handControle.py

import cv2
import mediapipe as mp

class HandGestureDetector:
    def __init__(self, max_num_hands=2, min_detection_confidence=0.5, min_tracking_confidence=0.5):
        self.mp_hands = mp.solutions.hands
        self.hands = self.mp_hands.Hands(static_image_mode=False,
                                         max_num_hands=max_num_hands,
                                         min_detection_confidence=min_detection_confidence,
                                         min_tracking_confidence=min_tracking_confidence)
        self.mp_drawing = mp.solutions.drawing_utils

    def is_finger_open(self, landmark_list, finger_tip_idx, finger_bottom_idx):
        if finger_tip_idx == 4:
            return self.is_thumb_open(landmark_list, finger_tip_idx, finger_bottom_idx)
        return landmark_list[finger_tip_idx].y < landmark_list[finger_bottom_idx].y

    def is_thumb_open(self, landmark_list, thumb_tip_idx=4, thumb_mcp_idx=2, reference_idx=0):
        # Thumb tip and MCP joint
        thumb_tip = landmark_list[thumb_tip_idx]
        thumb_mcp = landmark_list[thumb_mcp_idx]

        # Reference point (wrist or index finger MCP)
        reference_point = landmark_list[reference_idx]

        # For right hand, check if thumb tip is to the right of the MCP joint when viewed from the wrist/index MCP
        # For left hand, the condition would be inverted
        if reference_point.x < thumb_mcp.x:  # Assuming right hand
            return thumb_tip.x > thumb_mcp.x
        else:  # Assuming left hand
            return thumb_tip.x < thumb_mcp.x

    def count_open_fingers(self, landmarks):
        # Make it so that this function considers that thumbs are still higher than the knuckles even when closed

        thumb_tip_idx, index_tip_idx, middle_tip_idx, ring_tip_idx, pinky_tip_idx = 4, 8, 12, 16, 20
        thumb_base_idx, index_bottom_idx, middle_bottom_idx, ring_bottom_idx, pinky_bottom_idx = 1, 5, 9, 13, 17

        landmark_list = landmarks.landmark
        fingers_open = [
            self.is_finger_open(landmark_list, thumb_tip_idx, thumb_tip_idx - 2),
            self.is_finger_open(landmark_list, index_tip_idx, index_bottom_idx),
            self.is_finger_open(landmark_list, middle_tip_idx, middle_bottom_idx),
            self.is_finger_open(landmark_list, ring_tip_idx, ring_bottom_idx),
            self.is_finger_open(landmark_list, pinky_tip_idx, pinky_bottom_idx)
        ]

        return fingers_open.count(True)

    def run(self, image):
        image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
        image.flags.writeable = False
        results = self.hands.process(image)

        image.flags.writeable = True
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)

        if results.multi_hand_landmarks:
            for hand_idx, hand_landmarks in enumerate(results.multi_hand_landmarks):
                self.mp_drawing.draw_landmarks(image, hand_landmarks, self.mp_hands.HAND_CONNECTIONS)
                open_fingers = self.count_open_fingers(hand_landmarks)

                if open_fingers == 5:
                    gesture = 5
                    print("gesture hand signeled = " + gesture)
                elif open_fingers == 0:
                    gesture = 0
                    print("gesture hand signeled = " + gesture)
                else:
                    gesture = open_fingers
                    print("gesture hand signeled = " + gesture)
                    return gesture

        else: # No hands detected
            cv2.putText(image, "No hands detected", (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2,
                        cv2.LINE_AA)


# Example of usage
if __name__ == "__main__":
    detector = HandGestureDetector()
    detector.run()