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orig_code.py
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orig_code.py
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import cv2
import mediapipe as mp
import math
from ctypes import cast, POINTER
from comtypes import CLSCTX_ALL
from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume
import numpy as np
devices = AudioUtilities.GetSpeakers()
interface = devices.Activate(
IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
volume = cast(interface, POINTER(IAudioEndpointVolume))
# volume.GetMute() ==> 'true' if comp id muted
# volume.GetVolumeRange() ==> range is (-65.25,0.0,0.03125)
# volume.GetMasterVolumeLevel() ==> gives current value of volume in terms of the above range -65.25 to 0.0
# volume.SetMasterVolumeLevel(-20.0, None) ==> sets to desired volume
mp_drawing = mp.solutions.drawing_utils
#mp_drawing_styles = mp.solutions.drawing_styles
mp_hands = mp.solutions.hands
hands = mp_hands.Hands()
vid = cv2.VideoCapture(0) # opens camera
with mp_hands.Hands(
model_complexity=0,
min_detection_confidence=0.5,
min_tracking_confidence=0.5) as hands:
while vid.isOpened():
success, img = vid.read() #to keep refreshing the image captured by camera
if not success:
print("Ignoring empty camera frame.")
continue
imgRGB= cv2.cvtColor(img, cv2.COLOR_BGR2RGB) #cv2 uses BGR but mediapipe uses RGB, so we have to convert
results = hands.process(imgRGB)
#print(results.multi_hand_landmarks) = 'None' when no hand on the screen. Else gives the coordinates of the hand.
if results.multi_hand_landmarks: # if hand is found
for hand_no in results.multi_hand_landmarks: # iterate over all hands found in frame
mp_drawing.draw_landmarks(img, hand_no, mp_hands.HAND_CONNECTIONS)
lmkList = [] #list of landmarks
for id, lm in enumerate(hand_no.landmark):
#print(id, lm) # prints coord of each of the 21 landmarks on the hand
h,w,c= img.shape # height,width,channel of image
px,py = int(lm.x*w) , int(lm.y*h) # converting coord to pixels
#print(id,px,py)
lmkList.append([id,px,py])
#print(lmkList)
if lmkList: # obtaining x and y coordinates of landmark 4 and 8
x1,y1= lmkList[4][1], lmkList[4][2] # thumb
x2,y2= lmkList[8][1], lmkList[8][2] # index finger
cv2.circle(img, (x1,y1), 10, (0,255,0),2) # image, center coord, radius, color(BGR), thickness
cv2.circle(img, (x2,y2), 10, (0,255,0),2)
cv2.line(img, (x1,y1), (x2,y2), (255,0,0),2) # a blue line btw them
length = math.hypot(x2-x1,y2-y1)
#print(length)
vol_range = volume.GetVolumeRange() #returns tuple
min_vol = vol_range[0] # doing this because we don't want to hardcode it
max_vol= vol_range[1]
# converting length to a value in volume range
vol = np.interp(length, [0,300],[min_vol,max_vol]) # interpolation- length, range of length, range to be converted to.
volume_bar = np.interp(length, [0,300], [400,150] ) #interpolation to coord of rectangle
volume_percentage= np.interp(length, [0,300], [0,100])
volume.SetMasterVolumeLevel(vol, None)
# displaying volume bar and volume percentage
cv2.rectangle(img, (50,150), (85,400), (0,255,0), 2)
cv2.rectangle(img, (50,int(volume_bar)), (85,400), (0,255,0), cv2.FILLED)
cv2.putText(img, str(int(volume_percentage)), (40,450), cv2.FONT_HERSHEY_PLAIN, 3, (0,255,255), 3)
cv2.imshow("Image", img) # show video
k = cv2.waitKey(1) # delay of 1ms to be able to actually see the video
if k==27: # ASCII value for ESC key. Press ESC key to exit program.
break
vid.release() # releasing memory occupied