OpenCV Image Detection

Small demo showing template-matching face detection with three confidence thresholds (low / mid / high) applied to a crowd image.

Prerequisites

• Python 3.8+ installed
• Git (optional)

Quick setup (recommended)

1. In a terminal run the project setup script to create a .venv, install dependencies, and register a Jupyter kernel:

./setup_venv.sh

2. Open the notebook image-detection.ipynb and select the kernel named "Python (image-detection-venv)".

3. Run the cells (or Run All) to generate output_low.png, output_mid.png, output_high.png in the out folder.

Files

• image-detection.ipynb — main notebook demo.
• setup_venv.sh — creates .venv, installs requirements.txt, registers an ipykernel.
• requirements.txt — minimal Python dependencies.
• VENV.md — short instructions for the virtual environment.

Notes

• Place the template images (e.g. person_1.png, person_2.png) and the haystack image (crowd.png) in the project root before running the notebook.
• If images fail to load the notebook will raise FileNotFoundError with the missing filename.

Enjoy — let me know if you want automated downloading of example images.