Python_Test

import cv2
import mediapipe as mp
from json import dumps
mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands

def dump_as_json(data_point):
  return dumps({'x': data_point.x, 'y': data_point.y, 'z': data_point.z})

cap = cv2.VideoCapture(0)
with mp_hands.Hands(
    max_num_hands=2,
    min_detection_confidence=0.8,
    min_tracking_confidence=0.8) as hands:
  while cap.isOpened():
    success, image = cap.read()
    if not success:
      print("Ignoring empty camera frame.")
      # If loading a video, use 'break' instead of 'continue'.
      continue

    # 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 i, hand_landmarks in enumerate(results.multi_hand_landmarks):
        for data_point in hand_landmarks.landmark:
          print(dump_as_json(data_point))
        mp_drawing.draw_landmarks(
            image, hand_landmarks, mp_hands.HAND_CONNECTIONS)
    cv2.imshow('MediaPipe Hands', image)
    if cv2.waitKey(5) & 0xFF == 27:
      break
cap.release()