TresPassGuard is a real-time security system designed for retail environments, particularly gold stores. It uses advanced object detection, line-crossing detection, and alert mechanisms to notify store owners of unauthorized movements. TresPassGuard supports multiple RTSP cameras for comprehensive surveillance.
- Object Detection: Utilizes YOLOv8 for accurate person detection.
- Line-Crossing Detection: Detects when a person crosses a predefined boundary using Shapely for intersection detection.
- Real-Time Alerts: Triggers an alarm to alert the shop owner of a potential trespasser.
- Visualization: Uses OpenCV to display detected objects and crossing events on the camera feed.
- YOLOv8: For object detection.
- Shapely: For geometric operations to detect line crossings.
- Supervision: To manage and process detection events.
- OpenCV: For image processing and visualization.
- ultralytics
- opencv-python==4.10.0.82
- supervision==0.3.0
- shapely==2.0.1
- chardet
- pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
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Clone the repository:
git clone https://github.com/deepaks11/TresPass_StoreGuard cd TresPass_StoreGuard -
Set Up Conda Environment conda create --name (env name) python=3.10 conda activate intent-identification
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Install Dependencies pip install -r requirements.txt
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Run the Project python rtsp_stream.py
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Configure the detection zone: Edit the script to set up the boundary line coordinates according to your store layout.
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Run the script:
python rtsp_stream.py
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The system will start detecting people and trigger an alert if someone crosses the predefined line.
Here's an example of how the system detects and alerts on trespassing:
Deepak.s
We welcome contributions to enhance TresPassGuard. If you have any ideas or improvements, please open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for more details.
- Thanks to the developers of YOLOv8, Shapely, Supervision, and OpenCV for their excellent tools.