HandTrackingModule.py

import cv2
import mediapipe as mp
import time
import os
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'


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 findHands(self, img, draw=True):
 imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
 self.results = self.hands.process(imgRGB)
 # print(results.multi_hand_landmarks)
 if self.results.multi_hand_landmarks:
 for handLms in self.results.multi_hand_landmarks:
 if draw:
 self.mpDraw.draw_landmarks(img, handLms,
 self.mpHands.HAND_CONNECTIONS)
 return img

 def findPosition(self, img, handNo=0, draw=True):
 lmList = []
 if self.results.multi_hand_landmarks:
 myHand = self.results.multi_hand_landmarks[handNo]
 for id, lm in enumerate(myHand.landmark):
 # print(id, lm)
 h, w, c = img.shape
 cx, cy = int(lm.x * w), int(lm.y * h)
 # print(id, cx, cy)
 lmList.append([id, cx, cy])
 if draw:
 cv2.circle(img, (cx, cy), 15, (255, 0, 255), cv2.FILLED)
 return lmList


def main():
 pTime = 0
 cTime = 0
 cap = cv2.VideoCapture("D:/Codes/ComputerVision/Poses/muslimface.mp4")
 detector = handDetector()
 while True:
 success, img = cap.read()
 img = detector.findHands(img)
 lmList = detector.findPosition(img)
 if len(lmList) != 0:
 print(lmList[4])
 cTime = time.time()
 fps = 1 / (cTime - pTime)
 pTime = cTime
 cv2.putText(img, str(int(fps)), (10, 70), cv2.FONT_HERSHEY_PLAIN, 3,
 (255, 0, 255), 3)
 cv2.imshow("Image", img)
 cv2.waitKey(1)


if __name__ == "__main__":
 main()