Face detection service

Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Contributing
5. License
6. Contact

About The Project

Its a service implemented by fast API and python opencv to detect faces in one given image

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Built With

python3.8, opencv, fast API, swagger, docker, docker compose, postgres sql, traefik, pytest

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Getting Started

Prerequisites

Install docker and docker compose

Installation

0. Clone the repo

   git clone https://github.com/hosnahoseini/face_detection-service.git 

1. run

   docker-compose -f solution/docker-compose.yml up 

2. then open http://0.0.0.0:8008/face/v1/docs#/ for face detection service in your browser or open http://0.0.0.0:8008/text/v1/docs#/ for text service in your browser

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Usage

choose file in /detect_with_image/ or put your image on input folder and enter image relative path (start after /app/) in /detect_with_path/{imagePath:path} API and see the last result in /result/ (you can use images in test folder to test)_

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Hosna Oyarhoseini - [email protected]

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