python control volume

Volume control based on opencv and mediapipe

First, use mediapipe to detect the hand and obtain the corresponding coordinates. Then take out the coordinate values ​​​​of the corresponding points for drawing and distance measurement based on opencv. Finally, the coordinate values ​​​​of the finger key points are mapped with the volume of the computer to control the computer. Computer volume.

import cv2
import mediapipe as mp
import numpy as np
import math
# 导入电脑音量控制模块
from ctypes import cast, POINTER
from comtypes import CLSCTX_ALL
from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume

class lis():
    def __init__(self,min_detection_confidence=0.7):
        self.mpmode = mp.solutions.hands
        self.mphand = self.mpmode.Hands()   #调用mediapipe

        self.min_det_con = min_detection_confidence

        self.draw = mp.solutions.drawing_utils

        # 获取电脑音量范围
        devices = AudioUtilities.GetSpeakers()
        interface = devices.Activate(
            IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
        self.volume = cast(interface, POINTER(IAudioEndpointVolume))
        self.volume_range = self.volume.GetVolumeRange()

    #手指识别
    def findhand(self,img):
        RGB_img = cv2.cvtColor(img,(cv2.COLOR_BGR2RGB))
        results = self.mphand.process(RGB_img)

        x_list = []
        y_list = []
        self.find_list = []
        #！！！！！！！
        if (results.multi_hand_landmarks):######需要判断是否存在返回的值，不然会报错
            for hand_landmarks in results.multi_hand_landmarks:
                self.draw.draw_landmarks(img,hand_landmarks,mp.solutions.hands.HAND_CONNECTIONS,
                                         mp.solutions.drawing_styles.get_default_pose_landmarks_style ( )
                                         )

                for id,landmark in enumerate(hand_landmarks.landmark):  #获取id以及手指信息

                    H,W,_ = img.shape  #需要获取图片宽度进行比例变换
                    x = int(landmark.x *W)
                    y = int(landmark.y *H)
                    x_list.append(x)
                    y_list.append(y)
                    self.find_list.append([id,x,y])

                x_min , y_min = min(x_list),min(y_list)
                x_max, y_max = max(x_list), max(y_list)
                cv2.rectangle(img,(x_min-10,y_min-10),(x_max+10,y_max+10),(255,0,255),2)

        return img,self.find_list
    #手指画点
    def finger_draw(self,img,id):
        x,y = self.find_list[id][1:]
        cv2.circle(img,(x,y),2,(0,255,0),10)
        return img

    #手指画线
    def finger_line(self,img,p1,p2,):
        x ,y = self.find_list[p1][1:]
        x1, y1 = self.find_list[p2][1:]
        cv2.line(img,(x,y),(x1,y1),(202,162,201),3)
        self.distance = math.hypot(x1-x,y1-y)
        if self.distance<100:
            x3= int((x1+x)/2)
            y3= int((y1+y)/2)
            cv2.circle(img, (x3, y3), 2, (151, 118, 52), 10)
        return img,self.distance

    def vio(self,img):
        distance = self.distance
        # 获取电脑最大最小音量
        min_volume = self.volume_range[0]
        max_volume = self.volume_range[1]
        # 将指尖长度映射到音量上
        vol = np.interp(distance, [10, 150], [min_volume, max_volume])
        # 将指尖长度映射到矩形显示上
        rect_height = np.interp(distance, [10, 150], [0, 200])
        rect_percent_text = np.interp(distance, [10, 150], [0, 100])
        # 设置电脑音量
        self.volume.SetMasterVolumeLevel(vol, None)
        # 显示矩形
        cv2.putText(img, str(math.ceil(rect_percent_text)) + "%", (10, 350),
                    cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 255), 3)
        img = cv2.rectangle(img, (30, 100), (70, 300), (255, 0, 0), 3)
        img = cv2.rectangle(img, (30, math.ceil(300 - rect_height)), (70, 300), (255, 0, 0), -1)
        return img

    def rec(self):

        cap = cv2.VideoCapture(0)
        while True:
            ret,frame = cap.read()
            frame = cv2.flip(frame,1)

            frame ,find_list = self.findhand(frame)
            if len(find_list) !=0:
                frame = self.finger_draw(frame,8)
                frame = self.finger_draw(frame,4)

                frame ,a = self.finger_line(frame,8,4)
                # print(a)
                frame = self.vio(frame)
            cv2.imshow('output',frame)
            if ord('q') == cv2.waitKey(1):
                break
        cap.release()
        cv2.destroyAllWindows()

s=lis()
s.rec()