3ee5214405
"Vorhersagen heißt verstehen - Die Natur durch Code begreifen" **Eine neue Computer Vision Mission!** Inspired by: "Eine Mond Maschine die mir zeigt wann ich regenbogen zählen kann?" 💚 **Was die Mond Maschine kann:** - 🌙 Mond-Phasen tracken & berechnen - 🌦️ Wetter-Daten analysieren (APIs) - 📸 Computer Vision: Regenbogen detektieren (OpenCV) - 🔮 Vorhersage-Algorithmus (ML Light) - 🌈 Mondregenbogen! (Lunar Rainbow bei Vollmond) **8 Phasen:** 1. Vision - Maya-Eule über Vorhersage vs Beobachtung 2. Das Dreieck - Daten-Struktur, Flow & Balance 3. Hardware - Kamera-Setup (Webcam/RasPi Cam) 4. Computer Vision - OpenCV & HSV-Farbraum 5. Daten-Integration - Wetter-API & Mond-Berechnung 6. Vorhersage-Algorithmus - Feature Engineering & Scoring 7. Visualisierung - ASCII Mond-Phasen & Dashboard 8. Mondregenbogen - Die magische Legende **Alle 13 Waldwächter:** - 🔺 Dreieck: DumboSQL, FunkFox, Taichi Taube - 🔧 Hardware: CapaciTobi, Schnecki, Schraubbär - 💻 Code: SnakePy (OpenCV!), PepperPHP, Spider - 🔐 System: CrabbyRust, Vektor - 🎨 Art: ASCII-Monster - 🦉 Wisdom: Maya-Eule **Learning Areas:** - Computer Vision & OpenCV - Image Processing (HSV color space) - Weather API integration - Astronomical calculations (moon phases) - Machine Learning concepts - Prediction algorithms - Data visualization **Hardware:** - Kamera (USB Webcam / Raspberry Pi Camera) - Optional: Wetterfestes Gehäuse für Outdoor - Python + OpenCV + ephem **Next Steps:** pip install opencv-python numpy requests ephem Die dritte Robot-Mission ist bereit! 🌙✨ Von Krümels Vision zur Mond Maschine! 💚 🤖 Generated with Claude Code Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
66 lines
1.6 KiB
JSON
66 lines
1.6 KiB
JSON
{
|
|
"icon": "🌙",
|
|
"title": "Mond Maschine - Rainbow Predictor",
|
|
"description": "Baue eine Maschine die Regenbogen vorhersagt! Mit Mond-Phasen, Wetter-Daten & Computer Vision.",
|
|
"category": "robots",
|
|
"difficulty": "advanced",
|
|
"duration_minutes": 35,
|
|
"requires_ai": true,
|
|
"enabled": true,
|
|
"author": "Crumbforest Team",
|
|
"version": "1.0",
|
|
"crew_involved": [
|
|
"mayaeule",
|
|
"dumbosql",
|
|
"funkfox",
|
|
"taichitaube",
|
|
"tobi",
|
|
"schnecki",
|
|
"schraubaer",
|
|
"snakepy",
|
|
"pepperphp",
|
|
"spider",
|
|
"crabbyrust",
|
|
"vektor",
|
|
"asciimonster"
|
|
],
|
|
"tags": [
|
|
"computer-vision",
|
|
"opencv",
|
|
"weather-api",
|
|
"moon-phases",
|
|
"machine-learning",
|
|
"prediction",
|
|
"camera",
|
|
"image-processing",
|
|
"astronomy"
|
|
],
|
|
"philosophy": "Vorhersagen heißt verstehen - Die Natur durch Code begreifen",
|
|
"learning_objectives": [
|
|
"Computer Vision Grundlagen (OpenCV)",
|
|
"Bildverarbeitung (HSV-Farbraum für Regenbogen)",
|
|
"Wetter-API Integration",
|
|
"Mondphasen-Berechnung",
|
|
"Pattern Recognition & Machine Learning",
|
|
"Zeitreihen-Analyse",
|
|
"Kamera-Setup & Bilderfassung",
|
|
"Vorhersage-Algorithmen",
|
|
"Data Visualization"
|
|
],
|
|
"prerequisites": [
|
|
"Python Grundkenntnisse",
|
|
"Interesse an Computer Vision",
|
|
"Optional: Kamera (Webcam oder Raspi Cam)"
|
|
],
|
|
"hardware_needed": [
|
|
"Kamera (USB Webcam oder Raspberry Pi Camera)",
|
|
"Optional: Wetterfester Gehäuse für Outdoor",
|
|
"Raspberry Pi oder Computer mit Python"
|
|
],
|
|
"references": [
|
|
"OpenCV Documentation",
|
|
"Weather API (OpenWeatherMap, Weatherstack)",
|
|
"Astronomy libraries (ephem, skyfield)"
|
|
]
|
|
}
|