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README.md

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YOLO Server API example

This section an example implementation of a YOLO Server API, designed to facilitate object detection using the YOLO model. This guide provides information on how to use, configure, and understand the features of this API.

Usage

  1. Run the server:

    python app.py

    or

    gunicorn -w 1 -b 0.0.0.0:8000 "examples.object_detection_server_api.app:app"

  2. Send a request to the API:

    • Use tools like curl, Postman, or your web browser to send a request to the server.
    • Example using curl: 
      curl -X POST -F "file=@path/to/your/image.jpg" http://localhost:8000/detect

Features

  • Authentication: Secure the API with authentication mechanisms.
  • Caching: Improve performance with caching of detection results.
  • Model Download: Automated downloading and loading of the YOLO model.
  • Configuration: Flexible configuration options to customise the API.
  • Object Detection: Perform object detection on uploaded images using YOLO.
  • Error Handling: Robust error handling to manage different scenarios gracefully.

Configuration

The API can be configured through the config.py file. Below are some of the key configuration options available:

  • Server Settings:

    • HOST: The hostname to run the server on. Default is 0.0.0.0.
    • PORT: The port to run the server on. Default is 8000.

  • Model Settings:

    • MODEL_PATH: Path to the YOLO model file.
    • CONFIDENCE_THRESHOLD: Confidence threshold for object detection.

  • Cache Settings:

    • CACHE_ENABLED: Enable or disable caching. Default is True.
    • CACHE_EXPIRY: Cache expiry time in seconds. Default is 3600.

  • Authentication Settings:

    • AUTH_ENABLED: Enable or disable authentication. Default is True.
    • SECRET_KEY: Secret key for JWT authentication.

File Overview

  • app.py: Main application file that starts the server and defines the API endpoints.
  • auth.py: Handles authentication mechanisms.
  • cache.py: Implements caching functionalities.
  • config.py: Contains configuration settings for the API.
  • detection.py: Performs object detection using the YOLO model.
  • model_downloader.py: Handles downloading and loading of the YOLO model.
  • models.py: Defines data models and schemas.
  • security.py: Implements security features.

Ensure to review and adjust the configuration settings in config.py to suit your specific requirements.