README.md

Gradio Model Server Skeleton

This repository contains a Gradio skeleton application which can be used to rapid prototype a demonstration app for your next machine learning/deep learning model.

To experiment and get a feeling on how to use this skeleton, a sample YOLOv5 object detection model is included in this proejct. Follow the installation and setup instructions to run the deep learning application.

Pre-requisite & Setup

Ensure to have a Python environment before setting up, preferably Python 3.8+.

apt-get update
apt-get install ffmpeg libsm6 libxext6  -y

pip install -r requirements.txt

# for dev env, hot-reloading is enabled
gradio app.py

# for testing/UAT/prod env, ensure port number is cleared
python app.py --host 0.0.0.0 --port 7860

Docker alternative

Alternatively, you can use docker to containerize the Gradio application.

# REQUIRED
export docker_repo_name=gradio-ml-skeleton
export docker_tag=dev_latest

# build an image from Dockerfile
sh build_docker.sh

# creates a container layer over the image
sh launch_docker.sh

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