手势控制鼠标（源码）

写在前面：程序不是很难，只是调用了很多的库，安装好库后点击运行即可。

pip install 以下这些
mediapipe==0.8.9
numpy
autopy
numpy
opencv-python

如果还有缺少按照相应的报错提示安装对应的库即可。

通过食指控制鼠标移动，五指控制上滑下滑，双指右键。

具体效果不展示了，因为不愿意露脸，大家自己尝试一下就知道了。

demo_windows.py

"""
功能：手势操作电脑鼠标
1、使用OpenCV读取摄像头视频流；
2、识别手掌关键点像素坐标；
3、根据坐标计算不同的手势模式
4、控制对应的鼠标操作：移动、单击、双击、右击、向上滑、向下滑、拖拽
"""# 导入其他依赖包
import timeimport autopy
# 导入OpenCV
import cv2
import numpy as np
import pyautogui# 导入handprocess
import handProcess
from utils import Utils# 识别控制类
class VirtualMouse:def __init__(self):# image实例，以便另一个类调用self.image=None# 主函数def recognize(self):handprocess = handProcess.HandProcess(False,1)utils = Utils()fpsTime = time.time()cap = cv2.VideoCapture(0)# 视频分辨率resize_w = 960resize_h = 720# 控制边距frameMargin = 100# 屏幕尺寸screenWidth, screenHeight = pyautogui.size() # 柔和处理参数stepX, stepY = 0, 0finalX, finalY = 0, 0smoothening = 7action_trigger_time = {'single_click':0,'double_click':0,'right_click':0}mouseDown = False# fps = cap.get(cv2.CAP_PROP_FPS)# fps = 18# videoWriter = cv2.VideoWriter('./record_video/out'+str(time.time())+'.mp4', cv2.VideoWriter_fourcc(*'H264'), fps, (618,720))while cap.isOpened():action_zh = ''success, self.image = cap.read()# 裁剪self.image = cv2.resize(self.image, (resize_w, resize_h))if not success:print("空帧")continue# 提高性能self.image.flags.writeable = False# 转为RGBself.image = cv2.cvtColor(self.image, cv2.COLOR_BGR2RGB)# 镜像，需要根据镜头位置来调整self.image = cv2.flip(self.image, 1)# 处理手掌self.image = handprocess.processOneHand(self.image)# 画框框cv2.rectangle(self.image, (frameMargin, frameMargin), (resize_w - frameMargin, resize_h - frameMargin),(255, 0, 255), 2)# 获取动作self.image,action,key_point = handprocess.checkHandAction(self.image,drawKeyFinger=True)action_zh = handprocess.action_labels[action]if key_point:# 映射距离x3 = np.interp(key_point[0], (frameMargin, resize_w - frameMargin), (0, screenWidth))y3 = np.interp(key_point[1], (frameMargin, resize_h - frameMargin), (0, screenHeight))# 柔和处理finalX = stepX + (x3 - stepX) / smootheningfinalY = stepY + (y3 - stepY) / smootheningnow = time.time() if action_zh == '鼠标拖拽':# 原始方法# pyautogui.dragTo(finalX, finalY)     # 解决windows可能无效及卡顿问题if not mouseDown:pyautogui.mouseDown(button='left')mouseDown = Trueautopy.mouse.move(finalX, finalY)else:if mouseDown:pyautogui.mouseUp(button='left')mouseDown = Falseif action_zh == '鼠标移动':# pyautogui.moveTo(finalX, finalY)# 解决移动卡顿的问题autopy.mouse.move(finalX, finalY)elif action_zh == '单击准备':passelif action_zh == '触发单击'  and  (now - action_trigger_time['single_click'] > 0.3):pyautogui.click()action_trigger_time['single_click'] = nowelif action_zh == '右击准备':passelif action_zh == '触发右击' and  (now - action_trigger_time['right_click'] > 2):pyautogui.click(button='right')  action_trigger_time['right_click'] = nowelif action_zh == '向上滑页':pyautogui.scroll(30)elif action_zh == '向下滑页':pyautogui.scroll(-30)stepX, stepY = finalX, finalYself.image.flags.writeable = Trueself.image = cv2.cvtColor(self.image, cv2.COLOR_RGB2BGR)# 显示刷新率FPScTime = time.time()fps_text = 1/(cTime-fpsTime)fpsTime = cTimeself.image = utils.cv2AddChineseText(self.image, "帧率: " + str(int(fps_text)),  (10, 30), textColor=(255, 0, 255), textSize=50)# 显示画面# videoWriter.write(self.image) self.image = cv2.resize(self.image, (resize_w//2, resize_h//2))cv2.imshow('virtual mouse', self.image)if cv2.waitKey(5) & 0xFF == 27:breakcap.release()# 开始程序
control = VirtualMouse()
control.recognize()

