Link paper and add sample usage

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by nielsr HF Staff - opened
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  1. README.md +35 -14
README.md CHANGED
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  ---
 
 
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  license: cc-by-nc-4.0
 
 
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  task_categories:
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- - depth-estimation
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- - image-to-image
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- language:
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- - en
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  tags:
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- - dermatology
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- - medical-imaging
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- - 3d-reconstruction
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- - synthetic-data
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- - skin-lesion
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- - depth-estimation
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- size_categories:
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- - 1K<n<10K
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  ---
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  # D-Synth: Synthetic Dermoscopic Dataset with Pixel-Perfect 3D Information
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- D-Synth is the first synthetic dermoscopic dataset providing pixel-perfect 3D ground truth (metric depth, surface normals, camera intrinsics) for monocular depth estimation in dermatology. Introduced in DermDepth (Carrión & Norouzi, MICCAI 2026).
 
 
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  ## Overview
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  - `generation_params.json` — full rendering parameters
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  - (subset) `render_rgb.png`, `render_depth.png`, `render_meta.json` — additional render variants
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  ## Generation pipeline
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  D-Synth extends [S-SYNTH](https://github.com/DIDSR/ssynth-release) (Kim et al., MICCAI 2024) with:
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  - **Code & training scripts**: https://github.com/hectorcarrion/dermdepth
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  - **Fine-tuned DermDepth checkpoints**: https://huggingface.co/hcarrion/DermDepth
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- - **Base depth model**: https://huggingface.co/Ruicheng/moge-2-vitl-normal
 
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  ---
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+ language:
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+ - en
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  license: cc-by-nc-4.0
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+ size_categories:
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+ - 1K<n<10K
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  task_categories:
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+ - depth-estimation
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+ - image-to-image
 
 
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  tags:
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+ - dermatology
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+ - medical-imaging
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+ - 3d-reconstruction
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+ - synthetic-data
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+ - skin-lesion
 
 
 
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  ---
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  # D-Synth: Synthetic Dermoscopic Dataset with Pixel-Perfect 3D Information
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+ D-Synth is the first synthetic dermoscopic dataset providing pixel-perfect 3D ground truth (metric depth, surface normals, camera intrinsics) for monocular depth estimation in dermatology. It was introduced in [DermDepth: Toward Monocular Metric Scale 3D Reconstruction Models for Dermatology](https://huggingface.co/papers/2607.13010) (Carrión & Norouzi, MICCAI 2026).
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+
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+ [Project Page / GitHub](https://github.com/hectorcarrion/dermdepth) | [Paper](https://huggingface.co/papers/2607.13010)
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  ## Overview
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  - `generation_params.json` — full rendering parameters
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  - (subset) `render_rgb.png`, `render_depth.png`, `render_meta.json` — additional render variants
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+ ## Sample Usage
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+
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+ You can download the dataset locally using the Hugging Face CLI:
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+
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+ ```bash
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+ hf download hcarrion/D-Synth --repo-type dataset --local-dir data/dermdepth_train/dsynth
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+ ```
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+
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+ Or programmatically via Python:
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+
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+ ```python
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+ from huggingface_hub import snapshot_download
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+
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+ snapshot_download(
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+ repo_id='hcarrion/D-Synth',
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+ repo_type='dataset',
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+ local_dir='data/dermdepth_train/dsynth'
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+ )
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+ ```
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+
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  ## Generation pipeline
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  D-Synth extends [S-SYNTH](https://github.com/DIDSR/ssynth-release) (Kim et al., MICCAI 2024) with:
 
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  - **Code & training scripts**: https://github.com/hectorcarrion/dermdepth
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  - **Fine-tuned DermDepth checkpoints**: https://huggingface.co/hcarrion/DermDepth
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+ - **Base depth model**: https://huggingface.co/Ruicheng/moge-2-vitl-normal