首先先导入所需要的库 import sys from matplotlib import pyplot from tensorflow.keras.utils import to_categorical from keras.models import Sequential from keras.layers import Conv2D from keras.layers import MaxPooling2D from keras.layers import Dense from keras.
笔者这几天在跟着莫烦学习TensorFlow,正好到迁移学习(至于什么是迁移学习,看这篇),莫烦老师做的是预测猫和老虎尺寸大小的学习.作为一个有为的学生,笔者当然不能再预测猫啊狗啊的大小啦,正好之前正好有做过猫狗大战数据集的图像分类,做好的数据都还在,二话不说,开撸. 既然是VGG16模型,当然首先上模型代码了: def conv_layers_simple_api(net_in): with tf.name_scope('preprocess'): # Notice that we inclu
我们用猫狗案例来表明在java中使用多态的好处: class Animal{ public Animal(){} public void eat(){ System.out.println("吃饭"); } public void sleep(){ System.out.println("睡觉"); } } class Cat extends Animal{ public Cat(){} public void eat(){ System.out.println(&
猫狗识别 数据集下载: 网盘链接:https://pan.baidu.com/s/1SlNAPf3NbgPyf93XluM7Fg 提取密码:hpn4 1. 要导入的包 import os import time import numpy as np import torch import torch.nn as nn import torch.nn.functional as F from torch.utils.data import DataLoader from torch.utils i