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https://github.com/mahdi-marjani/object-tracking-entry-exit

This project implements an object counting system using the YOLOv8 object detection model from Ultralytics. The system detects and counts objects of specified classes in a video stream in real-time. It utilizes computer vision techniques to track objects as they move across a predefined line or region of interest.
https://github.com/mahdi-marjani/object-tracking-entry-exit

ai bot computer-vision image-processing object-detection object-tracking opencv video-processing yolo yolov8

Last synced: 23 days ago
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This project implements an object counting system using the YOLOv8 object detection model from Ultralytics. The system detects and counts objects of specified classes in a video stream in real-time. It utilizes computer vision techniques to track objects as they move across a predefined line or region of interest.

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README

        

# object-tracking-entry-exit

https://github.com/mahdi-marjani/object-tracking-entry-exit/assets/129745867/156d90f7-ad6d-43cd-9e51-b117767f43c0

This project implements an object counting system using the YOLOv8 object detection model from Ultralytics. The system detects and counts objects of specified classes in a video stream in real-time. It utilizes computer vision techniques to track objects as they move across a predefined line or region of interest.

## Usage

1. Clone the repository:
```bash
git clone https://github.com/mahdi-marjani/object-tracking-entry-exit.git
```
2. Change directory to the cloned repository:
```bash
cd object-tracking-entry-exit
```
3. Install the required dependencies:
```bash
pip install -r requirements.txt
```
4. Run the scripts:
```bash
python3 main.py
```