code: def process_image(
      self, ann, data_debug_path=None, data_debug_counter=0
  ):
      output_images = []
      img_counter = 0
      for dialogue in ann["dialogue"]:
          if "images" in dialogue:
              for img in dialogue["images"]:
                  image_path = os.path.join(
                      ann["image_path"], str(img["image_id"]) + ".jpg"
                  )
                  save_debug_image(
                      image_path,
                      data_debug_path,
                      data_debug_counter,
                      get_rank(),
                      img_idx=img_counter,
                  )
                  img_counter += 1
                  image = Image.open(image_path).convert("RGB")
  
                  image = self.vis_processor(image)
                  try:
                      image = image["pixel_values"][0]
                  except:
                      image = image
                  output_images.append(image)
  
      return output_images
  
file_path: deepspeedexamples/applications/DeepSpeed-VisualChat/utils/data/sparkles_dialogue_dataset.py
imports: import os
  import torch
  import json
  import random
  import re
  from PIL import Image
  from .vqa_dataset import VQADataset
  from utils.utils import print_rank_0, is_rank_0, get_rank
  from .utils import save_debug_image, save_debug_text
label_desc: Use image node_id 3 for calling the SparklesDialogueDataset obj's underlying member method code with example usage: obj.process_image(ann, data_debug_path, data_debug_counter) and returns: output_images