,残差网络介绍,Resnet50, softmax及它的实现原理

一、我的环境

  • 电脑系统:Windows 11
  • 语言环境:python 3.8.6
  • 编译器:pycharm2020.2.3
  • 深度学习环境:TensorFlow 2.10.1
  • 显卡:NVIDIA GeForce RTX 4070

二、代码实现与执行结果

1.引入库

from PIL import Image
from pathlib import Path
import matplotlib.pyplot as plt
# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
import tensorflow as tf
from keras import layers, models, Input
from keras.layers import Input, Activation, BatchNormalization, Flatten
from keras.layers import Dense, Conv2D, MaxPooling2D, ZeroPadding2D, AveragePooling2D, Flatten, Dropout, BatchNormalization
from keras.models import Model
import matplotlib.pyplot as plt
import warnings

warnings.filterwarnings('ignore')  # 忽略一些warning内容,无需打印

2.设置GPU(如果使用的是CPU可以忽略这步)

'''前期工作-设置GPU(如果使用的是CPU可以忽略这步)'''
# 检查GPU是否可用
print(tf.test.is_built_with_cuda())
gpus = tf.config.list_physical_devices("GPU")
print(gpus)
if gpus:
    gpu0 = gpus[0]  # 如果有多个GPU,仅使用第0个GPU
    tf.config.experimental.set_memory_growth(gpu0, True)  # 设置GPU显存用量按需使用
    tf.config.set_visible_devices([gpu0], "GPU")

执行结果

True
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]

3.导入数据

'''前期工作-导入数据'''
data_dir = r"D:\DeepLearning\data\bird\bird_photos"
data_dir = Path(data_dir)

4.查看数据

'''前期工作-查看数据'''
image_count = len(list(data_dir.glob('*/*.jpg')))
print("图片总数为:", image_count)
image_list = list(data_dir.glob('Bananaquit/*.jpg'))
image = Image.open(str(image_list[1]))
# 查看图像实例的属性
print(image.format, image.size, image.mode)
plt.imshow(image)
plt.axis("off")
plt.show()

执行结果:

图片总数为: 565
JPEG (224, 224) RGB

在这里插入图片描述

5.加载数据

'''数据预处理-加载数据'''
batch_size = 8
img_height = 224
img_width = 224
"""
关于image_dataset_from_directory()的详细介绍可以参考文章:https://mtyjkh.blog.csdn.net/article/details/117018789
"""
train_ds = tf.keras.preprocessing.image_dataset_from_directory(
    data_dir,
    validation_split=0.2,
    subset="training",
    seed=123,
    image_size=(img_height, img_width),
    batch_size=batch_size)
val_ds = tf.keras.preprocessing.image_dataset_from_directory(
    data_dir,
    validation_split=0.2,
    subset="validation",
    seed=123,
    image_size=(img_height, img_width),
    batch_size=batch_size)
class_names = train_ds.class_names
print(class_names)

运行结果:

Found 565 files belonging to 4 classes.
Using 452 files for training.
Found 565 files belonging to 4 classes.
Using 113 files for validation.
['Bananaquit', 'Black Skimmer', 'Black Throated Bushtiti', 'Cockatoo']

6.再次检查数据

'''数据预处理-再次检查数据'''
# Image_batch是形状的张量(16, 336, 336, 3)。这是一批形状336x336x3的16张图片(最后一维指的是彩色通道RGB)。
# Label_batch是形状(16,)的张量,这些标签对应16张图片
for image_batch, labels_batch in train_ds:
    print(image_batch.shape)
    print(labels_batch.shape)
    break

运行结果

(8, 224, 224, 3)
(8,)

7.配置数据集

'''数据预处理-配置数据集'''
AUTOTUNE = tf.data.AUTOTUNE
train_ds = train_ds.cache().shuffle(1000).prefetch(buffer_size=AUTOTUNE)
val_ds = val_ds.cache().prefetch(buffer_size=AUTOTUNE)

8.可视化数据

'''数据预处理-可视化数据'''
plt.figure(figsize=(10, 5))
for images, labels in train_ds.take(1):
    for i in range(8):
        ax = plt.subplot(2, 4, i + 1)
        plt.imshow(images[i].numpy().astype("uint8"))
        plt.title(class_names[labels[i]], fontsize=10)
        plt.axis("off")
# 显示图片
plt.show()

在这里插入图片描述

9.构建ResNet50模型

"""构建ResNet50模型"""
def identity_block(input_tensor, kernel_size, filters, stage, block):
    filters1, filters2, filters3 = filters

    name_base = str(stage) + block + '_identity_block_'

    x = Conv2D(filters1, (1, 1), name=name_base + 'conv1')(input_tensor)
    x = BatchNormalization(name=name_base + 'bn1')(x)
    x = Activation('relu', name=name_base + 'relu1')(x)

    x = Conv2D(filters2, kernel_size, padding='same', name=name_base + 'conv2')(x)
    x = BatchNormalization(name=name_base + 'bn2')(x)
    x = Activation('relu', name=name_base + 'relu2')(x)

    x = Conv2D(filters3, (1, 1), name=name_base + 'conv3')(x)
    x = BatchNormalization(name=name_base + 'bn3')(x)

    x = layers.add([x, input_tensor], name=name_base + 'add')
    x = Activation('relu', name=name_base + 'relu4')(x)
    return x


def conv_block(input_tensor, kernel_size, filters, stage, block, strides=(2, 2)):
    filters1, filters2, filters3 = filters

    res_name_base = str(stage) + block + '_conv_block_res_'
    name_base = str(stage) + block + '_conv_block_'

    x = Conv2D(filters1, (1, 1), strides=strides, name=name_base + 'conv1')(input_tensor)
    x = BatchNormalization(name=name_base + 'bn1')(x)
    x = Activation('relu', name=name_base + 'relu1')(x)

    x = Conv2D(filters2, kernel_size, padding='same', name=name_base + 'conv2')(x)
    x = BatchNormalization(name=name_base + 'bn2')(x)
    x = Activation('relu', name=name_base + 'relu2')(x)

    x = Conv2D(filters3, (1, 1), name=name_base + 'conv3')(x)
    x = BatchNormalization(name=name_base + 'bn3')(x)

