code: def get_interactive_image(key=None):
      image = st.file_uploader(
          "Input", type=["jpg", "JPEG", "png"], key=key
      )
      if image is not None:
          image = Image.open(image)
          if not image.mode == "RGB":
              image = image.convert("RGB")
          return image
  
imports: import importlib
  import streamlit
  import torch
  import cv2
  import numpy
  import PIL
  from omegaconf import OmegaConf
  from PIL import Image
  from tqdm import trange
  import io, os
  from torch import autocast
  from einops import rearrange, repeat
  from torchvision.utils import make_grid
  from pytorch_lightning import seed_everything
  from contextlib import nullcontext
  from ldm.models.diffusion.ddim import DDIMSampler
  from ldm.models.diffusion.plms import PLMSSampler
  from ldm.models.diffusion.dpm_solver import DPMSolverSampler
label_desc: Use image node_id 3 for calling a global function with example usage: get_interactive_image(key) and returns: image