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Hands Tracker using OpenCV & MediaPipe
# 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)
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