Skip to content

Latest commit

 

History

History
124 lines (58 loc) · 2.94 KB

README.md

File metadata and controls

124 lines (58 loc) · 2.94 KB
Raw

GluonCV_Training_Inference_Classification_API

This is a repository for a classification training and inference API using the Gluoncv toolkit. It's supported on both Windows and Linux Operating systems. Note: To be able to fast train a model with the training_API repository make sure to use git clone and avoid downloading the repository as ZIP because it will not download the needed files stored on git lfs but just the pointer instead

Build_the_API

Prerequisites

  • Ubuntu 18.04
  • Docker CE latest stable release
  • Docker-Compose (1.19.0 or higher)

How to check for prerequisites

To check if you have docker-ce installed:

​ docker --version

To check if you have docker-compose installed:

​ docker-compose --version

Install prerequisites

Ubuntu

Installing Prerequisites

  • If you don't have neither docker nor docker-compose use the following command

    ​ chmod +x install_full.sh && source install_full.sh

  • If you have docker ce installed and wish only to install docker-compose and perform necessary operations, use the following command

    ​ chmod +x install_compose.sh && source install_compose.sh

Windows 10

To install Docker on Windows, please follow the link.

Build the Solution

To build the solution, run the following command from the repository's root directory

docker-compose -f build.yml build

Run the Solution

To run the solution, run the following command from the repository's root directory

docker-compose -f run.yml up

After a successful run you should see something like the following:

Usage

  • If the app is deployed on your machine:

    • open your web browser and type the following: localhost:8000 or 127.0.0.1:8000 for the training API
    • open your web browser and type the following: localhost:4343 or 127.0.0.1:4343 for the Inference API

  • If the app is deployed on a different machine: open your web browser and type the following: <machine_ip>:<port>

Endpoints summary

Training_API

/train_model (POST)

Train a new model and pass the parameters using a json format object

load model

/train/{model_name} (POST)

Train a new model and give only the model name as parameter

detect image

Inference_API

/models (GET)

Loads all available models and returns every model with it's hashed value. Loaded models are stored and aren't loaded again.

load model

/models/{model_name}/image_classification (POST)

Train a new model and give only the model name as parameter

detect image

Acknowledgements

gluoncv Toolkit

gluoncv and mxnet

Elio Hanna