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YOLOV8-FASTAPI-DOCKER

Ready to start your object detection journey with YOLOv8-FastAPI? 🚀

Description

This repository serves as a template for object detection using YOLOv8 and FastAPI. With YOLOv8, you get a popular real-time object detection model and with FastAPI, you get a modern, fast (high-performance) web framework for building APIs. The project also includes Docker, a platform for easily building, shipping, and running distributed applications.

Sample

Here's a sample of what you can expect to see with this project and also check the Results folder :

What's inside:

  • YOLOv8: A popular real-time object detection model
  • FastAPI: A modern, fast (high-performance) web framework for building APIs
  • Docker: A platform for easily building, shipping, and running distributed applications

Getting Started

You have two options to start the application: using Docker or locally on your machine.

Using Docker

Start the application with the following command:

docker build -t container_name .
docker run -p 8000:8000 container_name

Locally

To start the application locally, follow these steps:

  1. Install the required packages:
pip install -r requirements.txt
  1. Start the application:
python startscript.py

Note: You can change the address and port in the file docker-file

Overview of the code

  • main.py - Base FastAPI functions
  • helperfunc.py - YoloV8 functions
  • [TestImages] (Test Images) - For you to test the working