class_docstr: Dataset for EPIC-Kitchen.
class_docstr_tok: ["Dataset","for","EPIC-Kitchen","."]
code: def __init__(
      self,
      root_path: str,
      annotationfile_path: str,
      dataset_split: str,
      image_modality: str,
      num_segments: int = 1,
      frames_per_segment: int = 16,
      imagefile_template: str = "img_{:010d}.jpg",
      transform=None,
      random_shift: bool = True,
      test_mode: bool = False,
      n_classes: int = 8,
  ):
      self.root_path = Path(root_path)
      self.image_modality = image_modality
      self.dataset = dataset_split
      self.n_classes = n_classes
      self.img_path = self.root_path.joinpath(
          self.image_modality, self.dataset
      )
      super(EPIC, self).__init__(
          root_path,
          annotationfile_path,
          image_modality,
          num_segments,
          frames_per_segment,
          imagefile_template,
          transform,
          random_shift,
          test_mode,
      )
  
file_path: pykale/kale/loaddata/video_datasets.py
imports: import logging
  import math
  import os
  from pathlib import Path
  import pandas
  from PIL import Image
  from kale.loaddata.videos import VideoFrameDataset, VideoRecord
label_desc: Use image node_id 1 to create a new EPIC object from inherited base classes: VideoFrameDataset with example: obj = EPIC(root_path, annotationfile_path, dataset_split, image_modality, num_segments, frames_per_segment, imagefile_template, transform, random_shift, test_mode, n_classes)