# LeNet-5

**Repository Path**: shang_qi_yue/LeNet-5

## Basic Information

- **Project Name**: LeNet-5
- **Description**: No description available
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-03-29
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# LeNet-5

This implements a slightly modified LeNet-5 [LeCun et al., 1998a] and achieves an accuracy of ~99% on the [MNIST dataset](http://yann.lecun.com/exdb/mnist/).


![Epoch Train Loss visualization](https://i.imgur.com/h4h7CrF.gif)

## Setup

Install all dependencies using the following command

```
$ pip install -r requirements.txt
```

## Usage

Start the `visdom` server for visualization

```
$ python -m visdom.server
```

Start the training procedure

```
$ python run.py
```

See epoch train loss live graph at [`http://localhost:8097`](http://localhost:8097).

The trained model will be exported as ONNX to `lenet.onnx`. The `lenet.onnx` file can be viewed with [Neutron](https://www.electronjs.org/apps/netron)

## References

[[1](http://yann.lecun.com/exdb/publis/pdf/lecun-98.pdf)] Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. "Gradient-based learning applied to document recognition." Proceedings of the IEEE, 86(11):2278-2324, November 1998.