Keras-rest-server: A simple rest implementation for loading and serving keras models

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About:

This repository contains a very simple server implemented in flask which loads a a simple neural network model trained using Keras from its saved-weights and model.

In this example a very simple case of XOR is considered.

Getting started:

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1. Install Anaconda:

https://docs.continuum.io/anaconda/install

2. Clone this repository

git clone https://github.com/ansrivas/keras-rest-server.git
cd keras-rest-server

3. Create a new environment ( Change python=2 or python=3) and activate it:

conda create --name keras-server -y python=2
source activate keras-server

4. Install all the dependencies:

conda env update -n keras-server  --file requirements.txt

5. To remove the environment run:

conda remove -n keras-server --all -y

Usage

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Run to generate pickle files:

python createpickles.py

Run the server (defaults to http://localhost:7171)

python server.py

Send a post request to this server to test your model

python client.py