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
51 lines
1.6 KiB
Python
Executable File
51 lines
1.6 KiB
Python
Executable File
# gestures_debug.py
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import cv2
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import numpy as np
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def detect_hand_gesture(frame):
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height, width, _ = frame.shape
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# --- Fallback-ROI: Mitte des Bildes ---
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w, h = 100, 100
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x = width // 2 - w // 2
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y = height // 2 - h // 2
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roi = frame[y:y+h, x:x+w]
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if roi.size == 0:
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print("[warn] ROI leer – kein Bildausschnitt verarbeitet")
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return "none", (x, y, w, h)
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hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
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lower_skin = np.array([0, 20, 70], dtype=np.uint8)
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upper_skin = np.array([20, 255, 255], dtype=np.uint8)
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mask = cv2.inRange(hsv, lower_skin, upper_skin)
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mask = cv2.dilate(mask, np.ones((3, 3), np.uint8), iterations=4)
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mask = cv2.GaussianBlur(mask, (5, 5), 100)
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contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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gesture = "none"
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if contours and len(contours) > 0:
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max_contour = max(contours, key=cv2.contourArea)
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hull = cv2.convexHull(max_contour, returnPoints=False)
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if hull is not None and len(hull) > 3:
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defects = cv2.convexityDefects(max_contour, hull)
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if defects is not None:
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cnt_defects = defects.shape[0]
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if cnt_defects >= 4:
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gesture = "wave"
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elif cnt_defects <= 1:
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gesture = "fist"
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else:
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gesture = "unknown"
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print(f"[debug] Defekte: {len(defects) if defects is not None else 'None'}")
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else:
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print("[debug] Keine Konturen erkannt")
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print(f"[result] Geste erkannt: {gesture}")
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return gesture, (x, y, w, h)
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