HandTrackingProject/HandTrackingMin.py at master · kastrahl/HandTrackingProject · GitHub

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import cv2
import cv2 as cv
import mediapipe as mp
import time

cap = cv.VideoCapture(0)

mpHands = mp.solutions.hands
hands = mpHands.Hands()
mpDraw = mp.solutions.drawing_utils
pTime = 0
cTime=0

while True:
    success, img = cap.read()
    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    results = hands.process(imgRGB)
    #print(results.multi_hand_landmarks)

    if results.multi_hand_landmarks:   #returning if results has landmark points
        for handLms in results.multi_hand_landmarks:   #drawing points on hand landmarks
            for id, lm in enumerate(handLms.landmark):  # id's for exact landmarks
                print(id, lm)               #we're getting decimal values need to multiply div by height width to get pixels
                h, w, c = img.shape
                cx, cy = int(lm.x*w), int(lm.y*h) #to get pixels locations
                print(id, cx, cy)

                cv2.circle(img, (cx, cy), 20, (255,0,255), cv2.FILLED) #detecting only 0 landmark
            mpDraw.draw_landmarks(img, handLms, mpHands.HAND_CONNECTIONS)   #drawing points over image and hand_connections connects the dots


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

    cv2.putText(img, str(int(fps)), (18, 70), cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 255),3)
    cv.imshow("IMAGE", img)
    key = cv.waitKey(1)
    if key == ord('q'):
        break


"""
import cv2
import mediapipe as mp
import time
import math
class handDetector():
def __init__(self, mode=False, maxHands=2, detectionCon=0.5, trackCon=0.5):
    self.mode = mode
    self.maxHands = maxHands
    self.detectionCon = detectionCon
    self.trackCon = trackCon
    self.mpHands = mp.solutions.hands
    self.hands = self.mpHands.Hands(self.mode, self.maxHands,
    self.detectionCon, self.trackCon)
    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)
    # print(results.multi_hand_landmarks)
    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 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):
        # print(id, lm)
        h, w, c = img.shape
        cx, cy = int(lm.x * w), int(lm.y * h)
        xList.append(cx)
        yList.append(cy)
        # print(id, cx, 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, (bbox[0] - 20, bbox[1] - 20),(bbox[2] + 20, bbox[3] + 20), (0, 255, 0), 2)
        return self.lmList, bbox
def fingersUp(self):
    fingers = []
    # Thumb
    if self.lmList[self.tipIds[0]][1] &gt; self.lmList[self.tipIds[0] - 1][1]:
        fingers.append(1)
    else:
        fingers.append(0)
    # 4 Fingers
    for id in range(1, 5):
        if self.lmList[self.tipIds[id]][2] &lt; self.lmList[self.tipIds[id] - 2][2]:
            fingers.append(1)
        else:
            fingers.append(0)
    return fingers
def findDistance(self, p1, p2, img, draw=True):
    x1, y1 = self.lmList[p1][1], self.lmList[p1][2]
    x2, y2 = self.lmList[p2][1], self.lmList[p2][2]
    cx, cy = (x1 + x2) // 2, (y1 + y2) // 2
    if draw:
        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)
        length = math.hypot(x2 - x1, y2 - y1)
    return length, img, [x1, y1, x2, y2, cx, cy]
def main():
    pTime = 0
    cap = cv2.VideoCapture(1)
    detector = handDetector()
    while True:
        success, img = cap.read()
        img = detector.findHands(img)
        lmList = detector.findPosition(img)
        if len(lmList) != 0:
            print(lmList[4])
        cTime = time.time()
    fps = 1 / (cTime - pTime)
    pTime = cTime<br>
    cv2.putText(img, str(int(fps)), (10, 70), cv2.FONT_HERSHEY_PLAIN, 3,
    (255, 0, 255), 3)
    cv2.imshow("Image", img)
    cv2.waitKey(1)
if __name__ == "__main__":
    main()
"""