AI-Volume-Gesture-Control

just by using Hand Gesture we can alter the volume. using python and opencv amd the handtracking module. This repository contains my VolumeHandControl.py Code my modules for hand tracking

Volume Control by Hand Gestures

  import cv2
  import time
  import numpy as np
  import HandTrackingModule as htm
  import math
  from ctypes import cast, POINTER
  from comtypes import CLSCTX_ALL
  from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume

  #####################################
  wCam, hCam = 640, 480
  #####################################
  cap = cv2.VideoCapture(0)
  cap.set(3, wCam)
  cap.set(4, hCam)
  pTime = 0
  volPer = 0
  detector = htm.handDetector(detectionCon=0.8)

  devices = AudioUtilities.GetSpeakers()
  interface = devices.Activate(
      IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
  volume = cast(interface, POINTER(IAudioEndpointVolume))
  # volume.GetMute()
  # volume.GetMasterVolumeLevel()
  volRange = volume.GetVolumeRange()

  minVol = volRange[0]
  maxVol = volRange[1]
  vol = 0
  volBar = 400
  while True:
      success, img = cap.read()
      img = detector.findHands(img)
      lmList = detector.findPostion(img, draw=False)
      if len(lmList) != 0:
          # print(lmList[4], lmList[8])
          x1, y1 = lmList[4][1], lmList[4][2]
          x2, y2 = lmList[8][1], lmList[8][2]
          cx, cy = (x1 + x2) // 2, (y1 + y2) // 2

          cv2.circle(img, (x1, y1), 5, (255, 0, 0), cv2.FILLED)
          cv2.circle(img, (x2, y2), 5, (255, 0, 0), cv2.FILLED)
          cv2.line(img, (x1, y1), (x2, y2), (255, 0, 0), 2)
          cv2.circle(img, (cx, cy), 5, (255, 0, 0), cv2.FILLED)

          length = math.hypot(x2 - x1, y2 - y1)
          # print(length)
          # hand range min(Track points) 50 - max(track points) 350
          # Volume Range  -74  - 0
          vol = np.interp(length, [50, 220], [minVol, maxVol])
          volBar = np.interp(length, [50, 220], [400, 150])
          volPer = np.interp(length, [50, 220], [0, 100])
          print(int(length), vol)
          volume.SetMasterVolumeLevel(vol, None)

          if length < 50:
              cv2.circle(img, (cx, cy), 10, (0, 255, 255), cv2.FILLED)

      cv2.rectangle(img, (50, 150), (85, 400), (255, 0, 0), 3)
      cv2.rectangle(img, (50, int(volBar)), (85, 400), (255, 0, 0), cv2.FILLED)
      cv2.putText(img, f'{int(volPer)}%', (40, 450), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 2)

      cTime = time.time()
      fps = 1 / (cTime - pTime)
      pTime = cTime
      cv2.putText(img, f'FPS: {int(fps)}', (40, 70), cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 0), 2)

      cv2.imshow("img", img)
      cv2.waitKey(1)

HandTracking Module (to track movement of hands)

import mediapipe as mp
import time

cap = cv2.VideoCapture(0)
mpHands = mp.solutions.hands
hands = mpHands.Hands()
mpDraw = mp.solutions.drawing_utils

pTime = 0
cTime = 0
while True:
    success, img = cap.read()
    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    results = hands.process(imgRGB)
    # print(results.multi_hand_landmarks)

    if results.multi_hand_landmarks:
       for handLms in results.multi_hand_landmarks:
           for id,lm in enumerate(handLms.landmark):
                # print(id,lm)
                h, w, c = img.shape
                cx,cy = int(lm.x*w), int(lm.y*h)
                print(id, cx , cy)
                if id == 0:
                    cv2.circle(img, (cx,cy), 20, (255,0,255), cv2.FILLED)
           mpDraw.draw_landmarks(img, handLms, mpHands.HAND_CONNECTIONS)


    cTime = time.time()
    fps = 1/(cTime-pTime)
    pTime = cTime
    cv2.putText(img, str(int(fps)),(10,70), cv2.FONT_HERSHEY_PLAIN,3,(255,0,0),2)
    cv2.imshow("image", img)
    cv2.waitKey(1)

MY Hand Tracking Module which can be used for any project related to gestures

  import cv2
  import mediapipe as mp
  import time

  class handDetector():
      def __init__(self,mode=False, maxHands = 2, detectionCon=0.5, trackCon=0.5 ):
         self.mode = mode
         self.maxHands = maxHands
         self.detectionCon = detectionCon
         self.trackCon = trackCon

         self.mpHands = mp.solutions.hands
         self.hands = self.mpHands.Hands(self.mode,self.maxHands,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 findPostion(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), 5, (255, 0, 255), cv2.FILLED)

          return lmList


  def main():
      pTime = 0
      cTime = 0
      cap = cv2.VideoCapture(0)
      detector = handDetector()
      while True:
          success, img = cap.read()
          img = detector.findHands(img)
          lmList = detector.findPostion(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, 0), 2)
          cv2.imshow("image", img)
          cv2.waitKey(1)


  if __name__ == "__main__":
      main()