unify cards
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README.md
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@@ -5,7 +5,6 @@ license: apache-2.0
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pipeline_tag: image-to-image
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library_name: diffusers
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tags:
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- normals-estimation
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- normals estimation
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- latent consistency model
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- image analysis
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@@ -22,7 +21,7 @@ new_version: prs-eth/marigold-normals-v1-1
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<img src="https://img.shields.io/badge/%F0%9F%A4%97%20Image%20Normals%20-Demo-yellow" alt="Image Normals">
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</a>
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<a title="diffusers" href="https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
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<img src="https://img.shields.io/badge/%F0%9F%A4%97%20diffusers%20-Integration%20
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</a>
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<a title="Github" href="https://github.com/prs-eth/marigold" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
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<img src="https://img.shields.io/github/stars/prs-eth/marigold?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="Github">
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@@ -50,11 +49,10 @@ This is a model card for the `marigold-normals-lcm-v0-1` model for monocular nor
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The model is fine-tuned from the `marigold-normals-v0-1` [model](https://huggingface.co/prs-eth/marigold-normals-v0-1)
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using the latent consistency distillation method, as
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described in our papers:
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- [CVPR'2024 paper](https://
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- [
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### Using the model
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-
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- Play with the interactive [Hugging Face Spaces demo](https://huggingface.co/spaces/prs-eth/marigold-normals): check out how the model works with example images or upload your own.
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- Use it with [diffusers](https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage) to compute the results with a few lines of code.
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- Get to the bottom of things with our [official codebase](https://github.com/prs-eth/marigold).
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pipeline_tag: image-to-image
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library_name: diffusers
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tags:
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- normals estimation
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- latent consistency model
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- image analysis
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<img src="https://img.shields.io/badge/%F0%9F%A4%97%20Image%20Normals%20-Demo-yellow" alt="Image Normals">
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</a>
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<a title="diffusers" href="https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
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+
<img src="https://img.shields.io/badge/%F0%9F%A4%97%20diffusers%20-Integration%20🧨-yellow" alt="diffusers">
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</a>
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<a title="Github" href="https://github.com/prs-eth/marigold" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
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<img src="https://img.shields.io/github/stars/prs-eth/marigold?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="Github">
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The model is fine-tuned from the `marigold-normals-v0-1` [model](https://huggingface.co/prs-eth/marigold-normals-v0-1)
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using the latent consistency distillation method, as
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described in our papers:
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+
- [CVPR'2024 paper](https://hf.co/papers/2312.02145) titled "Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation"
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- [Journal extension](https://hf.co/papers/2505.09358) titled "Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis"
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### Using the model
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- Play with the interactive [Hugging Face Spaces demo](https://huggingface.co/spaces/prs-eth/marigold-normals): check out how the model works with example images or upload your own.
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- Use it with [diffusers](https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage) to compute the results with a few lines of code.
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- Get to the bottom of things with our [official codebase](https://github.com/prs-eth/marigold).
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