code: def from_config(cls, cfg=None):
      if cfg is None:
          cfg = OmegaConf.create()
  
      image_size = cfg.get("image_size", 256)
  
      mean = cfg.get("mean", None)
      std = cfg.get("std", None)
  
      min_scale = cfg.get("min_scale", 0.5)
      max_scale = cfg.get("max_scale", 1.0)
  
      n_frms = cfg.get("n_frms", MAX_INT)
      full_video = cfg.get("full_video", True)
  
      return cls(
          image_size=image_size,
          mean=mean,
          std=std,
          min_scale=min_scale,
          max_scale=max_scale,
          n_frms=n_frms,
          full_video=full_video,
      )
  
imports: import torch
  from lavis.common.registry import registry
  from lavis.datasets.data_utils import load_video, load_clip
  from lavis.processors import transforms_video
  from lavis.processors.base_processor import BaseProcessor
  from lavis.processors.randaugment import VideoRandomAugment
  from lavis.processors import functional_video
  from omegaconf import OmegaConf
  from torchvision import transforms
label_desc: Use image node_id 3 for calling the AlproVideoTrainProcessor obj's underlying member method code with example usage: obj.from_config(cls, cfg) and returns: cls