import cv2
import mediapipe as mp
import os

mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands

def process_image(image_path):
    """Run hand detection on a static image."""
    image = cv2.imread(image_path)
    if image is None:
        print(f"❌ Could not read image: {image_path}")
        return

    with mp_hands.Hands(static_image_mode=True, max_num_hands=2, min_detection_confidence=0.5) as hands:
        results = hands.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))

        if not results.multi_hand_landmarks:
            print("🙌 No hands detected in image.")
        else:
            for hand_landmarks in results.multi_hand_landmarks:
                mp_drawing.draw_landmarks(
                    image,
                    hand_landmarks,
                    mp_hands.HAND_CONNECTIONS,
                    mp_drawing.DrawingSpec(color=(0, 255, 0), thickness=2, circle_radius=3),
                    mp_drawing.DrawingSpec(color=(255, 255, 255), thickness=2, circle_radius=2)
                )

        cv2.imshow("🤚 Hand Recognition (Image Mode)", image)
        cv2.waitKey(0)
        cv2.destroyAllWindows()

def process_webcam():
    """Run hand detection using webcam if available."""
    cap = cv2.VideoCapture(0)
    if not cap.isOpened():
        print("⚠️ Webcam not detected. Switching to image mode...")
        return False

    with mp_hands.Hands(
        static_image_mode=False,
        max_num_hands=2,
        min_detection_confidence=0.5,
        min_tracking_confidence=0.5
    ) as hands:
        print("🎥 Hand Recognition running. Press ESC to exit.")
        while True:
            ret, frame = cap.read()
            if not ret:
                print("❌ Failed to capture frame.")
                break

            frame = cv2.flip(frame, 1)  # Mirror view
            results = hands.process(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))

            if results.multi_hand_landmarks:
                for hand_landmarks in results.multi_hand_landmarks:
                    mp_drawing.draw_landmarks(
                        frame,
                        hand_landmarks,
                        mp_hands.HAND_CONNECTIONS,
                        mp_drawing.DrawingSpec(color=(0, 255, 0), thickness=2, circle_radius=3),
                        mp_drawing.DrawingSpec(color=(255, 255, 255), thickness=2, circle_radius=2)
                    )

            cv2.imshow("🤚 Hand Recognition (ESC to exit)", frame)
            if cv2.waitKey(5) & 0xFF == 27:  # ESC
                break

    cap.release()
    cv2.destroyAllWindows()
    return True

if __name__ == "__main__":
    print("🚀 Starting MediaPipe Hand Recognition App...")

    if not process_webcam():
        test_image = "hand_test.jpg"
        if not os.path.exists(test_image):
            print(f"⚠️ No '{test_image}' found. Please place a hand image in this folder.")
        else:
            process_image(test_image)