Hands Tracker using OpenCV & MediaPipe

HandsTracker.py

# pip install mediapipe
import cv2
import mediapipe as mp
import time

cap = cv2.VideoCapture(0)

mpHands = mp.solutions.hands
hands = mpHands.Hands() # using default paramaters of '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:
		for handLms in results.multi_hand_landmarks:
			for id, lm in enumerate(handLms.landmark):
				# print(id, lm)
				h, w, c = img.shape
				cx, cy = int(lm.x * w), int(lm.y * h)
				# print(id, cx, cy)

				if id == 0: # change the ID
					cv2.circle(img, (cx, cy), 10, (255, 0, 255), cv2.FILLED)

				if id == 4: # finger 1
					cv2.circle(img, (cx, cy), 10, (255, 0, 255), cv2.FILLED)

				# cv2.circle(img, (cx, cy), 10, (255, 0, 255), cv2.FILLED) # show all

			mpDraw.draw_landmarks(img, handLms, mpHands.HAND_CONNECTIONS)

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

	cv2.putText(img, str(int(fps)), (10, 70), cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 255), 3)
	cv2.imshow("Image", img)
	cv2.waitKey(1)