python 93% acc. CNN Dogs Vs Cats ( Pytorch )

Last update: May 22, 2022

Related tags

Deep Learning machine-learning deep-learning images cnn python3 pytorch classification dog-vs-cat

Overview

English | 简体中文（测试中...敬请期待）

Cnn-Classification-Dog-Vs-Cat 猫狗辨别

(pytorch版本) CNN Resnet18 的猫狗分类器，基于ResNet及其变体网路系列，对于一般的图像识别任务表现优异，模型精准度高达93%（小型样本）。

项目制作于本科大三学习 [認識人工智慧AI：企業人工智慧] 课堂期间，正好遇上本人对这方面感兴趣的阶段，所以选择了入门的深度学习项目练手，希望做为兴趣点激励自己学习！距离DDL只剩几天了，现阶段时间和精力有限，遂没有自建神经网络，只是利用了已训练的常用网络进行深度学习，以后找机会补上。

1 requirement

python3
matplotlib
numpy
pytorch
pandas
os
Images

2 Description of files

inputs: 包含猫狗训练和测试样本图片数据[下载地址]，经过特殊改良，其中训练集包含1000笔狗狗图片、1000笔猫咪图片，测试集包含100笔猫狗混合图片；
dog_cat_classcial.ipynb：主文件，训练后测试集精度约 93%
ckpt_resnet18_catdog.pth：基于CNN的预测模型
preds_resnet18.csv：预测后结果储存位置
true_test.csv：一笔正确的资料数据

3 Start training

印出部分训练集图片

在CNN（Resnet）的基础上进行深度学习
```
dog_cat_classcial.ipynb
```

4 Output prediction results

5 References

[1]. 猫狗图像数据来源： https://www.kaggle.com/c/dogs-vs-cats/data
[2]. 参考kaggle竞赛奖牌获得者项目 https://www.kaggle.com/uysimty/keras-cnn-dog-or-cat-classification

Owner

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