Pytorch-Flask-Starter

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Pytorch-Flask-Starter

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🐍+🔥This project is aimed to help Pytorch machine learning developers to quickly build a Flask web app in a Docker container ready to be deployed.

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# Flask/Pytorch/Docker starter app

This project is aimed to help machine learning developers to quickly build and deploy a Flask web app that take advantage of their machine learning  ready PyTorch model. The documentation explains how to get up and running with either virtualenv or Docker.

![Website mockup](https://raw.githubusercontent.com/imadtoubal/Pytorch-Flask-Starter/master/assets/screenshot.png)

This website is deployed in Heroku: https://flaskpytorch.herokuapp.com/

By default, this app uses MobileNetV2 image classifier that was pre-trained on the ImageNet dataset. This can be easily changed with any custom deep learning model.

## Getting Started (using Python virtualenv)

You need to have Python installed in your computer.

1. Install `virtualenv`: 
    ```
    pip install virtualenv
    ```
2. Create a Python virtual environment:
    ```
    virtualenv venv
    ```
3. Activate virtual environment:
    1. Windows:
    ```
    cd venv\Scripts
    activate
    cd ..\..
    ```
    2. Lunix / Mac:
    ```
    source venv/bin/activate
    ```
4. Install libraries:
   
   ```
   pip install -r requirements.txt
   ```

### Run the code

* Run the app:
    ```
    flask run
    ```
* Run on a specific port:
    ```
    flask run -p <port>
    ```

## Getting Started (using Docker)

1. Create a Docker image
    ```
    docker build -t pytorchflask .
    ```
    This will create an image with the name `pytorchflask`. You can replace that with a custom name for your app.

2. Run the docker image
    ```
    docker run -d -p 127.0.0.1:5000:80 pytorchflask
    ```
    This will run the app on port `5000`. You can replace that with which ever port that is more suitable.

## Deploying to Heroku

- Create Heroku app
    ```
    heroku create 
    git push heroku master
    ```
    
OR

- Add to existing Heroku app
    ```
    heroku git:remote -a <your-app-name>
    git push heroku master
    ```

## Changing the model

1. Go to `models.py`
2. Follow the structure of the class `MobileNet`to create a custom model class
3. Use your class in `app.py`

## Built With

* [Pytorch](https://pytorch.org/) - The Machine Learning framework used
* [Flask](http://flask.palletsprojects.com/en/1.1.x/) - The web server library

## Authors

* **Imad Eddine Toubal** - *Initial work* - [imadtoubal](https://github.com/imadtoubal)

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details

Happy coding!

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