class_docstr: A dataset of `Methods-Time Measurement-1 <https://en.wikipedia.org/wiki/Methods-time_measurement>`_
  (MTM-1) motions, signalled as consecutive video frames of 21 3D hand keypoints, acquired via
  `MediaPipe Hands <https://google.github.io/mediapipe/solutions/hands.html>`_ from RGB-Video
  material. Vertices are the finger joints of the human hand and edges are the bones connecting
  them. The targets are manually labeled for each frame, according to one of the five MTM-1
  motions (classes :math:`C`): Grasp, Release, Move, Reach, Position plus a negative class for
  frames without graph signals (no hand present). This is a classification task where :math:`T`
  consecutive frames need to be assigned to the corresponding class :math:`C`. The data x is
  returned in shape :obj:`(3, 21, T)`, the target is returned one-hot-encoded in shape :obj:`(T, 6)`.
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code: def __init__(self):
      self._read_web_data()
  
file_path: pytorch_geometric_temporal/torch_geometric_temporal/dataset/mtm.py
imports: import json
  import urllib
  import numpy
  from torch_geometric_temporal.signal import StaticGraphTemporalSignal
label_desc: Use image node_id 1 to create a new MTMDatasetLoader object  with example: obj = MTMDatasetLoader()