ow_res_img = Image.open(BytesIO(response.content)).convert("RGB")
>>> low_res_img = low_res_img.resize((128, 128))

>>> # run pipeline in inference (sample random noise and denoise)
>>> upscaled_image = pipeline(low_res_img, num_inference_steps=100, eta=1).images[0]
>>> # save image
>>> upscaled_image.save("ldm_generated_image.png")  ImagePipelineOutput  class diffusers.ImagePipelineOutput  < source > ( images: Union  )   Parameters   images (L