content: # Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENT
  # except for the third-party components listed below.
  # Hunyuan 3D does not impose any additional limitations beyond what is outlined
  # in the repsective licenses of these third-party components.
  # Users must comply with all terms and conditions of original licenses of these third-party
  # components and must ensure that the usage of the third party components adheres to
  # all relevant laws and regulations.
  
  # For avoidance of doubts, Hunyuan 3D means the large language models and
  # their software and algorithms, including trained model weights, parameters (including
  # optimizer states), machine-learning model code, inference-enabling code, training-enabling code,
  # fine-tuning enabling code and other elements of the foregoing made publicly available
  # by Tencent in accordance with TENCENT HUNYUAN COMMUNITY LICENSE AGREEMENT.
  
  import numpy as np
  from PIL import Image
  
  
  class imageSuperNet:
      def __init__(self, config) -> None:
          from realesrgan import RealESRGANer
          from basicsr.archs.rrdbnet_arch import RRDBNet
  
          model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
          upsampler = RealESRGANer(
              scale=4,
              model_path=config.realesrgan_ckpt_path,
              dni_weight=None,
              model=model,
              tile=0,
              tile_pad=10,
              pre_pad=0,
              half=True,
              gpu_id=None,
          )
          self.upsampler = upsampler
  
      def __call__(self, image):
          output, _ = self.upsampler.enhance(np.array(image))
          output = Image.fromarray(output)
          return output
  