    shortcut = Conv2D(filters3, (1, 1), strides=strides, name=res_name_base + 'conv')(input_tensor)
    shortcut = BatchNormalization(name=res_name_base + 'bn')(shortcut)

    x = layers.add([x, shortcut], name=name_base + 'add')
    x = Activation('relu', name=name_base + 'relu4')(x)
    return x


def ResNet50(input_shape=[224, 224, 3], classes=1000):
    img_input = Input(shape=input_shape)
    x = ZeroPadding2D((3, 3))(img_input)

    x = Conv2D(64, (7, 7), strides=(2, 2), name='conv1')(x)
    x = BatchNormalization(name='bn_conv1')(x)
    x = Activation('relu')(x)
    x = MaxPooling2D((3, 3), strides=(2, 2))(x)

    x = conv_block(x, 3, [64, 64, 256], stage=2, block='a', strides=(1, 1))
    x = identity_block(x, 3, [64, 64, 256], stage=2, block='b')
    x = identity_block(x, 3, [64, 64, 256], stage=2, block='c')

    x = conv_block(x, 3, [128, 128, 512], stage=3, block='a')
    x = identity_block(x, 3, [128, 128, 512], stage=3, block='b')
    x = identity_block(x, 3, [128, 128, 512], stage=3, block='c')
    x = identity_block(x, 3, [128, 128, 512], stage=3, block='d')

    x = conv_block(x, 3, [256, 256, 1024], stage=4, block='a')
    x = identity_block(x, 3, [256, 256, 1024], stage=4, block='b')
    x = identity_block(x, 3, [256, 256, 1024], stage=4, block='c')
    x = identity_block(x, 3, [256, 256, 1024], stage=4, block='d')
    x = identity_block(x, 3, [256, 256, 1024], stage=4, block='e')
    x = identity_block(x, 3, [256, 256, 1024], stage=4, block='f')

    x = conv_block(x, 3, [512, 512, 2048], stage=5, block='a')
    x = identity_block(x, 3, [512, 512, 2048], stage=5, block='b')
    x = identity_block(x, 3, [512, 512, 2048], stage=5, block='c')

    x = AveragePooling2D((7, 7), name='avg_pooling')(x)
    x = Flatten()(x)

    x = Dense(classes, activation='softmax', name='fc1000')(x)

    model = Model(img_input, x, name='resnet50')

    # 加载预训练模型
    model.load_weights("resnet50_weights_tf_dim_ordering_tf_kernels.h5")

    return model


model = ResNet50()
model.summary()


网络结构结果如下:

Model: "resnet50"
__________________________________________________________________________________________________
 Layer (type)                   Output Shape         Param #     Connected to                     
==================================================================================================
 input_1 (InputLayer)           [(None, 224, 224, 3  0           []                               
                                )]                                                                
                                                                                                  
 zero_padding2d (ZeroPadding2D)  (None, 230, 230, 3)  0          ['input_1[0][0]']                
                                                                                                  
 conv1 (Conv2D)                 (None, 112, 112, 64  9472        ['zero_padding2d[0][0]']         
                                )                                                                 
                                                                                                  
 bn_conv1 (BatchNormalization)  (None, 112, 112, 64  256         ['conv1[0][0]']                  
                                )                                                                 
                                                                                                  
 activation (Activation)        (None, 112, 112, 64  0           ['bn_conv1[0][0]']               
                                )                                                                 
                                                                                                  
 max_pooling2d (MaxPooling2D)   (None, 55, 55, 64)   0           ['activation[0][0]']             
                                                                                                  
 2a_conv_block_conv1 (Conv2D)   (None, 55, 55, 64)   4160        ['max_pooling2d[0][0]']          
                                                                                                  
 2a_conv_block_bn1 (BatchNormal  (None, 55, 55, 64)  256         ['2a_conv_block_conv1[0][0]']    
 ization)                                                                                         
                                                                                                  
 2a_conv_block_relu1 (Activatio  (None, 55, 55, 64)  0           ['2a_conv_block_bn1[0][0]']      
 n)                                                                                               
                                                                                                  
 2a_conv_block_conv2 (Conv2D)   (None, 55, 55, 64)   36928       ['2a_conv_block_relu1[0][0]']    
                                                                                                  
 2a_conv_block_bn2 (BatchNormal  (None, 55, 55, 64)  256         ['2a_conv_block_conv2[0][0]']    
 ization)                                                                                         
                                                                                                  
 2a_conv_block_relu2 (Activatio  (None, 55, 55, 64)  0           ['2a_conv_block_bn2[0][0]']      
 n)                                                                                               
                                                                                                  
 2a_conv_block_conv3 (Conv2D)   (None, 55, 55, 256)  16640       ['2a_conv_block_relu2[0][0]']    
                                                                                                  
 2a_conv_block_res_conv (Conv2D  (None, 55, 55, 256)  16640      ['max_pooling2d[0][0]']          
 )                                                                                                
                                                                                                  
 2a_conv_block_bn3 (BatchNormal  (None, 55, 55, 256)  1024       ['2a_conv_block_conv3[0][0]']    
 ization)                                                                                         
                                                                                                  
 2a_conv_block_res_bn (BatchNor  (None, 55, 55, 256)  1024       ['2a_conv_block_res_conv[0][0]'] 
 malization)                                                                                      
                                                                                                  
 2a_conv_block_add (Add)        (None, 55, 55, 256)  0           ['2a_conv_block_bn3[0][0]',      
                                                                  '2a_conv_block_res_bn[0][0]']   
                                                                                                  
 2a_conv_block_relu4 (Activatio  (None, 55, 55, 256)  0          ['2a_conv_block_add[0][0]']      
 n)                                                                                               
                                                                                                  
 2b_identity_block_conv1 (Conv2  (None, 55, 55, 64)  16448       ['2a_conv_block_relu4[0][0]']    
 D)                                                                                               
                                                                                                  
 2b_identity_block_bn1 (BatchNo  (None, 55, 55, 64)  256         ['2b_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 2b_identity_block_relu1 (Activ  (None, 55, 55, 64)  0           ['2b_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 2b_identity_block_conv2 (Conv2  (None, 55, 55, 64)  36928       ['2b_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 2b_identity_block_bn2 (BatchNo  (None, 55, 55, 64)  256         ['2b_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 2b_identity_block_relu2 (Activ  (None, 55, 55, 64)  0           ['2b_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 2b_identity_block_conv3 (Conv2  (None, 55, 55, 256)  16640      ['2b_identity_block_relu2[0][0]']
 D)                                                                                               
                                                                                                  
