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gesture_input_osc.py

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+import cv2
+import mediapipe as mp
+import json, time, math, numpy as np
+from pythonosc import udp_client
+
+# Verbindung zum Spiel herstellen
+client = udp_client.SimpleUDPClient("127.0.0.1", 5005)
+
+# Hilfsfunktion zur Kalibrierung (wie zuvor)
+def map_to_screen(x, y, calib_points, screen_size=(800, 600)):
+    pts_src = np.array(calib_points, dtype=np.float32)
+    pts_dst = np.array([
+        [0, 0],
+        [screen_size[0], 0],
+        [screen_size[0], screen_size[1]],
+        [0, screen_size[1]]
+    ], dtype=np.float32)
+    M = cv2.getPerspectiveTransform(pts_src, pts_dst)
+    p = np.array([[[x, y]]], dtype=np.float32)
+    mapped = cv2.perspectiveTransform(p, M)[0][0]
+    return int(mapped[0]), int(mapped[1])
+
+def run_gesture_input(touch_cam_index=0, gesture_cam_index=1, screen_size=(800, 600)):
+    mp_hands = mp.solutions.hands
+    mp_draw = mp.solutions.drawing_utils
+    hands_touch = mp_hands.Hands(max_num_hands=1, min_detection_confidence=0.6)
+    hands_gesture = mp_hands.Hands(max_num_hands=2, min_detection_confidence=0.6)
+
+    # Kalibrierung laden
+    try:
+        calib_points = json.load(open("calibration.json"))
+        print("📄 Kalibrierung geladen:", calib_points)
+    except:
+        print("⚠️  Keine calibration.json – zuerst calibrate_touch.py ausführen!")
+        return
+
+    cam_touch = cv2.VideoCapture(touch_cam_index)
+    cam_gesture = cv2.VideoCapture(gesture_cam_index)
+    prev_clap_time = 0
+    clap_cooldown = 1.5
+
+    while True:
+        ok1, frame_touch = cam_touch.read()
+        ok2, frame_gest = cam_gesture.read()
+        if not ok1 or not ok2:
+            print("⚠️ Kamera nicht verfügbar"); break
+
+        frame_touch = cv2.flip(frame_touch, 1)
+        frame_gest = cv2.flip(frame_gest, 1)
+
+        # --- Touch-Erkennung ---
+        rgb_t = cv2.cvtColor(frame_touch, cv2.COLOR_BGR2RGB)
+        res_t = hands_touch.process(rgb_t)
+        h, w, _ = frame_touch.shape
+        if res_t.multi_hand_landmarks:
+            lm = res_t.multi_hand_landmarks[0]
+            mp_draw.draw_landmarks(frame_touch, lm, mp_hands.HAND_CONNECTIONS)
+            fx = int(lm.landmark[8].x * w)
+            fy = int(lm.landmark[8].y * h)
+            sx, sy = map_to_screen(fx, fy, calib_points, screen_size)
+            if lm.landmark[8].y > 0.8:
+                client.send_message("/touch", [sx, sy])
+                cv2.putText(frame_touch, f"Touch ({sx},{sy})", (40, 60),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2)
+
+        # --- Clap-Erkennung ---
+        rgb_g = cv2.cvtColor(frame_gest, cv2.COLOR_BGR2RGB)
+        res_g = hands_gesture.process(rgb_g)
+        gh, gw, _ = frame_gest.shape
+        if res_g.multi_hand_landmarks and len(res_g.multi_hand_landmarks) == 2:
+            h1, h2 = res_g.multi_hand_landmarks
+            x1 = np.mean([p.x for p in h1.landmark]) * gw
+            y1 = np.mean([p.y for p in h1.landmark]) * gh
+            x2 = np.mean([p.x for p in h2.landmark]) * gw
+            y2 = np.mean([p.y for p in h2.landmark]) * gh
+            dist = math.hypot(x2 - x1, y2 - y1)
+            if dist < 100 and (time.time() - prev_clap_time) > clap_cooldown:
+                client.send_message("/clap", 1)
+                prev_clap_time = time.time()
+                cv2.putText(frame_gest, "👏", (int(gw / 2) - 20, 80),
+                            cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 255, 255), 3)
+
+        cv2.imshow("Touch-Cam", frame_touch)
+        cv2.imshow("Gesture-Cam", frame_gest)
+        if cv2.waitKey(5) & 0xFF == 27:
+            break
+
+    cam_touch.release()
+    cam_gesture.release()
+    cv2.destroyAllWindows()
+
+if __name__ == "__main__":
+    run_gesture_input()