HandDetector.py

import cv2
import math
import mediapipe as mp

class HandDetector():
    def __init__(self, mode=False, maxHands=2, modelComplexity=1, detectionCon=0.5, trackCon=0.5):
        self.mode = mode
        self.maxHands = maxHands
        self.modelComplex = modelComplexity
        self.detectionCon = detectionCon
        self.trackCon = trackCon

        self.mpHands = mp.solutions.hands
        self.hands = self.mpHands.Hands(self.mode, self.maxHands, self.modelComplex, self.detectionCon, self.trackCon)
        self.mpDraw = mp.solutions.drawing_utils

    def process_hands(self, img, draw=True):
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        self.results = self.hands.process(imgRGB)

        if self.results.multi_hand_landmarks:
            for landmark in self.results.multi_hand_landmarks:
                if draw:
                    self.mpDraw.draw_landmarks(img, landmark, self.mpHands.HAND_CONNECTIONS)

        return img

    def get_positions(self, img, hand_number=0, draw=True):
        landmark_list = []
        if self.results.multi_hand_landmarks:
            myHand = self.results.multi_hand_landmarks[hand_number]

            for id, lm in enumerate(myHand.landmark):
                h, w, c = img.shape
                cx, cy = int(lm.x * w), int(lm.y * h)

                landmark_list.append([id, cx, cy])
                if draw:
                    cv2.circle(img, (cx, cy), 5, (255, 0, 255), cv2.FILLED)

        return landmark_list


    def is_click(self, hand_landmarks):
        thumb_tip = hand_landmarks[4]
        index_tip = hand_landmarks[8]
        middle_tip = hand_landmarks[12]
        ring_tip = hand_landmarks[16]
        little_tip = hand_landmarks[20]

        distance_thumb_index = math.sqrt((thumb_tip[1] - index_tip[1])**2 + (thumb_tip[2] - index_tip[2])**2)

        distances = [
            math.sqrt((index_tip[1] - middle_tip[1])**2 + (index_tip[2] - middle_tip[2])**2),
            math.sqrt((index_tip[1] - ring_tip[1])**2 + (index_tip[2] - ring_tip[2])**2),
            math.sqrt((index_tip[1] - little_tip[1])**2 + (index_tip[2] - little_tip[2])**2)
        ]

        if distance_thumb_index < 30 and all(distance > 50 for distance in distances):
            return True
        else:
            return False