 2b_identity_block_bn3 (BatchNo  (None, 55, 55, 256)  1024       ['2b_identity_block_conv3[0][0]']
 rmalization)                                                                                     
                                                                                                  
 2b_identity_block_add (Add)    (None, 55, 55, 256)  0           ['2b_identity_block_bn3[0][0]',  
                                                                  '2a_conv_block_relu4[0][0]']    
                                                                                                  
 2b_identity_block_relu4 (Activ  (None, 55, 55, 256)  0          ['2b_identity_block_add[0][0]']  
 ation)                                                                                           
                                                                                                  
 2c_identity_block_conv1 (Conv2  (None, 55, 55, 64)  16448       ['2b_identity_block_relu4[0][0]']
 D)                                                                                               
                                                                                                  
 2c_identity_block_bn1 (BatchNo  (None, 55, 55, 64)  256         ['2c_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 2c_identity_block_relu1 (Activ  (None, 55, 55, 64)  0           ['2c_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 2c_identity_block_conv2 (Conv2  (None, 55, 55, 64)  36928       ['2c_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 2c_identity_block_bn2 (BatchNo  (None, 55, 55, 64)  256         ['2c_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 2c_identity_block_relu2 (Activ  (None, 55, 55, 64)  0           ['2c_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 2c_identity_block_conv3 (Conv2  (None, 55, 55, 256)  16640      ['2c_identity_block_relu2[0][0]']
 D)                                                                                               
                                                                                                  
 2c_identity_block_bn3 (BatchNo  (None, 55, 55, 256)  1024       ['2c_identity_block_conv3[0][0]']
 rmalization)                                                                                     
                                                                                                  
 2c_identity_block_add (Add)    (None, 55, 55, 256)  0           ['2c_identity_block_bn3[0][0]',  
                                                                  '2b_identity_block_relu4[0][0]']
                                                                                                  
 2c_identity_block_relu4 (Activ  (None, 55, 55, 256)  0          ['2c_identity_block_add[0][0]']  
 ation)                                                                                           
                                                                                                  
 3a_conv_block_conv1 (Conv2D)   (None, 28, 28, 128)  32896       ['2c_identity_block_relu4[0][0]']
                                                                                                  
 3a_conv_block_bn1 (BatchNormal  (None, 28, 28, 128)  512        ['3a_conv_block_conv1[0][0]']    
 ization)                                                                                         
                                                                                                  
 3a_conv_block_relu1 (Activatio  (None, 28, 28, 128)  0          ['3a_conv_block_bn1[0][0]']      
 n)                                                                                               
                                                                                                  
 3a_conv_block_conv2 (Conv2D)   (None, 28, 28, 128)  147584      ['3a_conv_block_relu1[0][0]']    
                                                                                                  
 3a_conv_block_bn2 (BatchNormal  (None, 28, 28, 128)  512        ['3a_conv_block_conv2[0][0]']    
 ization)                                                                                         
                                                                                                  
 3a_conv_block_relu2 (Activatio  (None, 28, 28, 128)  0          ['3a_conv_block_bn2[0][0]']      
 n)                                                                                               
                                                                                                  
 3a_conv_block_conv3 (Conv2D)   (None, 28, 28, 512)  66048       ['3a_conv_block_relu2[0][0]']    
                                                                                                  
 3a_conv_block_res_conv (Conv2D  (None, 28, 28, 512)  131584     ['2c_identity_block_relu4[0][0]']
 )                                                                                                
                                                                                                  
 3a_conv_block_bn3 (BatchNormal  (None, 28, 28, 512)  2048       ['3a_conv_block_conv3[0][0]']    
 ization)                                                                                         
                                                                                                  
 3a_conv_block_res_bn (BatchNor  (None, 28, 28, 512)  2048       ['3a_conv_block_res_conv[0][0]'] 
 malization)                                                                                      
                                                                                                  
 3a_conv_block_add (Add)        (None, 28, 28, 512)  0           ['3a_conv_block_bn3[0][0]',      
                                                                  '3a_conv_block_res_bn[0][0]']   
                                                                                                  
 3a_conv_block_relu4 (Activatio  (None, 28, 28, 512)  0          ['3a_conv_block_add[0][0]']      
 n)                                                                                               
                                                                                                  
 3b_identity_block_conv1 (Conv2  (None, 28, 28, 128)  65664      ['3a_conv_block_relu4[0][0]']    
 D)                                                                                               
                                                                                                  
 3b_identity_block_bn1 (BatchNo  (None, 28, 28, 128)  512        ['3b_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 3b_identity_block_relu1 (Activ  (None, 28, 28, 128)  0          ['3b_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 3b_identity_block_conv2 (Conv2  (None, 28, 28, 128)  147584     ['3b_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 3b_identity_block_bn2 (BatchNo  (None, 28, 28, 128)  512        ['3b_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 3b_identity_block_relu2 (Activ  (None, 28, 28, 128)  0          ['3b_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 3b_identity_block_conv3 (Conv2  (None, 28, 28, 512)  66048      ['3b_identity_block_relu2[0][0]']
 D)                                                                                               
                                                                                                  
 3b_identity_block_bn3 (BatchNo  (None, 28, 28, 512)  2048       ['3b_identity_block_conv3[0][0]']
 rmalization)                                                                                     
                                                                                                  
 3b_identity_block_add (Add)    (None, 28, 28, 512)  0           ['3b_identity_block_bn3[0][0]',  
                                                                  '3a_conv_block_relu4[0][0]']    
                                                                                                  
 3b_identity_block_relu4 (Activ  (None, 28, 28, 512)  0          ['3b_identity_block_add[0][0]']  
 ation)                                                                                           
                                                                                                  
 3c_identity_block_conv1 (Conv2  (None, 28, 28, 128)  65664      ['3b_identity_block_relu4[0][0]']
 D)                                                                                               
                                                                                                  
