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There is no YOLO or any framework like that. Only pure image processing.\n\n---\n\n## Requirements\n\n- Python 3.x  \n- OpenCV → `opencv-contrib-python`  \n- NumPy  \n\nInstall dependencies:\n\n```bash\npip install -r requirements.txt\n```\n\n---\n\n## Folder Structure\n\n```\nmain.py\nvideo.mp4\ndetections/        # Frames with detections will be saved here\nhazmats/           # Template PNG files (hazmat symbols)\n```\n\n---\n\n## Usage\n\n1. Place PNG templates of the hazmat signs you want to detect inside the `hazmats/` folder.  \n2. Put the video you want to analyse in the project root as `video.mp4`.  \n3. Run the script:\n\n   ```bash\n   python main.py\n   ```\n\n4. When prompted, enter the frame interval (e.g. **20**) or press *Enter* to accept the default (recommended) value.  \n5. Detected objects are shown on‑screen and saved to the `detections/` folder.  \n   Press any key to continue after each displayed detection.  \n   *(If the folder does not exist, nothing is saved.)*\n\n---\n\n## Notes\n\n- A screenshot is taken for every detected object and written to `detections/`.  \n- Red and blue barrels are detected via colour‑based segmentation.  \n- Hazmat symbols are detected using **SIFT** keypoint matching and template matching.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftugcantopaloglu%2Fhazmat-detection-image-processing","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftugcantopaloglu%2Fhazmat-detection-image-processing","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftugcantopaloglu%2Fhazmat-detection-image-processing/lists"}