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AiVirtualMouse4.py
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import cv2
import HandTrackingModule as htm
from pynput.mouse import Controller, Button
from pynput.keyboard import Controller as KeyboardController, Key
import numpy as np
import time
# 配置变量
frameR = 20 # 窗口缩减
smoothening = 10 # 平滑系数，用于鼠标移动
# 初始化摄像头
cap = cv2.VideoCapture(0)
# 获取摄像头宽高
wCam = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
hCam = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
print(wCam, hCam)
# 用于计算帧率和鼠标位置的变量
pTime = 0
plocX, plocY = 0, 0
clocX, clocY = 0, 0
# 初始化手部检测器和鼠标控制器
detector = htm.handDetector(maxHands=1)
mouse = Controller()
keyboard = KeyboardController()
# 屏幕分辨率
wScr, hScr = 2560, 1440
# 用于存储食指和拇指之间的前一帧距离
prevDistance = 0
# 0:握拳 1:食指移动鼠标 2:食指和中指拖动 3:食指和拇指缩放
action_flag = 0
last_zoom_time = 0 # 记录上次缩放的时间
zoom_delay = 0.05 # 延迟时间（秒）
while True:
# 从摄像头读取帧
success, img = cap.read()
# 检测手部
img = detector.findHands(img)
cv2.rectangle(img, (frameR, frameR), (wCam - frameR, hCam - frameR), (0, 255, 0), 2)
# 获取手部关键点位置
lmList = detector.findPosition(img, draw=False)
if len(lmList) == 0:
if action_flag == 2:
mouse.release(Button.left)
action_flag = 0
else:
# 检测哪些手指抬起
fingers = detector.fingersUp()
# 没有手指伸出
if fingers == [0, 0, 0, 0, 0]:
action_flag = 0
mouse.release(Button.left)
# 只有食指伸出
elif fingers == [0, 1, 0, 0, 0]:
if action_flag == 2:
mouse.release(Button.left)
action_flag = 1
forefinger_x, forefinger_y = lmList[8][1:] # 食指指尖
x3 = np.interp(forefinger_x, (frameR, wCam - frameR), (0, wScr))
y3 = np.interp(forefinger_y, (frameR, hCam - frameR), (0, hScr))
# 平滑移动
clocX = plocX + (x3 - plocX) / smoothening
clocY = plocY + (y3 - plocY) / smoothening
# 设置鼠标位置
mouse.position = (wScr - clocX, clocY)
cv2.circle(img, (forefinger_x, forefinger_y), 5, (255, 0, 0), cv2.FILLED)
plocX, plocY = clocX, clocY
# 食指和中指同时伸出
elif fingers == [0, 1, 1, 0, 0]:
if action_flag != 2:
mouse.press(Button.left)
action_flag = 2
length, img, pointInfo = detector.findDistance(8, 12, img)
cv2.circle(img, (pointInfo[4], pointInfo[5]), 5, (0, 255, 0), cv2.FILLED)
forefinger_x, forefinger_y = lmList[8][1:] # 食指指尖
# 控制鼠标移动
x3 = np.interp(forefinger_x, (frameR, wCam - frameR), (0, wScr))
y3 = np.interp(forefinger_y, (frameR, hCam - frameR), (0, hScr))
clocX = plocX + (x3 - plocX) / smoothening
clocY = plocY + (y3 - plocY) / smoothening
mouse.position = (wScr - clocX, clocY)
plocX, plocY = clocX, clocY
# 食指和拇指同时抬起
elif fingers == [1, 1, 0, 0, 0]:
action_flag = 3
length, img, _ = detector.findDistance(4, 8, img)
# 比较当前距离和之前的距离
if prevDistance == 0:
prevDistance = length
current_time = time.time()
if current_time - last_zoom_time > zoom_delay: # 检查延迟
if length > prevDistance + 5: # 增大
keyboard.press(Key.ctrl)
mouse.scroll(0, 2)
keyboard.release(Key.ctrl)
elif length < prevDistance - 5: # 减小
keyboard.press(Key.ctrl)
mouse.scroll(0, -2)
keyboard.release(Key.ctrl)
last_zoom_time = current_time # 更新最后缩放时间
prevDistance = length
else:
prevDistance = 0
# 计算并显示帧率
cTime = time.time()
fps = 1 / (cTime - pTime)
# print(fps)
pTime = cTime
cv2.putText(img, f'fps:{int(fps)}', (15, 25), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 255), 2)
cv2.imshow("Image", img)
cv2.waitKey(1)