main.py

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


wCam, hCam = 640, 480
frameR = 100
smoothening = 7


pTime = 0
plocX, plocY = 0, 0
clocX, clocY = 0, 0

cap = cv2.VideoCapture(0)
cap.set(3, wCam)
cap.set(4, hCam)
detector = htm.handDetector(maxHands=1)
wScr, hScr = autopy.screen.size()

devices = AudioUtilities.GetSpeakers()
interface = devices.Activate(
    IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
volume = cast(interface, POINTER(IAudioEndpointVolume))

volRange = volume.GetVolumeRange()
minVol = volRange[0]
maxVol = volRange[1]
vol = 0
volBar = 400
volPer = 0
area = 0
colorVol = (255, 0, 0)
while True:
    # For Find hand Landmarks
    success, img = cap.read()
    img = detector.findHands(img)
    lmList, bbox = detector.findPosition(img)
    # Get the tip of the index and middle finger
    if len(lmList) != 0:
        x1, y1 = lmList[8][1:]
        x2, y2 = lmList[12][1:]
        # Filter based on size
        area = (bbox[2] - bbox[0]) * (bbox[3] - bbox[1]) // 100
        # print(area)
        if 250 < area < 1000:
            # Find Distance between index and Thumb
            length, img, lineInfo = detector.findDistance(4, 8, img)

            # Convert Volume
            volBar = np.interp(length, [50, 200], [400, 150])
            volPer = np.interp(length, [50, 200], [0, 100])

            # Reduce Resolution to make it smoother
            smoothness = 10
            volPer = smoothness * round(volPer / smoothness)

            # Check fingers up
            fingers = detector.fingersUp()

            # If pinky is down set volume
            if not fingers[4]:
                volume.SetMasterVolumeLevelScalar(volPer / 100, None)
                cv2.circle(img, (lineInfo[4], lineInfo[5]), 15, (0, 255, 0), cv2.FILLED)
                colorVol = (0, 255, 0)
            else:
                colorVol = (255, 0, 0)

    # Checking which fingers are up
    fingers = detector.fingersUp()

    cv2.rectangle(img, (frameR, frameR), (wCam - frameR, hCam - frameR),
                  (255, 0, 255), 2)
    # For Moving the cursor by detecting which finger are up
    if fingers[1] == 1 and fingers[2] == 0:
        # Converting Coordinates
        x3 = np.interp(x1, (frameR, wCam - frameR), (0, wScr))
        y3 = np.interp(y1, (frameR, hCam - frameR), (0, hScr))
        # Smoothen Values
        clocX = plocX + (x3 - plocX) / smoothening
        clocY = plocY + (y3 - plocY) / smoothening

        # Move Mouse by using the coordinate
        autopy.mouse.move(wScr - clocX, clocY)
        cv2.circle(img, (x1, y1), 15, (255, 0, 255), cv2.FILLED)
        plocX, plocY = clocX, clocY

    # For clicking by detecting index finger and middle finger
    if fingers[1] == 1 and fingers[2] == 1:
        # Find distance between index finger and middle finger
        length, img, lineInfo = detector.findDistance(8, 12, img)
        # print(length)
        """
        Mouse will be click if distance between index finger and middle finger less than 40 
        which mean index finger and middle finger need to be close
        """
        if length < 40:
            cv2.circle(img, (lineInfo[4], lineInfo[5]),
                       15, (0, 255, 0), cv2.FILLED)
            autopy.mouse.click()

    # Drawing the things we need like volume
    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_COMPLEX,
                1, (255, 0, 0), 3)
    cVol = int(volume.GetMasterVolumeLevelScalar() * 100)
    cv2.putText(img, f'Vol Set: {int(cVol)}', (400, 50), cv2.FONT_HERSHEY_COMPLEX,
                1, colorVol, 3)

    # To see the Frame Rate
    cTime = time.time()
    fps = 1 / (cTime - pTime)
    pTime = cTime
    cv2.putText(img, str(int(fps)), (20, 50), cv2.FONT_HERSHEY_PLAIN, 3,
                (255, 0, 0), 3)

    # Display or showing the app
    cv2.imshow("Image", img)
    cv2.waitKey(1)