 3c_identity_block_bn1 (BatchNo  (None, 28, 28, 128)  512        ['3c_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 3c_identity_block_relu1 (Activ  (None, 28, 28, 128)  0          ['3c_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 3c_identity_block_conv2 (Conv2  (None, 28, 28, 128)  147584     ['3c_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 3c_identity_block_bn2 (BatchNo  (None, 28, 28, 128)  512        ['3c_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 3c_identity_block_relu2 (Activ  (None, 28, 28, 128)  0          ['3c_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 3c_identity_block_conv3 (Conv2  (None, 28, 28, 512)  66048      ['3c_identity_block_relu2[0][0]']
 D)                                                                                               
                                                                                                  
 3c_identity_block_bn3 (BatchNo  (None, 28, 28, 512)  2048       ['3c_identity_block_conv3[0][0]']
 rmalization)                                                                                     
                                                                                                  
 3c_identity_block_add (Add)    (None, 28, 28, 512)  0           ['3c_identity_block_bn3[0][0]',  
                                                                  '3b_identity_block_relu4[0][0]']
                                                                                                  
 3c_identity_block_relu4 (Activ  (None, 28, 28, 512)  0          ['3c_identity_block_add[0][0]']  
 ation)                                                                                           
                                                                                                  
 3d_identity_block_conv1 (Conv2  (None, 28, 28, 128)  65664      ['3c_identity_block_relu4[0][0]']
 D)                                                                                               
                                                                                                  
 3d_identity_block_bn1 (BatchNo  (None, 28, 28, 128)  512        ['3d_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 3d_identity_block_relu1 (Activ  (None, 28, 28, 128)  0          ['3d_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 3d_identity_block_conv2 (Conv2  (None, 28, 28, 128)  147584     ['3d_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 3d_identity_block_bn2 (BatchNo  (None, 28, 28, 128)  512        ['3d_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 3d_identity_block_relu2 (Activ  (None, 28, 28, 128)  0          ['3d_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 3d_identity_block_conv3 (Conv2  (None, 28, 28, 512)  66048      ['3d_identity_block_relu2[0][0]']
 D)                                                                                               
                                                                                                  
 3d_identity_block_bn3 (BatchNo  (None, 28, 28, 512)  2048       ['3d_identity_block_conv3[0][0]']
 rmalization)                                                                                     
                                                                                                  
 3d_identity_block_add (Add)    (None, 28, 28, 512)  0           ['3d_identity_block_bn3[0][0]',  
                                                                  '3c_identity_block_relu4[0][0]']
                                                                                                  
 3d_identity_block_relu4 (Activ  (None, 28, 28, 512)  0          ['3d_identity_block_add[0][0]']  
 ation)                                                                                           
                                                                                                  
 4a_conv_block_conv1 (Conv2D)   (None, 14, 14, 256)  131328      ['3d_identity_block_relu4[0][0]']
                                                                                                  
 4a_conv_block_bn1 (BatchNormal  (None, 14, 14, 256)  1024       ['4a_conv_block_conv1[0][0]']    
 ization)                                                                                         
                                                                                                  
 4a_conv_block_relu1 (Activatio  (None, 14, 14, 256)  0          ['4a_conv_block_bn1[0][0]']      
 n)                                                                                               
                                                                                                  
 4a_conv_block_conv2 (Conv2D)   (None, 14, 14, 256)  590080      ['4a_conv_block_relu1[0][0]']    
                                                                                                  
 4a_conv_block_bn2 (BatchNormal  (None, 14, 14, 256)  1024       ['4a_conv_block_conv2[0][0]']    
 ization)                                                                                         
                                                                                                  
 4a_conv_block_relu2 (Activatio  (None, 14, 14, 256)  0          ['4a_conv_block_bn2[0][0]']      
 n)                                                                                               
                                                                                                  
 4a_conv_block_conv3 (Conv2D)   (None, 14, 14, 1024  263168      ['4a_conv_block_relu2[0][0]']    
                                )                                                                 
                                                                                                  
 4a_conv_block_res_conv (Conv2D  (None, 14, 14, 1024  525312     ['3d_identity_block_relu4[0][0]']
 )                              )                                                                 
                                                                                                  
 4a_conv_block_bn3 (BatchNormal  (None, 14, 14, 1024  4096       ['4a_conv_block_conv3[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 4a_conv_block_res_bn (BatchNor  (None, 14, 14, 1024  4096       ['4a_conv_block_res_conv[0][0]'] 
 malization)                    )                                                                 
                                                                                                  
 4a_conv_block_add (Add)        (None, 14, 14, 1024  0           ['4a_conv_block_bn3[0][0]',      
                                )                                 '4a_conv_block_res_bn[0][0]']   
                                                                                                  
 4a_conv_block_relu4 (Activatio  (None, 14, 14, 1024  0          ['4a_conv_block_add[0][0]']      
 n)                             )                                                                 
                                                                                                  
 4b_identity_block_conv1 (Conv2  (None, 14, 14, 256)  262400     ['4a_conv_block_relu4[0][0]']    
 D)                                                                                               
                                                                                                  
 4b_identity_block_bn1 (BatchNo  (None, 14, 14, 256)  1024       ['4b_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4b_identity_block_relu1 (Activ  (None, 14, 14, 256)  0          ['4b_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 4b_identity_block_conv2 (Conv2  (None, 14, 14, 256)  590080     ['4b_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 4b_identity_block_bn2 (BatchNo  (None, 14, 14, 256)  1024       ['4b_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4b_identity_block_relu2 (Activ  (None, 14, 14, 256)  0          ['4b_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 4b_identity_block_conv3 (Conv2  (None, 14, 14, 1024  263168     ['4b_identity_block_relu2[0][0]']
 D)                             )                                                                 
                                                                                                  
 4b_identity_block_bn3 (BatchNo  (None, 14, 14, 1024  4096       ['4b_identity_block_conv3[0][0]']
 rmalization)                   )                                                                 
                                                                                                  
 4b_identity_block_add (Add)    (None, 14, 14, 1024  0           ['4b_identity_block_bn3[0][0]',  
                                )                                 '4a_conv_block_relu4[0][0]']    
                                                                                                  
 4b_identity_block_relu4 (Activ  (None, 14, 14, 1024  0          ['4b_identity_block_add[0][0]']  
 ation)                         )                                                                 
                                                                                                  