handProcess.py

"""
! author: enpei
! date: 2021-12-15
功能：封装手部识别常用功能，简化Demo代码复杂度
"""
# 导入OpenCV
import cv2
# 导入mediapipe
import mediapipe as mp
import time
import math
import numpy as np
from utils import Utilsclass HandProcess:def __init__(self,static_image_mode=False,max_num_hands=2):# 参数self.mp_drawing = mp.solutions.drawing_utilsself.mp_drawing_styles = mp.solutions.drawing_stylesself.mp_hands = mp.solutions.handsself.hands = self.mp_hands.Hands(static_image_mode=static_image_mode,min_detection_confidence=0.7,min_tracking_confidence=0.5,max_num_hands=max_num_hands)self.landmark_list = []self.action_labels = {'none': '无','move': '鼠标移动','click_single_active': '触发单击','click_single_ready': '单击准备','click_right_active': '触发右击','click_right_ready': '右击准备','scroll_up': '向上滑页','scroll_down': '向下滑页','drag': '鼠标拖拽'}self.action_deteted = ''# 检查左右手在数组中的indexdef checkHandsIndex(self,handedness):# 判断数量if len(handedness) == 1:handedness_list = [handedness[0].classification[0].label]else:handedness_list = [handedness[0].classification[0].label,handedness[1].classification[0].label]return handedness_list# 计算两点点的距离def getDistance(self,pointA,pointB):return math.hypot((pointA[0]-pointB[0]),(pointA[1]-pointB[1]))# 获取坐标    def getFingerXY(self,index):return (self.landmark_list[index][1],self.landmark_list[index][2])# 绘制相关点def drawInfo(self,img,action):thumbXY,indexXY,middleXY = map(self.getFingerXY,[4,8,12])if action == 'move':img = cv2.circle(img,indexXY,20,(255,0,255),-1)elif action == 'click_single_active':middle_point = int(( indexXY[0]+ thumbXY[0])/2),int((  indexXY[1]+ thumbXY[1] )/2)img = cv2.circle(img,middle_point,30,(0,255,0),-1)elif action == 'click_single_ready':img = cv2.circle(img,indexXY,20,(255,0,255),-1)img = cv2.circle(img,thumbXY,20,(255,0,255),-1)img = cv2.line(img,indexXY,thumbXY,(255,0,255),2)elif action == 'click_right_active':middle_point = int(( indexXY[0]+ middleXY[0])/2),int((  indexXY[1]+ middleXY[1] )/2)img = cv2.circle(img,middle_point,30,(0,255,0),-1)elif action == 'click_right_ready':img = cv2.circle(img,indexXY,20,(255,0,255),-1)img = cv2.circle(img,middleXY,20,(255,0,255),-1)img = cv2.line(img,indexXY,middleXY,(255,0,255),2)return img# 返回手掌各种动作def checkHandAction(self,img,drawKeyFinger=True):upList = self.checkFingersUp()action = 'none'if len(upList) == 0:return img,action,None# 侦测距离dete_dist = 100# 中指key_point = self.getFingerXY(8)# 移动模式：单个食指在上，鼠标跟随食指指尖移动，需要smooth处理防抖if (upList == [0,1,0,0,0]):action = 'move'# 单击：食指与拇指出现暂停移动，如果两指捏合，触发单击if (upList == [1,1,0,0,0]):l1 = self.getDistance(self.getFingerXY(4),self.getFingerXY(8))action = 'click_single_active'  if l1 < dete_dist else  'click_single_ready'                # 右击：食指、中指出现暂停移动，如果两指捏合，触发右击if (upList == [0,1,1,0,0]):l1 = self.getDistance(self.getFingerXY(8),self.getFingerXY(12))action = 'click_right_active' if l1 < dete_dist else 'click_right_ready'# 向上滑：五指向上if (upList == [1,1,1,1,1]):action = 'scroll_up'# 向下滑：除拇指外四指向上if (upList == [0,1,1,1,1]):action = 'scroll_down'# 拖拽：拇指、食指外的三指向上if (upList == [0,0,1,1,1]):# 换成中指key_point = self.getFingerXY(12)action = 'drag'# 根据动作绘制相关点img = self.drawInfo(img,action) if drawKeyFinger else imgself.action_deteted = self.action_labels[action]return img,action,key_point# 返回向上手指的数组def checkFingersUp(self):fingerTipIndexs = [4,8,12,16,20]upList = []if len(self.landmark_list) == 0:return upList# 拇指，比较x坐标if self.landmark_list[fingerTipIndexs[0]][1] < self.landmark_list[fingerTipIndexs[0]-1][1]:upList.append(1)else:upList.append(0)# 其他指头，比较Y坐标for i in range(1,5):if self.landmark_list[fingerTipIndexs[i]][2] < self.landmark_list[fingerTipIndexs[i]-2][2]:upList.append(1)else:upList.append(0)return upList# 分析手def processOneHand(self,img,drawBox=True,drawLandmarks=True):utils = Utils()results = self.hands.process(img)self.landmark_list = []if results.multi_hand_landmarks:for hand_index,hand_landmarks in enumerate(results.multi_hand_landmarks):if drawLandmarks:self.mp_drawing.draw_landmarks(img,hand_landmarks,self.mp_hands.HAND_CONNECTIONS,self.mp_drawing_styles.get_default_hand_landmarks_style(),self.mp_drawing_styles.get_default_hand_connections_style())# 遍历landmarkfor landmark_id, finger_axis in enumerate(hand_landmarks.landmark):h,w,c = img.shapep_x,p_y = math.ceil(finger_axis.x * w), math.ceil(finger_axis.y * h)self.landmark_list.append([landmark_id, p_x, p_y,finger_axis.z])# 框框和labelif drawBox:x_min,x_max =  min(self.landmark_list,key=lambda i : i[1])[1], max(self.landmark_list,key=lambda i : i[1])[1]y_min,y_max =  min(self.landmark_list,key=lambda i : i[2])[2], max(self.landmark_list,key=lambda i : i[2])[2]img = cv2.rectangle(img,(x_min-30,y_min-30),(x_max+30,y_max+30),(0, 255, 0),2)img = utils.cv2AddChineseText(img, self.action_deteted,  (x_min-20,y_min-120), textColor=(255, 0, 255), textSize=60)return img

utils.py

# 导入PIL
from PIL import Image, ImageDraw, ImageFont
# 导入OpenCV
import cv2
import numpy as npclass Utils:def __init__(self):pass# 添加中文def cv2AddChineseText(self,img, text, position, textColor=(0, 255, 0), textSize=30):if (isinstance(img, np.ndarray)):  # 判断是否OpenCV图片类型img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))# 创建一个可以在给定图像上绘图的对象draw = ImageDraw.Draw(img)# 字体的格式fontStyle = ImageFont.truetype("./fonts/simsun.ttc", textSize, encoding="utf-8")# 绘制文本draw.text(position, text, textColor, font=fontStyle)# 转换回OpenCV格式return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)

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