# Depth-to-image

The Stable Diffusion model can also infer depth based on an image using [MiDaS](https://github.com/isl-org/MiDaS). This allows you to pass a text prompt and an initial image to condition the generation of new images as well as a `depth_map` to preserve the image structure. > [!TIP] > Make sure to check out the Stable Diffusion [Tips](overview#tips) section to learn how to explore the tradeoff between scheduler speed and quality, and how to reuse pipeline components efficiently! > > If you're interested in using one of the official checkpoints for a task, explore the [CompVis](https://huggingface.co/CompVis) and [Stability AI](https://huggingface.co/stabilityai) Hub organizations! ## StableDiffusionDepth2ImgPipeline [[autodoc]] StableDiffusionDepth2ImgPipeline - all - __call__ - enable_attention_slicing - disable_attention_slicing - enable_xformers_memory_efficient_attention - disable_xformers_memory_efficient_attention - load_textual_inversion - load_lora_weights - save_lora_weights ## StableDiffusionPipelineOutput [[autodoc]] pipelines.stable_diffusion.StableDiffusionPipelineOutput