 4c_identity_block_conv1 (Conv2  (None, 14, 14, 256)  262400     ['4b_identity_block_relu4[0][0]']
 D)                                                                                               
                                                                                                  
 4c_identity_block_bn1 (BatchNo  (None, 14, 14, 256)  1024       ['4c_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4c_identity_block_relu1 (Activ  (None, 14, 14, 256)  0          ['4c_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 4c_identity_block_conv2 (Conv2  (None, 14, 14, 256)  590080     ['4c_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 4c_identity_block_bn2 (BatchNo  (None, 14, 14, 256)  1024       ['4c_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4c_identity_block_relu2 (Activ  (None, 14, 14, 256)  0          ['4c_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 4c_identity_block_conv3 (Conv2  (None, 14, 14, 1024  263168     ['4c_identity_block_relu2[0][0]']
 D)                             )                                                                 
                                                                                                  
 4c_identity_block_bn3 (BatchNo  (None, 14, 14, 1024  4096       ['4c_identity_block_conv3[0][0]']
 rmalization)                   )                                                                 
                                                                                                  
 4c_identity_block_add (Add)    (None, 14, 14, 1024  0           ['4c_identity_block_bn3[0][0]',  
                                )                                 '4b_identity_block_relu4[0][0]']
                                                                                                  
 4c_identity_block_relu4 (Activ  (None, 14, 14, 1024  0          ['4c_identity_block_add[0][0]']  
 ation)                         )                                                                 
                                                                                                  
 4d_identity_block_conv1 (Conv2  (None, 14, 14, 256)  262400     ['4c_identity_block_relu4[0][0]']
 D)                                                                                               
                                                                                                  
 4d_identity_block_bn1 (BatchNo  (None, 14, 14, 256)  1024       ['4d_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4d_identity_block_relu1 (Activ  (None, 14, 14, 256)  0          ['4d_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 4d_identity_block_conv2 (Conv2  (None, 14, 14, 256)  590080     ['4d_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 4d_identity_block_bn2 (BatchNo  (None, 14, 14, 256)  1024       ['4d_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4d_identity_block_relu2 (Activ  (None, 14, 14, 256)  0          ['4d_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 4d_identity_block_conv3 (Conv2  (None, 14, 14, 1024  263168     ['4d_identity_block_relu2[0][0]']
 D)                             )                                                                 
                                                                                                  
 4d_identity_block_bn3 (BatchNo  (None, 14, 14, 1024  4096       ['4d_identity_block_conv3[0][0]']
 rmalization)                   )                                                                 
                                                                                                  
 4d_identity_block_add (Add)    (None, 14, 14, 1024  0           ['4d_identity_block_bn3[0][0]',  
                                )                                 '4c_identity_block_relu4[0][0]']
                                                                                                  
 4d_identity_block_relu4 (Activ  (None, 14, 14, 1024  0          ['4d_identity_block_add[0][0]']  
 ation)                         )                                                                 
                                                                                                  
 4e_identity_block_conv1 (Conv2  (None, 14, 14, 256)  262400     ['4d_identity_block_relu4[0][0]']
 D)                                                                                               
                                                                                                  
 4e_identity_block_bn1 (BatchNo  (None, 14, 14, 256)  1024       ['4e_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4e_identity_block_relu1 (Activ  (None, 14, 14, 256)  0          ['4e_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 4e_identity_block_conv2 (Conv2  (None, 14, 14, 256)  590080     ['4e_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 4e_identity_block_bn2 (BatchNo  (None, 14, 14, 256)  1024       ['4e_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4e_identity_block_relu2 (Activ  (None, 14, 14, 256)  0          ['4e_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 4e_identity_block_conv3 (Conv2  (None, 14, 14, 1024  263168     ['4e_identity_block_relu2[0][0]']
 D)                             )                                                                 
                                                                                                  
 4e_identity_block_bn3 (BatchNo  (None, 14, 14, 1024  4096       ['4e_identity_block_conv3[0][0]']
 rmalization)                   )                                                                 
                                                                                                  
 4e_identity_block_add (Add)    (None, 14, 14, 1024  0           ['4e_identity_block_bn3[0][0]',  
                                )                                 '4d_identity_block_relu4[0][0]']
                                                                                                  
 4e_identity_block_relu4 (Activ  (None, 14, 14, 1024  0          ['4e_identity_block_add[0][0]']  
 ation)                         )                                                                 
                                                                                                  
 4f_identity_block_conv1 (Conv2  (None, 14, 14, 256)  262400     ['4e_identity_block_relu4[0][0]']
 D)                                                                                               
                                                                                                  
 4f_identity_block_bn1 (BatchNo  (None, 14, 14, 256)  1024       ['4f_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4f_identity_block_relu1 (Activ  (None, 14, 14, 256)  0          ['4f_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 4f_identity_block_conv2 (Conv2  (None, 14, 14, 256)  590080     ['4f_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 4f_identity_block_bn2 (BatchNo  (None, 14, 14, 256)  1024       ['4f_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 4f_identity_block_relu2 (Activ  (None, 14, 14, 256)  0          ['4f_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 4f_identity_block_conv3 (Conv2  (None, 14, 14, 1024  263168     ['4f_identity_block_relu2[0][0]']
 D)                             )                                                                 
                                                                                                  
 4f_identity_block_bn3 (BatchNo  (None, 14, 14, 1024  4096       ['4f_identity_block_conv3[0][0]']
 rmalization)                   )                                                                 
                                                                                                  
 4f_identity_block_add (Add)    (None, 14, 14, 1024  0           ['4f_identity_block_bn3[0][0]',  
                                )                                 '4e_identity_block_relu4[0][0]']
                                                                                                  
 4f_identity_block_relu4 (Activ  (None, 14, 14, 1024  0          ['4f_identity_block_add[0][0]']  
 ation)                         )                                                                 
                                                                                                  
 5a_conv_block_conv1 (Conv2D)   (None, 7, 7, 512)    524800      ['4f_identity_block_relu4[0][0]']
                                                                                                  
 5a_conv_block_bn1 (BatchNormal  (None, 7, 7, 512)   2048        ['5a_conv_block_conv1[0][0]']    
 ization)                                                                                         
                                                                                                  
 5a_conv_block_relu1 (Activatio  (None, 7, 7, 512)   0           ['5a_conv_block_bn1[0][0]']      
 n)                                                                                               
                                                                                                  
