# gestures_debug.py
import cv2
import numpy as np

def detect_hand_gesture(frame):
    height, width, _ = frame.shape

    # --- Fallback-ROI: Mitte des Bildes ---
    w, h = 100, 100
    x = width // 2 - w // 2
    y = height // 2 - h // 2
    roi = frame[y:y+h, x:x+w]

    if roi.size == 0:
        print("[warn] ROI leer – kein Bildausschnitt verarbeitet")
        return "none", (x, y, w, h)

    hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)

    lower_skin = np.array([0, 20, 70], dtype=np.uint8)
    upper_skin = np.array([20, 255, 255], dtype=np.uint8)

    mask = cv2.inRange(hsv, lower_skin, upper_skin)
    mask = cv2.dilate(mask, np.ones((3, 3), np.uint8), iterations=4)
    mask = cv2.GaussianBlur(mask, (5, 5), 100)

    contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    gesture = "none"

    if contours and len(contours) > 0:
        max_contour = max(contours, key=cv2.contourArea)
        hull = cv2.convexHull(max_contour, returnPoints=False)
        if hull is not None and len(hull) > 3:
            defects = cv2.convexityDefects(max_contour, hull)
            if defects is not None:
                cnt_defects = defects.shape[0]
                if cnt_defects >= 4:
                    gesture = "wave"
                elif cnt_defects <= 1:
                    gesture = "fist"
                else:
                    gesture = "unknown"
        print(f"[debug] Defekte: {len(defects) if defects is not None else 'None'}")
    else:
        print("[debug] Keine Konturen erkannt")

    print(f"[result] Geste erkannt: {gesture}")
    return gesture, (x, y, w, h)