File size: 1,825 Bytes
fc64fc0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | import cv2
import mediapipe as mp
# Initialize mediapipe hands module
mphands = mp.solutions.hands
mpdrawing = mp.solutions.drawing_utils
# Specify the path to your video file
vids =[
'/home/stevend/Documents/Notebooks/Dia1/videos/mano1.mp4',
'/home/stevend/Documents/Notebooks/Dia1/videos/mano2.mp4',
'/home/stevend/Documents/Notebooks/Dia1/videos/mano3.mp4',
'/home/stevend/Documents/Notebooks/Dia1/videos/mano4.mp4',
'/home/stevend/Documents/Notebooks/Dia1/videos/mano5.mp4',
'/home/stevend/Documents/Notebooks/Dia1/videos/parkinzon.mp4',
'/home/stevend/Documents/Notebooks/Dia1/videos/dedo_gatillo.mp4'
]
vidpath = vids[6]
# Initialize video capture
vidcap = cv2.VideoCapture(vidpath)
# Set the desired window width and height
winwidth = 350
winheight = 600
# Initialize hand tracking
with mphands.Hands(min_detection_confidence=0.5, min_tracking_confidence=0.5) as hands:
while vidcap.isOpened():
ret, frame = vidcap.read()
if not ret:
break
# Convert the BGR image to RGB
rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# Process the frame for hand tracking
processFrames = hands.process(rgb_frame)
# Draw landmarks on the frame
if processFrames.multi_hand_landmarks:
for lm in processFrames.multi_hand_landmarks:
mpdrawing.draw_landmarks(frame, lm, mphands.HAND_CONNECTIONS)
# Resize the frame to the desired window size
resized_frame = cv2.resize(frame, (winwidth, winheight))
# Display the resized frame
cv2.imshow('Hand Tracking', resized_frame)
# Exit loop by pressing 'q'
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Release the video capture and close windows
vidcap.release()
cv2.destroyAllWindows() |