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

Related tags

Deep Learningmachine-learningdeep-learningimagescnnpython3pytorchclassificationdog-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）。 Resnet

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

Training set

  • 在CNN（Resnet）的基础上进行深度学习

    dog_cat_classcial.ipynb

4 Output prediction results

Prediction set

5 References

Owner
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