Create HTrack.py

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Srinadh Vura 2023-10-21 12:59:00 +05:30 committed by GitHub
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"""
This file uses mediapipe - a framework by google to detect the landmarks of hand (21)
in the image captured from webcam using openCV
The functionality wrapped as handDetector class containing methods drawHands() and getPositions()
drawHands() --> To draw land marks of detected hands
getPositions() --> To return the found landmarks as a list
"""
import cv2
import mediapipe as mp
import time
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.mpDraw = mp.solutions.drawing_utils
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)
def drawHands(self, img, draw=True):
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
self.res = self.hands.process(imgRGB)
if self.res.multi_hand_landmarks:
for handLms in self.res.multi_hand_landmarks:
if draw:
self.mpDraw.draw_landmarks(img, handLms,mp.solutions.hands.HAND_CONNECTIONS)
return img
def getPositions(self, img, handId=0):
self.xList=[]
self.yList=[]
self.lmList = []
if self.res.multi_hand_landmarks:
decHand = self.res.multi_hand_landmarks[handId]
for index, lmark in enumerate(decHand.landmark):
h, w, c = img.shape
cx, cy = int(lmark.x * w), int(lmark.y * h)
self.xList.append(cx)
self.yList.append(cy)
self.lmList.append([index, cx, cy])
return self.lmList
def main():
prevTime = 0
currTime = 0
cap = cv2.VideoCapture(0)
detector = handDetector()
while True:
_, img = cap.read()
img = detector.drawHands(img)
lms= detector.getPositions(img)
print(lms)
currTime = time.time()
fps = 1 / (cTime - pTime)
prevTime = cTime
cv2.putText(img, str(int(fps)), (10, 70), cv2.FONT_HERSHEY_PLAIN, 3,(51, 0, 255), 3)
cv2.imshow("Image", img)
cv2.waitKey(1)
if __name__ == "__main__":
main()