code: def load_image(image_file):
      import requests
      from PIL import Image
      from io import BytesIO
  
      if image_file.startswith("http://") or image_file.startswith(
          "https://"
      ):
          response = requests.get(image_file)
          image = Image.open(BytesIO(response.content)).convert("RGB")
      else:
          image = Image.open(image_file).convert("RGB")
      return image
  
file_path: BigDL/python/llm/example/GPU/PyTorch-Models/Model/llava/generate.py
imports: import argparse
  import torch
  import time
  from transformers import AutoModelForCausalLM
  from llava.model.language_model.llava_llama import LlavaLlamaForCausalLM
  from transformers import AutoTokenizer
  from llava.constants import DEFAULT_IMAGE_PATCH_TOKEN, IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_TOKEN, DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN
  from llava.conversation import conv_templates, SeparatorStyle
  from llava.utils import disable_torch_init
  from llava.mm_utils import process_images, tokenizer_image_token, get_model_name_from_path, KeywordsStoppingCriteria
  from bigdl.llm import optimize_model
label_desc: Use image node_id 3 for calling a global function with example usage: load_image(image_file) and returns: image