🖼️ GoCV Face Detection

A lightweight Go application using GoCV and Haar Cascade for real-time webcam-based face detection. Features a live preview with a heads-up display (HUD) showing FPS and hotkeys, plus eye validation to reduce false positives.

Features

• Real-time Preview: Webcam feed with HUD showing FPS and hotkeys.
• Face Detection: Haar Cascade with eye validation for accuracy.
• Hotkeys:
  • ESC: Exit the application.
  • S: Save a snapshot.
  • F: Flip (mirror) the feed.
  • G: Toggle grayscale mode.
  • E: Apply Canny edge detection.
  • N: Revert to normal mode.

Prerequisites

• OS: macOS (tested on Apple Silicon)
• Go: ≥ 1.21
• OpenCV: 4.x (via Homebrew)
• Tools: pkg-config

Installation

1. Install Dependencies

brew update
brew install opencv pkg-config

2. Configure Environment

Add OpenCV to PKG_CONFIG_PATH:

echo 'export PKG_CONFIG_PATH="$(brew --prefix opencv)/lib/pkgconfig:$PKG_CONFIG_PATH"' >> ~/.zshrc
source ~/.zshrc

Verify OpenCV installation:

pkg-config --modversion opencv4

3. Set Up Project

git clone <repository-url>
cd <repository-directory>
go mod tidy

Usage

Run the application:

go run .

Hotkeys

• ESC: Quit
• S: Save snapshot
• F: Flip feed
• G: Grayscale
• E: Canny edges
• N: Normal mode

Contributing

1. Fork the repository.
2. Create a branch (git checkout -b feature/your-feature).
3. Commit changes (git commit -m 'Add feature').
4. Push to the branch (git push origin feature/your-feature).
5. Open a pull request.

Ensure code follows the project’s style and includes tests.

License

MIT License

Acknowledgments

• GoCV
• OpenCV
• Haar Cascade classifiers