手势虚拟键盘

 定义一个HandDetector类

import cv2
import mediapipe as mp
import math


class HandDetector:
    """
    Finds Hands using the mediapipe library. Exports the landmarks
    in pixel format. Adds extra functionalities like finding how
    many fingers are up or the distance between two fingers. Also
    provides bounding box info of the hand found.
    """

    def __init__(self, mode=False, maxHands=2, detectionCon=0.5, minTrackCon=0.5):
        """
        :param mode: In static mode, detection is done on each image: slower
        :param maxHands: Maximum number of hands to detect
        :param detectionCon: Minimum Detection Confidence Threshold
        :param minTrackCon: Minimum Tracking Confidence Threshold
        """
        self.mode = mode
        self.maxHands = maxHands
        self.detectionCon = detectionCon
        self.minTrackCon = minTrackCon

        self.mpHands = mp.solutions.hands
        self.hands = self.mpHands.Hands(static_image_mode=self.mode, max_num_hands=self.maxHands,
                                        min_detection_confidence=self.detectionCon, min_tracking_confidence = self.minTrackCon)
        self.mpDraw = mp.solutions.drawing_utils
        self.tipIds = [4, 8, 12, 16, 20]
        self.fingers = []
        self.lmList = []
        
    def findPosition(self, img, draw=True):
        self.lmList = []
        if self.results.multi_hand_landmarks:
            for handLms in self.results.multi_hand_landmarks:
                for id, lm in enumerate(handLms.landmark):
                    h, w, c = img.shape
                    cx, cy = int(lm.x * w), int(lm.y * h)
                    # print(id, cx, cy)
                    self.lmList.append([id, cx, cy])
                    if draw:
                        cv2.circle(img, (cx, cy), 12, (255, 0, 255), cv2.FILLED)
        return self.lmList

    def findHands(self, img, draw=True, flipType=True):
        """
        Finds hands in a BGR image.
        :param img: Image to find the hands in.
        :param draw: Flag to draw the output on the image.
        :return: Image with or without drawings
        """
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        self.results = self.hands.process(imgRGB)
        allHands = []
        h, w, c = img.shape
        if  self.results.multi_hand_landmarks:
            for handType,handLms in zip(self.results.multi_handedness,self.results.multi_hand_landmarks):
                myHand={}
                ## lmList
                mylmList = []
                xList = []
                yList = []
                for id, lm in enumerate(handLms.landmark):
                    px, py = int(lm.x * w), int(lm.y * h)
                    mylmList.append([px, py])
                    xList.append(px)
                    yList.append(py)

                ## bbox
                xmin, xmax = min(xList), max(xList)
                ymin, ymax = min(yList), max(yList)
                boxW, boxH = xmax - xmin, ymax - ymin
                bbox = xmin, ymin, boxW, boxH
                cx, cy = bbox[0] + (bbox[2] // 2), \
                         bbox[1] + (bbox[3] // 2)

                myHand["lmList"] = mylmList
                myHand["bbox"] = bbox
                myHand["center"] =  (cx, cy)

                if flipType:
                    if handType.classification[0].label =="Right":
                        myHand["type"] = "Left"
                    else:
                        myHand["type"] = "Right"
                else:myHand["type"] = handType.classification[0].label
                allHands.append(myHand)

                ## draw
                if draw:
                    self.mpDraw.draw_landmarks(img, handLms,
                                               self.mpHands.HAND_CONNECTIONS)
                    cv2.rectangle(img, (bbox[0] - 20, bbox[1] - 20),
                                  (bbox[0] + bbox[2] + 20, bbox[1] + bbox[3] + 20),
                                  (255, 0, 255), 2)
                    cv2.putText(img,myHand["type"],(bbox[0] - 30, bbox[1] - 30),cv2.FONT_HERSHEY_PLAIN,
                                2,(255, 0, 255),2)
        if draw:
            return allHands,img
        else:
            return allHands

    def fingersUp(self,myHand):
        """
        Finds how many fingers are open and returns in a list.
        Considers left and right hands separately
        :return: List of which fingers are up
        """
        myHandType =myHand["type"]
        myLmList = myHand["lmList"]
        if self.results.multi_hand_landmarks:
            fingers = []
            # Thumb
            if myHandType == "Right":
                if myLmList[self.tipIds[0]][0] > myLmList[self.tipIds[0] - 1][0]:
                    fingers.append(1)
                else:
                    fingers.append(0)
            else:
                if myLmList[self.tipIds[0]][0] < myLmList[self.tipIds[0] - 1][0]:
                    fingers.append(1)
                else:
                    fingers.append(0)

