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Create HTrack.py
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Volume_hand_controller/HTrack.py
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61
Volume_hand_controller/HTrack.py
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"""
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This file uses mediapipe - a framework by google to detect the landmarks of hand (21)
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in the image captured from webcam using openCV
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The functionality wrapped as handDetector class containing methods drawHands() and getPositions()
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drawHands() --> To draw land marks of detected hands
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getPositions() --> To return the found landmarks as a list
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"""
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import cv2
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import mediapipe as mp
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import time
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class handDetector():
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def __init__(self, mode=False, maxHands=2, detectionCon=0.5, trackCon=0.5):
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self.mode = mode
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self.maxHands = maxHands
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self.detectionCon = detectionCon
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self.trackCon = trackCon
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self.mpDraw = mp.solutions.drawing_utils
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self.hands = mp.solutions.hands.Hands(static_image_mode=self.mode,max_num_hands= self.maxHands,min_detection_confidence=self.detectionCon,min_tracking_confidence= self.trackCon)
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def drawHands(self, img, draw=True):
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imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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self.res = self.hands.process(imgRGB)
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if self.res.multi_hand_landmarks:
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for handLms in self.res.multi_hand_landmarks:
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if draw:
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self.mpDraw.draw_landmarks(img, handLms,mp.solutions.hands.HAND_CONNECTIONS)
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return img
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def getPositions(self, img, handId=0):
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self.xList=[]
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self.yList=[]
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self.lmList = []
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if self.res.multi_hand_landmarks:
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decHand = self.res.multi_hand_landmarks[handId]
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for index, lmark in enumerate(decHand.landmark):
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h, w, c = img.shape
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cx, cy = int(lmark.x * w), int(lmark.y * h)
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self.xList.append(cx)
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self.yList.append(cy)
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self.lmList.append([index, cx, cy])
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return self.lmList
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def main():
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prevTime = 0
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currTime = 0
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cap = cv2.VideoCapture(0)
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detector = handDetector()
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while True:
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_, img = cap.read()
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img = detector.drawHands(img)
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lms= detector.getPositions(img)
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print(lms)
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currTime = time.time()
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fps = 1 / (cTime - pTime)
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prevTime = cTime
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cv2.putText(img, str(int(fps)), (10, 70), cv2.FONT_HERSHEY_PLAIN, 3,(51, 0, 255), 3)
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cv2.imshow("Image", img)
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cv2.waitKey(1)
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if __name__ == "__main__":
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main()
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