Deploy Keras Model with Flask as Web App in 10 Minutes

---

Getting started in 10 minutes

• Clone this repo
• Install requirements
• Run the script
• Check http://localhost:5000
• Done! 🎉

👇Screenshot:

---

Installation

Clone the repo

$ git clone https://github.com/mtobeiyf/keras-flask-deploy-webapp.git

Install requirements

$ pip install -r requirements.txt

Make sure you have the following installed:

• tensorflow
• keras
• flask
• pillow
• h5py
• gevent

Run with Python

Python 2.7 or 3.5+ are supported.

$ python app.py

Play

Open http://localhost:5000 and have fun. 😃

---

Customization

Use your own model

Place your trained .h5 file saved by model.save() under models directory.

Check the commented code in app.py.

Use other pre-trained model

See Keras applications for more available models such as DenseNet, MobilNet, NASNet, etc.

Check this section in app.py.

Frontend

Modify files in templates and static directory.

Deployment

To deploy it for public use, you need to have a public linux server.

Run the app

Run the script and hide it in background.

$ python app.py .

You can also use gunicorn instead of gevent

$ gunicorn -b 127.0.0.1:5000 app:app

More deployment options, check here

Set up Nginx

To redirect the traffic to your local app. Configure your Nginx .conf file.

server {
    listen  80;

    client_max_body_size 20M;

    location / {
        proxy_pass http://127.0.0.1:5000;
    }
}

More resources

Check Siraj's "How to Deploy a Keras Model to Production" video. The corresponding repo.

Building a simple Keras + deep learning REST API