2915828adf
- Interactive mission selector with metadata-driven design - 5 educational missions (basics + advanced) - AI assistant roles (Deepbit, Bugsy, Schnippsi, Tobi) - SnakeCam gesture recognition system - Token tracking utilities - CLAUDE.md documentation - .gitignore for logs and secrets
53 lines
1.4 KiB
Python
Executable File
53 lines
1.4 KiB
Python
Executable File
from flask import Flask, render_template, Response, request, redirect
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import cv2
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import json
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from datetime import datetime
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app = Flask(__name__)
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def gen_frames():
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cam = cv2.VideoCapture(0)
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if not cam.isOpened():
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print("[WARNUNG] Kamera konnte nicht geöffnet werden.")
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return
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try:
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while True:
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success, frame = cam.read()
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if not success:
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break
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ret, buffer = cv2.imencode('.jpg', frame)
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frame = buffer.tobytes()
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yield (b'--frame\r\n'
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b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
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finally:
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cam.release()
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print("[info] Kamera wurde sauber freigegeben.")
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@app.route('/')
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def index():
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return render_template('index.html')
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@app.route('/video_feed')
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def video_feed():
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return Response(gen_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
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@app.route('/log_answer', methods=['POST'])
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def log_answer():
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user_input = request.form.get('antwort', 'nichts gesagt')
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mood = request.form.get('mood', 'unspecified')
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gesture = request.form.get('gesture', 'none')
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timestamp = datetime.now().isoformat()
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log_entry = {
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'timestamp': timestamp,
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'antwort': user_input,
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'mood': mood,
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'gesture': gesture
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}
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with open("snake_log.jsonl", "a") as log_file:
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log_file.write(json.dumps(log_entry) + "\n")
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return redirect("/")
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