This project demonstrates an object detection microservice using the YOLOv5 model and FastAPI. Given a byte array as input, the service outputs a response in the following JSON format:

response_data = {
    "bounding_boxes": [...],
    "confidence_scores": [...],
    "classes": [...]
}

To install and run this project, follow these steps:

1. Clone this repository to your local machine:

git clone https://github.com/ismailousa/yolo-detector.git

2. Navigate to the project directory:

cd yolo-detector

3. Use Poetry to install the project dependencies:

poetry install 

To run the Yolo detector service, execute the following command:

poetry run ./run.sh

This will start the server, and you can use the following endpoint for object detection:

POST /detect_objects/: Upload an image as a byte array to this endpoint to receive object detection results in the specified response format.

A quick demo can also be started by:

poetry run python demo.py

This project is licensed under the MIT License