code: def __init__(
      self,
      image_size=224,
      mean=None,
      std=None,
      min_scale=0.9,
      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,
              ),
              _convert_to_rgb,
              transforms.ToTensor(),
              self.normalize,
          ]
      )
  
file_path: lavis/lavis/processors/clip_processors.py
imports: from lavis.common.registry import registry
  from lavis.processors.blip_processors import BlipImageBaseProcessor
  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 ClipImageTrainProcessor object from inherited base classes: BlipImageBaseProcessor with example: obj = ClipImageTrainProcessor(image_size, mean, std, min_scale, max_scale)