push 20220529

Author: Caczhtus

.idea/.gitignore

@@ -1,2 +1,73 @@
-# deeplearning-resnet-impl
-Residual network with 18 layers based on mnist handwritten digital image dataset.
+# 基于ResNet18的数字图像检测
+
+## 简介
+
+基于『common』包下的卷积层、池化层等基础层，实现了何凯明博士在『Deep Residual Learning for Image Recognition』论文中提到的残差单元，并拼接为『ResNet18』
+
+## 快速开始
+
+1. 下载数据集
+
+```
+python mnist.py
+```
+
+2. 训练并测试
+
+```python
+python unit_test.py
+```
+
+## 代码结构
+
+```
+.
+├── common
+│   ├── functions.py
+│   ├── gradient.py
+│   ├── __init__.py
+│   ├── layers.py
+│   ├── multi_layer_net_extend.py
+│   ├── multi_layer_net.py
+│   ├── optimizer.py
+│   ├── __pycache__
+│   │   ├── functions.cpython-38.pyc
+│   │   ├── __init__.cpython-38.pyc
+│   │   ├── layers.cpython-38.pyc
+│   │   ├── optimizer.cpython-38.pyc
+│   │   ├── trainer.cpython-38.pyc
+│   │   └── util.cpython-38.pyc
+│   ├── trainer.py
+│   └── util.py
+├── mnist.pkl
+├── mnist.py
+├── __pycache__
+│   ├── mnist.cpython-38.pyc
+│   ├── Residual.cpython-38.pyc
+│   └── ResNet18.cpython-38.pyc
+├── Residual.py
+├── ResNet18.py
+├── t10k-images-idx3-ubyte.gz
+├── t10k-labels-idx1-ubyte.gz
+├── train-images-idx3-ubyte.gz
+├── train-labels-idx1-ubyte.gz
+└── unit_test.py
+```
+
+## 说明
+
+目前本代码还有很多不足，仅供学习参考。后续有能力再进行优化补全。
+
+- base-resnet-block
+- resnet18
+- 普通卷积层
+- 平均池化层
+- 最大池化层
+- 线性变换层
+- 训练器
+
+## 参考
+
+1. [https://arxiv.org/pdf/1512.03385.pdf](https://arxiv.org/pdf/1512.03385.pdf)
+2. [ZhangXinNan/deep_learning_from_scratch](https://github.com/ZhangXinNan/deep_learning_from_scratch)
+3. 《深度学习入门——基于Python的理论与实现》作者：斋藤康毅 译者：陆宇杰