Loading repository data…
Loading repository data…
kmvishn / repository
A compact real-time weapon detection system using Python and YOLOv8. It detects weapons from live streams, triggers customizable alerts, and offers a desktop GUI and Django interface. Powered by a pretrained YOLOv8 model with support for retraining and data collection, its modular design separates the detection server, GUI, and training logic.
A transparent discovery signal based on current public GitHub metadata.
This score does not audit code, security, maintainers, documentation quality, or suitability. Verify the repository and its current documentation before adoption.
This project aims to detect weapons in real-time through cameras and notify authorities instantly. It's a mini project demonstrating the use of deep learning for security purposes.
alarm.mp3) can be customized.Clone the Repository
git clone https://github.com/jztchl/realtime-weapon-detection.git
cd realtime-weapon-detection
Install Dependencies Ensure you have Python installed. Then, install the required Python packages:
pip install -r needs.txt
Download YOLOv8 Model
The project uses a pre-trained YOLOv8 model (yolov8m.pt) for detection.
Running the GUI Application
python guiapp.py
Running the Web Server
Navigate to the weapon_detection_server directory and start the server:
cd weapon_detection_server
python manage.py runserver
Training the Model To train the model on a new dataset, use:
python train.py
Testing the Model To test the model, run:
python test.py
Downloading Images To download images for training or testing, use:
python download_images.py
Contributions are welcome! Please create an issue or submit a pull request for any improvements.
This project is licensed under the MIT License.