handTrackingmodule1.py

import cv2
import mediapipe as mp
import time
import math
import numpy as np


class handDetector():
    def __init__(self):
        self.mode = False
        self.maxHands = 2
        self.detectionCon = 0.5
        self.trackCon = 0.5
        self.lmList=[]
        self.mpHands = mp.solutions.hands
        self.hands = self.mpHands.Hands()
        self.mpDraw = mp.solutions.drawing_utils
        self.tipIds = [4, 8, 12, 16, 20]


    # def findHands(self, img, draw=True):
    #     imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    #     self.results = self.hands.process(imgRGB)
    #
    #     if self.results.multi_hand_landmarks:
    #         for handLms in self.results.multi_hand_landmarks:
    #             if draw:
    #                 self.mpDraw.draw_landmarks(img, handLms, self.mpHands.HAND_CONNECTIONS)
    #
    #     return img

    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, pz = int(lm.x * w), int(lm.y * h), int(lm.z * w)
                    mylmList.append([px, py, pz])
                    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 findPosition(self, img, handNo=0, draw=True):
        xList = []
        yList = []
        bbox = []
        self.lmList = []
        if self.results.multi_hand_landmarks:
            myHand = self.results.multi_hand_landmarks[handNo]
            for id, lm in enumerate(myHand.landmark):
                h, w, c = len(img),len(img[0]),len(img[0][0])
                cx, cy = int(lm.x * w), int(lm.y * w)
                xList.append(cx)
                yList.append(cy)
                self.lmList.append([id, cx, cy])
                if draw:
                    cv2.circle(img, (cx, cy), 5, (255, 0, 255), cv2.FILLED)

            xmin, xmax = min(xList), max(xList)
            ymin, ymax = min(yList), max(yList)
            bbox = xmin, ymin, xmax, ymax
            if draw:
                cv2.rectangle(img, (xmin - 20, ymin - 20), (xmax + 20, ymax + 20), (0, 255, 0), 2)
        return self.lmList, bbox

    # def fingersUp(self):
    #     fingers = []
    #     # thumb
    #     if self.lmlist[self.tipIds[0]][1] > self.lmlist[self.tipIds[0] - 1][1]:
    #         fingers.append(1)
    #     else:
    #         fingers.append(0)
    #
    #     # fingers
    #     for id in range(1, 5):
    #         if self.lmlist[self.tipIds[id]][2] < self.lmlist[self.tipIds[id] - 2][2]:
    #             fingers.append(1)
    #         else:
    #             fingers.append(0)
    #
    #     # totalFingers = fingers.count(1)
    #     return fingers

    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:
            self.fingers = []
            # Thumb
            if myHandType == "Right":
                if myLmList[self.tipIds[0]][0] > myLmList[self.tipIds[0] - 1][0]:
                    self.fingers.append(1)
                else:
                    self.fingers.append(0)
            else:
                if myLmList[self.tipIds[0]][0] < myLmList[self.tipIds[0] - 1][0]:
                    self.fingers.append(1)
                else:
                    self.fingers.append(0)

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

    def findDistance(self, p1, p2, img, draw=True, r=15, t=3):
        x1, y1 = p1[0],p1[1]
        x2, y2 = p2[0],p2[1]
        cx, cy = (x1 + x2) // 2, (y1 + y2) // 2
        info = (x1, y1, x2, y2, cx, cy)
        if draw:
            cv2.line(img, (x1, y1), (x2, y2), (255, 0, 255), t)
            cv2.circle(img, (x1, y1), r, (255, 0, 255), cv2.FILLED)
            cv2.circle(img, (x2, y2), r, (255, 0, 255), cv2.FILLED)
            cv2.circle(img, (cx, cy), r, (0, 0, 255), cv2.FILLED)
        length = math.hypot(x2 - x1, y2 - y1)

        return length, info, img


def main():
    pTime = 0
    cTime = 0
    cap = cv2.VideoCapture(0)
    detector = handDetector()
    while True:
        success, img = cap.read()
        img = detector.findHands(img)
        lmlist, bbox = detector.findPosition(img)
        if len(lmlist) != 0:
            print(lmlist[4])

        cTime = time.time()
        fps = 1 / (cTime - pTime)
        pTime = cTime

        cv2.putText(img, str(int(fps)), (10, 70), cv2.FONT_HERSHEY_PLAIN, 3, (255, 8, 8), 3)

        # 12. display
        cv2.imshow('image', img)
        cv2.waitKey(1)


if __name__ == "__main__":
    main()