            # 4 Fingers
            for id in range(1, 5):
                if myLmList[self.tipIds[id]][1] < myLmList[self.tipIds[id] - 2][1]:
                    fingers.append(1)
                else:
                    fingers.append(0)
        return fingers

    def findDistance(self,p1, p2, img=None):
        """
        Find the distance between two landmarks based on their
        index numbers.
        :param p1: Point1
        :param p2: Point2
        :param img: Image to draw on.
        :param draw: Flag to draw the output on the image.
        :return: Distance between the points
                 Image with output drawn
                 Line information
        """

        x1, y1 = p1
        x2, y2 = p2
        cx, cy = (x1 + x2) // 2, (y1 + y2) // 2
        length = math.hypot(x2 - x1, y2 - y1)
        info = (x1, y1, x2, y2, cx, cy)
        if img is not None:
            cv2.circle(img, (x1, y1), 15, (255, 0, 255), cv2.FILLED)
            cv2.circle(img, (x2, y2), 15, (255, 0, 255), cv2.FILLED)
            cv2.line(img, (x1, y1), (x2, y2), (255, 0, 255), 3)
            cv2.circle(img, (cx, cy), 15, (255, 0, 255), cv2.FILLED)
            return length,info, img
        else:
            return length, info


        


def main():
    cap = cv2.VideoCapture(0)
    detector = HandDetector(detectionCon=0.8, maxHands=2)
    while True:
        # Get image frame
        success, img = cap.read()
        # Find the hand and its landmarks
        hands, img = detector.findHands(img)  # with draw
        # hands = detector.findHands(img, draw=False)  # without draw

        if hands:
            # Hand 1
            hand1 = hands[0]
            lmList1 = hand1["lmList"]  # List of 21 Landmark points
            bbox1 = hand1["bbox"]  # Bounding box info x,y,w,h
            centerPoint1 = hand1['center']  # center of the hand cx,cy
            handType1 = hand1["type"]  # Handtype Left or Right

            fingers1 = detector.fingersUp(hand1)

            if len(hands) == 2:
                # Hand 2
                hand2 = hands[1]
                lmList2 = hand2["lmList"]  # List of 21 Landmark points
                bbox2 = hand2["bbox"]  # Bounding box info x,y,w,h
                centerPoint2 = hand2['center']  # center of the hand cx,cy
                handType2 = hand2["type"]  # Hand Type "Left" or "Right"

                fingers2 = detector.fingersUp(hand2)

                # Find Distance between two Landmarks. Could be same hand or different hands
                length, info, img = detector.findDistance(lmList1[8], lmList2[8], img)  # with draw
                # length, info = detector.findDistance(lmList1[8], lmList2[8])  # with draw
        # Display
        cv2.imshow("Image", img)
        cv2.waitKey(1)


if __name__ == "__main__":
    main()

虚拟输入

import cv2
from cvzone.HandTrackingModule import HandDetector
from time import sleep
import pyautogui
import cvzone
from pynput.keyboard import Key,Controller
cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)

# 识别手势
detector = HandDetector(detectionCon=0.8)
keyboard = Controller()

# 键盘关键字
keys = [['Q', 'W', 'E', 'R', 'T', 'Y', 'U', 'I', 'O', 'P'],
        ['A', 'S', 'D', 'F', 'G', 'H', 'J', 'K', 'L', ';'],
        ['Z', 'X', 'C', 'V', 'B', 'N', 'M', ',', '.', '/']]



class Button():
    def __init__(self, pos, text, size = [50, 50]):
        self.pos = pos
        self.text = text
        self.size = size
   
   
buttonList = []
finalText = ''
for j in range(len(keys)):
    for x, key in enumerate(keys[j]):
        # 循环创建buttonList对象列表
        buttonList.append(Button([60*x+20,100+j*60],key))


def drawAll(img,buttonList):
    for button in buttonList:
        x, y = button.pos
        w, h = button.size
        cvzone.cornerRect(img, (x, y, w, h),20,rt = 0)
        cv2.rectangle(img, button.pos, (x + w, y + h), (255, 0, 255), cv2.FILLED)
        cv2.putText(img, button.text, (x + 10, y + 40),
                    cv2.FONT_HERSHEY_PLAIN, 3, (255, 255, 255), 2)
    return img


while True:
    success, img = cap.read()
    # 识别手势
    hand = detector.findHands(img)
    lmList = detector.findPosition(img, True)

    # img = mybutton.draw(img)
    img = drawAll(img,buttonList )
    if lmList:
        for button in buttonList:
            x,y = button.pos
            w,h = button.size
            if x

 

 最后:代码我完全开源可用,需要安装必要的python包。

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