https://github.com/alihassanml/object-detection-yolov8-supervision
This project demonstrates object detection using the YOLOv8 model with video annotation, utilizing supervision for tracking and labeling, and opencv for video processing.
https://github.com/alihassanml/object-detection-yolov8-supervision
computer-vision cvzon machine-learning object-detection opencv-python sort supervision yolov8
Last synced: 8 months ago
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This project demonstrates object detection using the YOLOv8 model with video annotation, utilizing supervision for tracking and labeling, and opencv for video processing.
- Host: GitHub
- URL: https://github.com/alihassanml/object-detection-yolov8-supervision
- Owner: alihassanml
- License: mit
- Created: 2024-09-18T08:10:02.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-18T09:06:58.000Z (about 1 year ago)
- Last Synced: 2025-01-01T15:11:45.883Z (9 months ago)
- Topics: computer-vision, cvzon, machine-learning, object-detection, opencv-python, sort, supervision, yolov8
- Language: Jupyter Notebook
- Homepage:
- Size: 26.7 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Object Detection with YOLOv8 and Supervision
This project demonstrates object detection using the YOLOv8 model with video annotation, utilizing `supervision` for tracking and labeling, and `opencv` for video processing.
## Installation
1. Clone the repository:
```bash
git clone https://github.com/alihassanml/Object-Detection-Yolov8-Supervision.git
cd Object-Detection-Yolov8-Supervision
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
Ensure you have `opencv-python`, `supervision`, and `ultralytics` installed.
## Usage
1. Place your input video in the root directory of the project (e.g., `Shopping.mp4`).
2. Run the object detection script:
```bash
python detect.py
```
3. The annotated video will be saved as `Annotated_Shopping.mp4`.
## Description
- **Object Detection**: YOLOv8 is used to detect objects in a video.
- **Tracking**: `ByteTrack` is used for tracking objects across frames.
- **Annotation**: Bounding ellipses and labels are drawn for detected objects.
- **Output**: Annotated video is saved to a file.