Object_Detection

This script implements real-time object detection using YOLO models and your webcam. It captures video frames, processes them through a trained YOLO model, and displays the detected objects with bounding boxes and confidence scores. The output video is saved in AVI format for later review.

Acknowledgments

This repository is an improvement based on the codebase from Dipankar Medhi

Features

• Real-time Object Detection: Process video frames on-the-fly using YOLO models.
• Customizable Model and Output: Specify your YOLO model file and output video path via command-line arguments.
• User-friendly Interface: Displays detected objects in real-time on the video feed.

Requirements

1. Python 3.x and pip installed
2. An objection detection model like YOLOv10
3. A webcam

Installation

1. Downloaded necessary files and YOLOv10 model in Resources tab
2. Open the terminal wherever you downloaded the scripts and install the required packages using the following command:

pip install -r requirements.txt

Usage

To run the script, use the following command:

python main.py <model_path> --output <output_path>

model_path: Path to your YOLO model file (must end with .pt).

--output: (Optional) Path to save the output video (default is output.avi, must end with .avi).

Example Usage

python main.py yolov10x.pt --output detected_objects.avi

To exit the script, use Ctrl + C in the terminal that runs the script. This will terminate the script gracefully

License

This repository is licensed under the Unlicense, see the LICENSE file for more details