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33 lines
1.7 KiB
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33 lines
1.7 KiB
Plaintext
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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-->
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# Depth-to-Image Generation
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## StableDiffusionDepth2ImgPipeline
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The depth-guided stable diffusion model was created by the researchers and engineers from [CompVis](https://github.com/CompVis), [Stability AI](https://stability.ai/), and [LAION](https://laion.ai/), as part of Stable Diffusion 2.0. It uses [MiDas](https://github.com/isl-org/MiDaS) to infer depth based on an image.
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[`StableDiffusionDepth2ImgPipeline`] lets you pass a text prompt and an initial image to condition the generation of new images as well as a `depth_map` to preserve the images’ structure.
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The original codebase can be found here:
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- *Stable Diffusion v2*: [Stability-AI/stablediffusion](https://github.com/Stability-AI/stablediffusion#depth-conditional-stable-diffusion)
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Available Checkpoints are:
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- *stable-diffusion-2-depth*: [stabilityai/stable-diffusion-2-depth](https://huggingface.co/stabilityai/stable-diffusion-2-depth)
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[[autodoc]] StableDiffusionDepth2ImgPipeline
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- all
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- __call__
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- enable_attention_slicing
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- disable_attention_slicing
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- enable_xformers_memory_efficient_attention
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- disable_xformers_memory_efficient_attention |