pyw-motion 🏃

Motion detection e tracking utilities per il pythonWoods ecosystem.
(algoritmi real-time, OpenCV integration, type-safe APIs).

Installation (nothing to use yet)

pip install pyw-motion

Usage

from pyw.motion import MotionDetector, OpticalFlow
detector = MotionDetector()
frames = detector.detect_motion(video_source)

Questo installerà automaticamente:

• pyw-core (namespace comune)
• opencv-python (computer vision base)
• numpy (array processing)

Extras per algoritmi avanzati:

pip install pyw-motion[advanced]  # + scikit-image, scipy
pip install pyw-motion[gpu]       # + OpenCV GPU acceleration
pip install pyw-motion[full]      # tutto incluso

Philosophy

• Real-time ready – algoritmi ottimizzati per streaming video.
• Multiple backends – OpenCV, scikit-image, custom implementations.
• Type-safe APIs – Pydantic models per bounding boxes, tracks.
• Lightweight core – dipendenze pesanti come extras opzionali.

Roadmap

• 🎯 Motion detection: Background subtraction, frame differencing
• 📹 Object tracking: Kalman filter, particle filter, deep SORT
• 🌊 Optical flow: Lucas-Kanade, Farneback, deep learning methods
• 📊 Analytics: Trajectory analysis, heat maps, statistics
• ⚡ Performance: GPU acceleration, multi-threading, async processing

Contributing

1. Fork il repo: pyw-motion.
2. Crea virtual-env via Poetry: poetry install && poetry shell.
3. Lancia linter e mypy: ruff check . && mypy.
4. Apri la PR: CI esegue lint, type-check, build.

Felice tracking nella foresta di pythonWoods! 🌲🏃

Links utili

Documentazione dev (work-in-progress) → https://pythonwoods.dev/docs/pyw-motion/latest/

Issue tracker → https://github.com/pythonWoods/pyw-motion/issues

Changelog → https://github.com/pythonWoods/pyw-motion/releases

© pythonWoods — MIT License