预训练ResNet50-keras

import tensorflow as tf
from tensorflow import keras

resnet = keras.applications.ResNet50(weights="imagenet",include_top=False)

Downloading data from https://github.com/keras-team/keras-applications/releases/download/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5

resnet.summary()

x = tf.random.normal([4,224,224,3])
out = resnet(x)

########全局池化层降维
global_average_layer = keras.layers.GlobalAveragePooling2D()  
x = tf.random.normal([4,7,7,2048])
out = global_average_layer(x)     #####输出(4,2048)
fc = keras.layers.Dense(100)

myNet = keras.Sequential([resnet,global_average_layer,fc])
mynet.summary()