mage,
...     cond_subject,
...     tgt_subject,
...     guidance_scale=guidance_scale,
...     num_inference_steps=num_inference_steps,
...     neg_prompt=negative_prompt,
...     height=512,
...     width=512,
... ).images
>>> output[0].save("image.png")  BlipDiffusionControlNetPipeline  class diffusers.BlipDiffusionControlNetPipeline  < source > ( tokenizer: CLIPTokenizer text_encoder: ContextCLIPTextModel vae: AutoencoderKL unet: UNet2DCond