Count-Cups 💧

A cross-platform water intake tracker that uses computer vision to automatically detect and count your drinking gestures. Stay hydrated with intelligent sip detection and comprehensive tracking features.

✨ Features

• 🤖 Automatic Sip Detection: Computer vision-based detection from your webcam
• ✋ Manual Entry: Quick-add sips or cups when automatic detection isn't available
• 📊 Daily Goal Tracking: Set and track daily hydration goals with visual progress
• 📈 Statistics & Analytics: View hydration patterns over time with detailed charts
• ☕ Multiple Cup Profiles: Calibrate different cup sizes and types
• 🌍 Cross-Platform: Works seamlessly on Windows, macOS, and Linux
• 🎨 Modern UI: Clean PyQt6 interface with dark/light themes
• 🔒 Privacy-First: All data stored locally

🚀 Quick Start

# 1) Clone and setup
git clone https://github.com/VoxHash/Count-Cups.git
cd Count-Cups
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# 2) Install dependencies
pip install -r requirements.txt

# 3) Run
python -m app.main

💿 Installation

See docs/installation.md for platform-specific steps and pre-built binaries.

🛠 Usage

Basic usage:

1. Launch Count-Cups and allow camera access
2. Set up your first cup profile in the Calibration screen
3. Configure your daily goal in Settings
4. Start tracking in the Live Camera screen
5. View progress on the Dashboard

Advanced usage: docs/usage.md and docs/cli.md

⚙️ Configuration

Create a .env file in the project root:

DETECTION_ENGINE=heuristics
DEFAULT_THEME=auto
ENABLE_NOTIFICATIONS=true
GOAL_REMINDER_HOUR=20

Full reference: docs/configuration.md

📚 Examples

• Start here: docs/examples/example-01.md
• More examples: docs/examples/

🧩 Architecture

High-level overview: docs/ARCHITECTURE.md

🗺 Roadmap

Planned milestones: ROADMAP.md. For changes, see CHANGELOG.md.

🤝 Contributing

We welcome PRs! Please read CONTRIBUTING.md and follow the PR template.

🔒 Security

Please report vulnerabilities via SECURITY.md.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• OpenCV for computer vision capabilities
• PyQt6 for the modern user interface
• MediaPipe for advanced pose detection (optional)
• SQLite for local data storage
• Nuitka for cross-platform compilation

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Count-Cups - Stay hydrated, stay healthy! 💧

Made with ❤️ by VoxHash