code: def __init__(
      self,
      image_size=364,
      mean=None,
      std=None,
      min_scale=0.5,
      max_scale=1.0,
  ):
      super().__init__(mean=mean, std=std)
  
      self.transform = transforms.Compose(
          [
              transforms.RandomResizedCrop(
                  image_size,
                  scale=(min_scale, max_scale),
                  interpolation=InterpolationMode.BICUBIC,
              ),
              transforms.RandomHorizontalFlip(),
              transforms.ToTensor(),
              self.normalize,
          ]
      )
  
imports: import re
  from lavis.common.registry import registry
  from lavis.processors.base_processor import BaseProcessor
  from lavis.processors.randaugment import RandomAugment
  from omegaconf import OmegaConf
  from torchvision import transforms
  from torchvision.transforms.functional import InterpolationMode
label_desc: Use image node_id 1 to create a new Blip2ImageTrainProcessor object from inherited base classes: BlipImageBaseProcessor with example: obj = Blip2ImageTrainProcessor(image_size, mean, std, min_scale, max_scale)