 5a_conv_block_conv2 (Conv2D)   (None, 7, 7, 512)    2359808     ['5a_conv_block_relu1[0][0]']    
                                                                                                  
 5a_conv_block_bn2 (BatchNormal  (None, 7, 7, 512)   2048        ['5a_conv_block_conv2[0][0]']    
 ization)                                                                                         
                                                                                                  
 5a_conv_block_relu2 (Activatio  (None, 7, 7, 512)   0           ['5a_conv_block_bn2[0][0]']      
 n)                                                                                               
                                                                                                  
 5a_conv_block_conv3 (Conv2D)   (None, 7, 7, 2048)   1050624     ['5a_conv_block_relu2[0][0]']    
                                                                                                  
 5a_conv_block_res_conv (Conv2D  (None, 7, 7, 2048)  2099200     ['4f_identity_block_relu4[0][0]']
 )                                                                                                
                                                                                                  
 5a_conv_block_bn3 (BatchNormal  (None, 7, 7, 2048)  8192        ['5a_conv_block_conv3[0][0]']    
 ization)                                                                                         
                                                                                                  
 5a_conv_block_res_bn (BatchNor  (None, 7, 7, 2048)  8192        ['5a_conv_block_res_conv[0][0]'] 
 malization)                                                                                      
                                                                                                  
 5a_conv_block_add (Add)        (None, 7, 7, 2048)   0           ['5a_conv_block_bn3[0][0]',      
                                                                  '5a_conv_block_res_bn[0][0]']   
                                                                                                  
 5a_conv_block_relu4 (Activatio  (None, 7, 7, 2048)  0           ['5a_conv_block_add[0][0]']      
 n)                                                                                               
                                                                                                  
 5b_identity_block_conv1 (Conv2  (None, 7, 7, 512)   1049088     ['5a_conv_block_relu4[0][0]']    
 D)                                                                                               
                                                                                                  
 5b_identity_block_bn1 (BatchNo  (None, 7, 7, 512)   2048        ['5b_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 5b_identity_block_relu1 (Activ  (None, 7, 7, 512)   0           ['5b_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 5b_identity_block_conv2 (Conv2  (None, 7, 7, 512)   2359808     ['5b_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 5b_identity_block_bn2 (BatchNo  (None, 7, 7, 512)   2048        ['5b_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 5b_identity_block_relu2 (Activ  (None, 7, 7, 512)   0           ['5b_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 5b_identity_block_conv3 (Conv2  (None, 7, 7, 2048)  1050624     ['5b_identity_block_relu2[0][0]']
 D)                                                                                               
                                                                                                  
 5b_identity_block_bn3 (BatchNo  (None, 7, 7, 2048)  8192        ['5b_identity_block_conv3[0][0]']
 rmalization)                                                                                     
                                                                                                  
 5b_identity_block_add (Add)    (None, 7, 7, 2048)   0           ['5b_identity_block_bn3[0][0]',  
                                                                  '5a_conv_block_relu4[0][0]']    
                                                                                                  
 5b_identity_block_relu4 (Activ  (None, 7, 7, 2048)  0           ['5b_identity_block_add[0][0]']  
 ation)                                                                                           
                                                                                                  
 5c_identity_block_conv1 (Conv2  (None, 7, 7, 512)   1049088     ['5b_identity_block_relu4[0][0]']
 D)                                                                                               
                                                                                                  
 5c_identity_block_bn1 (BatchNo  (None, 7, 7, 512)   2048        ['5c_identity_block_conv1[0][0]']
 rmalization)                                                                                     
                                                                                                  
 5c_identity_block_relu1 (Activ  (None, 7, 7, 512)   0           ['5c_identity_block_bn1[0][0]']  
 ation)                                                                                           
                                                                                                  
 5c_identity_block_conv2 (Conv2  (None, 7, 7, 512)   2359808     ['5c_identity_block_relu1[0][0]']
 D)                                                                                               
                                                                                                  
 5c_identity_block_bn2 (BatchNo  (None, 7, 7, 512)   2048        ['5c_identity_block_conv2[0][0]']
 rmalization)                                                                                     
                                                                                                  
 5c_identity_block_relu2 (Activ  (None, 7, 7, 512)   0           ['5c_identity_block_bn2[0][0]']  
 ation)                                                                                           
                                                                                                  
 5c_identity_block_conv3 (Conv2  (None, 7, 7, 2048)  1050624     ['5c_identity_block_relu2[0][0]']
 D)                                                                                               
                                                                                                  
 5c_identity_block_bn3 (BatchNo  (None, 7, 7, 2048)  8192        ['5c_identity_block_conv3[0][0]']
 rmalization)                                                                                     
                                                                                                  
 5c_identity_block_add (Add)    (None, 7, 7, 2048)   0           ['5c_identity_block_bn3[0][0]',  
                                                                  '5b_identity_block_relu4[0][0]']
                                                                                                  
 5c_identity_block_relu4 (Activ  (None, 7, 7, 2048)  0           ['5c_identity_block_add[0][0]']  
 ation)                                                                                           
                                                                                                  
 avg_pooling (AveragePooling2D)  (None, 1, 1, 2048)  0           ['5c_identity_block_relu4[0][0]']
                                                                                                  
 flatten (Flatten)              (None, 2048)         0           ['avg_pooling[0][0]']            
                                                                                                  
 fc1000 (Dense)                 (None, 1000)         2049000     ['flatten[0][0]']                
                                                                                                  
==================================================================================================
Total params: 25,636,712
Trainable params: 25,583,592
Non-trainable params: 53,120
__________________________________________________________________________________________________

10.编译模型

#设置初始学习率
initial_learning_rate = 1e-3
opt = tf.keras.optimizers.Adam(learning_rate=initial_learning_rate)
model.compile(optimizer=opt,
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])


11.训练模型

'''训练模型'''
epochs = 10
history = model.fit(
    train_ds,
    validation_data=val_ds,
    epochs=epochs
)

训练记录如下:

