thisishamody / yolo_paper_project

Object Detection with YOLO on COCO Dataset

This project demonstrates the use of the YOLO (You Only Look Once) object detection model on the COCO dataset. It processes images from the dataset and provides object detection results. The model used is a YOLOv8 Large model for better accuracy.

Prerequisites

The project requires the following packages:

• cv2
• json
• glob
• pycocotools
• ultralytics YOLO

Installation

To run the project, follow these steps:

1. Clone the repository:

   git clone https://github.com/thisishamody/yolo_paper_project.git
   

2. Install the necessary dependencies:

   pip install opencv-python pycocotools glob2 ultralytics
   

3. Download the model weights and place them in the Yolo-Weights directory. You can download them from here. In this project, we use yolov8l.pt for better accuracy.

Usage

The main.py script runs the object detection process on images located in coco/val2017.

The script evaluates the model's predictions and saves them in a JSON file named predictions.json. It also calculates the mean Average Precision (mAP) for the model's predictions.

To run the script: