윈도우 환경 mediapipe hand tracking

20201115 윈도우 환경 mediapipe hand tracking

import os
import cv2
import mediapipe as mp

mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands

def track(input_data_path):
  # For webcam input: 
  hands = mp_hands.Hands(
      min_detection_confidence=0.7, min_tracking_confidence=0.5)
  # cap = cv2.VideoCapture(0) => default: webcam input
  cap = cv2.VideoCapture(input_data_path)
  # cap = cv2.VideoCapture('input_video/hwajae/KETI_SL_0000000419.avi')

  while cap.isOpened():
    success, image = cap.read()
    if not success:
      break

    # Flip the image horizontally for a later selfie-view display, and convert
    # the BGR image to RGB.
    image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
    # To improve performance, optionally mark the image as not writeable to
    # pass by reference.
    image.flags.writeable = False
    results = hands.process(image)
    # Draw the hand annotations on the image.
    image.flags.writeable = True
    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
    if results.multi_hand_landmarks:
      for hand_landmarks in results.multi_hand_landmarks:
        print(hand_landmarks)
        mp_drawing.draw_landmarks(
            image, hand_landmarks, mp_hands.HAND_CONNECTIONS)
    cv2.imshow('MediaPipe Hands', image)
    # print(image, end=' ')
    # print(len(image))
    # print(image[0])
    if cv2.waitKey(5) & 0xFF == 27:
      break
  hands.close()
  cap.release()

  print("success")
  
def main(input_data_path):
    folder_list = os.listdir(input_data_path)

    for folder in folder_list:
        word = '/' + folder + '/'
        file_list = os.listdir(input_data_path + word)
        
        for file in file_list:
            # print(file)
            # print(input_data_path + word + file)
             track(input_data_path + word + file)

if __name__ == "__main__":
  main('input_video')

 

코드 참고

google.github.io/mediapipe/getting_started/install.html#installing-on-windows