Epoch 1/10
57/57 [==============================] - 8s 54ms/step - loss: 1.3797 - accuracy: 0.7212 - val_loss: 4021.5437 - val_accuracy: 0.2301
Epoch 2/10
57/57 [==============================] - 2s 40ms/step - loss: 0.4452 - accuracy: 0.8695 - val_loss: 22.2432 - val_accuracy: 0.3274
Epoch 3/10
57/57 [==============================] - 2s 40ms/step - loss: 0.3566 - accuracy: 0.8761 - val_loss: 21.0750 - val_accuracy: 0.2743
Epoch 4/10
57/57 [==============================] - 2s 40ms/step - loss: 0.1800 - accuracy: 0.9469 - val_loss: 4.8014 - val_accuracy: 0.3894
Epoch 5/10
57/57 [==============================] - 2s 40ms/step - loss: 0.0815 - accuracy: 0.9646 - val_loss: 0.2824 - val_accuracy: 0.9204
Epoch 6/10
57/57 [==============================] - 2s 40ms/step - loss: 0.0380 - accuracy: 0.9867 - val_loss: 1.8555 - val_accuracy: 0.8053
Epoch 7/10
57/57 [==============================] - 2s 40ms/step - loss: 0.0421 - accuracy: 0.9889 - val_loss: 1.5017 - val_accuracy: 0.7080
Epoch 8/10
57/57 [==============================] - 2s 41ms/step - loss: 0.0060 - accuracy: 0.9978 - val_loss: 0.7932 - val_accuracy: 0.8407
Epoch 9/10
57/57 [==============================] - 2s 41ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.1006 - val_accuracy: 0.9469
Epoch 10/10
57/57 [==============================] - 2s 41ms/step - loss: 6.7589e-04 - accuracy: 1.0000 - val_loss: 0.0842 - val_accuracy: 0.9735
......


12.模型评估

'''模型评估'''
acc = history.history['accuracy']
val_acc = history.history['val_accuracy']
loss = history.history['loss']
val_loss = history.history['val_loss']
epochs_range = range(len(loss))
plt.figure(figsize=(12, 4))
plt.subplot(1, 2, 1)
plt.plot(epochs_range, acc, label='Training Accuracy')
plt.plot(epochs_range, val_acc, label='Validation Accuracy')
plt.legend(loc='lower right')
plt.title('Training and Validation Accuracy')
plt.subplot(1, 2, 2)
plt.plot(epochs_range, loss, label='Training Loss')
plt.plot(epochs_range, val_loss, label='Validation Loss')
plt.legend(loc='upper right')
plt.title('Training and Validation Loss')
plt.show()

在这里插入图片描述
13.图像预测

'''指定图片进行预测'''
# 采用加载的模型(new_model)来看预测结果
plt.figure(figsize=(10, 5))  # 图形的宽为10高为5
plt.suptitle("预测结果展示", fontsize=10)
for images, labels in val_ds.take(1):
    for i in range(8):
        ax = plt.subplot(2, 4, i + 1)

        # 显示图片
        plt.imshow(images[i].numpy().astype("uint8"))

        # 需要给图片增加一个维度
        img_array = tf.expand_dims(images[i], 0)

        # 使用模型预测图片中的人物
        predictions = model.predict(img_array)
        plt.title(class_names[np.argmax(predictions)],fontsize=10)

        plt.axis("off")
plt.show()

在这里插入图片描述

三、知识点详解

1. CNN算法发展

在这里插入图片描述

首先借用一下来自于网络的插图,在这张图上列出了一些有里程碑意义的、经典卷积神经网络。评估网络的性能,一个维度是识别精度,另一个维度则是网络的复杂度(计算量)。从这张图里,我们能看到:
(1)2012年,AlexNet是由Alex Krizhevsky、Ilya Sutskever和Geoffrey Hinton在2012年ImageNet图像分类竞赛中提出的一种经典的卷积神经网络。AlexNet是首个深层卷积神经网络,同时也引入了ReLU激活函数、局部归一化、数据增强和Dropout 处理。
(2)VGG-16和VGG-19,这是依靠多层卷积+池化层堆叠而成的一个网络,其性能在当时也还不错,但是计算量巨大。VGG-16的网络结构在前面已经总结过,是将深层网络结构分为几个组,每组堆叠数量不等的Conv-ReLU层,并在最后一层使用MaxPool缩减特征图尺寸。 (3)GoogLeNet(也就是Inception V1),这是一个提出了使用并联卷积结构、且在每个通路中使用不同卷积核的网络,并且随后衍生出V2、V3、V4等一系列网络结构,构成一个家族。
(4)ResNet,有V1、V2、NeXt等不同的版本,这是一个提出恒等映射概念、具有短路直接路径、模块化的网络结构,可以很方便地扩展为18~1001层(ResNet-18、ResNet-34、ResNet-50、ResNet-101中的数字都是表示网络层数)。
(5)DenseNet,这是一种具有前级特征重用、层间直连、结构递归扩展等特点的卷积网络。

下图是另一篇文章总结的cnn发展史
在这里插入图片描述

2. 残差网络介绍

深度残差网络ResNet(deep residual network)在2015年由何凯明等提出,因为它简单与实用并存,随后很多研究都是建立在ResNet-50或者ResNet-101基础上完成。
ResNet主要解决深度卷积网络在深度加深时候的”退化“问题。在一般的卷积神经网络中,增大网络深度后带来的第一个问题就是梯度消失或梯度爆炸,这个问题Szegedy提出的BN层后被顺利解决。BN层能对各层的输出做归一化,这样梯度在反向层层传递后仍能保持大小稳定,不会出现过大或过小的情况。但是作者发现加了BN层后再加大深度仍然不容易收敛,其提到了第二个问题–准确率下降问题:层级大到一定程度时准确率就会饱和,然后迅速下降,这种下降既不是梯度消失引起的,也不是过拟合造成的,而是由于网络过于复杂,以至于光靠不加约束的放养式的训练很难达到理想的准确率。
准确率下降问题不是网络结构本身的问题,而是现有的训练方式不够理想造成的。当前广泛使用的优化器,无论是SGD,还是RMSProp,或是Adam,都无法在网络深度变大后达到理论上最优的收敛结果。
作者在文中证明了只要有合适的网络结构,更深的网络肯定会比较浅的网络效果好。证明过程也很简单:假设在一种网络A的后面添加几层形成新的网络B,如果增加的层级只是对A的输出做了个恒等映射(identity mapping),即A的输出经过新增的层级变成B的输出后没有发生变化,这样网络A和网络B的错误率就是相等的,也就证明了加深后的网络不会比加深前的网络效果差。

