image_emb, zero_image_emb = prior_pipeline(
prompt=prompt, negative_prompt=negative_prior_prompt, generator=generator
).to_tuple()
```  
Finally, pass the image embeddings and the depth image to the [`KandinskyV22ControlnetPipeline`] to generate an image:  
```py
image = pipeline(image_embeds=image_emb, negative_image_embeds=zero_image_emb, hint=hint, num_inference_steps=50, generator=generator, height=768, width=768).images[0]
image
```  
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