This API provides a simple way to perform object detection using the YOLO (You Only Look Once) model implemented with Darknet, integrated with a Flask server. It allows users to send images to the server and receive JSON responses containing the result. Currently, this model can detect 80 objects

1. Clone the repository
2. git clone https://github.com/aravind-tronix/object-detection-web-client.git
3. cd object-detection-web-client
4. Install required packages by pip install -r requirements.txt
5. Download the model manually since it exceeds 100mb.
6. Place the model file into the project root folder.
7. Start the Flask server python app.py
8. Start the Front-end app >>> https://github.com/aravind-tronix/object-detection-webapp

The architecture of this API involves four main components:

1. YOLO (You Only Look Once) is a state-of-the-art, real-time object detection system.
2. Darknet is an open-source neural network framework written in C and CUDA.
3. Project uses the YOLO model implemented with Darknet for efficient object detection.

1. Flask is a lightweight WSGI web application framework in Python.
2. Have integrated the YOLO model with a Flask server to create a RESTful API.
3. The Flask server listens for incoming HTTPS requests, processes them, and returns JSON responses.

1. Apache HTTP Server is a widely-used open-source web server software.
2. Have deployed the Flask application behind Apache using mod_wsgi module to serve the API.
3. Apache acts as a gateway, routing incoming requests to the Flask application.

1. Hetzner Cloud is a cloud hosting provider offering scalable virtual private servers (VPS) and cloud infrastructure.
2. The deployment of the Apache HTTP Server along with the Flask application is done on Hetzner Cloud infrastructure for reliable and scalable hosting.

View and run the API on postman:

The app is live at https://dev.aravind.one/