Hazardous‑Material Sign & Barrel Detection in a Robotic Environment

This project uses OpenCV with the SIFT algorithm to detect hazardous‑material symbols (hazmat signs) and coloured barrels (red / blue) in a video file. There is no YOLO or any framework like that. Only pure image processing.

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Requirements

• Python 3.x
• OpenCV → opencv-contrib-python
• NumPy

Install dependencies:

pip install -r requirements.txt

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Folder Structure

main.py
video.mp4
detections/        # Frames with detections will be saved here
hazmats/           # Template PNG files (hazmat symbols)

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Usage

1. Place PNG templates of the hazmat signs you want to detect inside the hazmats/ folder.

2. Put the video you want to analyse in the project root as video.mp4.

3. Run the script:

   python main.py

4. When prompted, enter the frame interval (e.g. 20) or press Enter to accept the default (recommended) value.

5. Detected objects are shown on‑screen and saved to the detections/ folder.
   Press any key to continue after each displayed detection.
   (If the folder does not exist, nothing is saved.)

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Notes

• A screenshot is taken for every detected object and written to detections/.
• Red and blue barrels are detected via colour‑based segmentation.
• Hazmat symbols are detected using SIFT keypoint matching and template matching.