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图1 残差模块????
何凯明提出了一种残差结构来实现上述恒等映射(如上图所示):整个模块除了正常的卷积层输出外,还有一个分支把输入直接连到输出上,该分支输出和卷积的输出做算术相加得到最终的输出,用公式表达就是H(x)=F(x)+x,其中x是输入,F(x)是卷积分支的输出,H(x)是整个结构的输出。可以证明如果F(x)分支中所有参数都是0,H(x)=x,即H(x)与x为恒等映射。残差结构是人为的制造了恒等映射,能让整个结构朝着恒等映射的方向去收敛,确保最终的错误率不会因为深度的变大而越来越差。如果一个网络通过简单的手工设置参数值就能达到想要的结果,那这种结构就很容易通过训练来收敛到该结果,这是一条设计复杂的网络时通用的规则。
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图2 两种残差模块
图2 左边的单元为ResNet两层的残差单元,两层的残差单元包含两个相同输出通道数的33卷积,只是用于较浅的ResNet网络,对较深的网络主要使用三层的残差单元。三层的残差单元又称为bottleneck结构,先用一个11卷积进行降维,最后用1*1升维恢复原有的维度。另外,如果有输入输出维度不同的情况,可以对输入做一个线性映射变换维度,再连接后面的层。三层的残差单元对于相同数量的层又减少了参数量,因此可以拓展更深的模型。通过残差单元的组合有经典的ResNet-50,ResNet-101等网络结构。

何恺明的这篇文章:Deep Residual Learning for Image Recognition.pdf

BP算法基于梯度下降策略,以目标的负梯度方向对参数进行调整,参数的更新为 w←w+Δw,给定 学习速率 α,得出 Δw = ?α * ?Loss / ?w
根据 链式求导法则,更新梯度信息,?fn / ?fm 其实就是 对激活函数进行求导
当层数增加,?fn / ?fm < 1 → 梯度消失
当层数增加,?fn / ?fm > 1 → 梯度爆炸
在统计学中,残差的初始定义为:实际观测值 与 估计值 (拟合值) 的差值
在神经网络中,残差为恒等映射 H(X) 与 跨层连接 X 的差值
残差元结构图,两部分组成:恒等映射 H(X) + 跨层连接 X,使得前向传播过程为线性,而非连乘

残差网络的基本思路:在原神经网络结构基础上,添加跨层跳转连接,形成残差元 (identity block),即 H(X) = F(X) + X,包含了大量浅层网络的可能性
数学原理:在反向传播的过程中,链式求导会从连乘变成连加,即:(?fn / ?fm) * (1 + (?fm / ?fo)),可以有效解决 梯度消失 & 梯度爆炸 问题

参考链接:【CV】04_残差网络【梯度消失 & 梯度爆炸】

2 残差网络解决了什么

残差网络是为了解决神经网络隐藏层过多时,而引起的网络退化问题。退化(degradation)问题是指:当网络隐藏层变多时,网络的准确度达到饱和然后急剧退化,而且这个退化不是由于过拟合引起的。

拓展:深度神经网络的"两朵乌云"

梯度弥散/爆炸
简单来讲就是网络太深了,会导致模型训练难以收敛。这个问题可以被标准初始化和中间层正规化的方法有效控制。

网络退化
随着网络深度增加,网络的表现先是逐渐增加至饱和,然后迅速下降,这个退化不是由过拟合引起的。

3 ResNet的各种网络结构图

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4 resnet18&resnet50网络图

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参考链接:resnet18 50网络结构以及pytorch实现代码

ResNet-50有两个基本的块,分别名为Conv Block和Identity Block
首先说说Conv Block,也就是第一个实线方框中虚线连接的三层:
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可以看到,总体的思路是先通过1×1的卷积对特征图像进行降维,做一次3×3的卷积操作,最后再通过1×1卷积恢复维度,后面跟着BN和ReLU层;虚线处用256个1×1的卷积网络,将maxpool的输出降维到255×56×56。
再说Identity Block,
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也就是实线连接所示,不经过卷积网络降维,直接将输入加到最后的1×1卷积输出上。
经过后面的Block,经过平均池化和全连接,用softmax实现回归。
参考链接:ResNet-50网络理解

Resnet50简化画法如下:在这里插入图片描述

2 SoftMax以及它的实现原理

SoftMax要处理多个类别分类的问题。并且,需要把每个分类的得分值换算成概率,同时解决两个分类得分值接近的问题。

先从公式上看,SoftMmax是怎么做到的。

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公式中,每个 z 就对应了多个分类的得分值。SoftMax对得分值进行了如下处理:

以e为底数进行了指数运算,算出每个分类的 eZi,作为公式的分子

分母为各分类得分指数运算的加和。

根据公式很自然可以想到,各个分类的SoftMax值加在一起是1,也就是100%。

所以,每个分类的SoftMax的值,就是将得分转化为了概率,所有分类的概率加在一起是100%。

这个公式很自然的就解决了从得分映射到概率的问题。那,它又是怎么解决两个得分相近的问题的呢?

其实也很简单,重点在选择的指数操作上。我们知道指数的曲线是下面的样子。

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指数曲线,恒大于零,并且在正半轴,离零越远,增长越快(指数增长)

指数增长的特性就是,横轴变化很小的量,纵轴就会有很大的变化。所以,从1.9变化到2.1,经过指数的运算,两者的差距立马被的拉大了。whaosoft aiot http://143ai.com

从而,我们可以更加明确的知道,图片的分类应该属于最大的那个。下面是将猫、狗、人三个分类经过SoftMax计算之后得到的概率。

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可以看到,分类是猫的概率遥遥领先。所以,神经网络在经过softmax层之后,会以70%的概率,认为这张图片是一张猫。

这就是SoftMax的底层原理。

指数让得分大的分类最终的概率更大,得分小的分类最终的概率更小,而得分为负数的分类,几乎可以忽略。
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参考链接:Resnet50算法原理

总结

通过本次的学习,了解了cnn的发展史,了解了残差网络可以解决梯度消失、爆炸及网络退化的问题,并了解了softmax的实现原理与作用。

文章来源:https://blog.csdn.net/LittleRuby/article/details/135120650
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