Face Detection Service

A service providing REST API for face detection.

I created two endpoints:

• REST endpoint for "production" usage
• Web interface for easy result checking

The application uses Flask, OpenCV and Tensorflow. Detection is based on the MTCNN face detector.

There is a dockerfile available that allows to build and run the application easily. The container deployment uses gunicorn as a server.

I set up a simple CI using Github Actions. No docker image is pushed anywhere.

Installation

Docker

To build and run the application using docker-compose run: docker-compose -f docker-compose.yml up face_service

By default, the application listens on the 8000 port.

Manual install

apt-get -y install build-essential gcc g++ python3-dev python3-opencv

pip install --trusted-host pypi.python.org -r requirements.txt

Running with Flask: python3 main.py

Running with Gunicorn: sh entrypoint.sh

Usage

Web interface

Assuming that you have started the app locally, visit the: http://localhost:8000.

You should see following interface:

Detection is applied immediately after uploading an image. Image itself is lightened a bit to make boxes more visible.

REST API

curl --location --request POST 'localhost:8000/api/detect' \
--header 'Content-Type: image/jpeg' \
--data-binary '@examples/1.jpeg'

Example response

The service returns a JSON containing list of objects in a following form:

    {
        "box": [
            1820,
            352,
            29,
            41
        ],
        "confidence": 0.7826327085494995,
        "keypoints": {
            "left_eye": [
                1832,
                368
            ],
            "right_eye": [
                1844,
                366
            ],
            "nose": [
                1840,
                375
            ],
            "mouth_left": [
                1834,
                384
            ],
            "mouth_right": [
                1843,
                383
            ]
        }
    }
]

Box format: [x, y, width, height]

Features format: [x, y]