update model cards

README.md

@@ -1,6 +1,74 @@
 ---
-license: openrail
+license: openrail++
+language:
+- en
+pipeline_tag: depth-estimation
+pinned: true
+tags:
+- depth estimation
+- image analysis
+- computer vision
+- in-the-wild
+- zero-shot
 ---
 
+<h1 align="center">Marigold Depth v1-1 Model Card</h1>
 
-<!-- Checkpoint:  train_marigold_0snr/checkpoint/iter_020000 -->
+<p align="center">
+<a title="Image Depth" href="https://huggingface.co/spaces/prs-eth/marigold" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/badge/%F0%9F%A4%97%20Image%20Depth%20-Demo-yellow" alt="Image Depth">
+</a>
+<a title="diffusers" href="https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/badge/%F0%9F%A4%97%20diffusers%20-Integration%20🧨-yellow" alt="diffusers">
+</a>
+<a title="Github" href="https://github.com/prs-eth/marigold" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/github/stars/prs-eth/marigold?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="Github">
+</a>
+<a title="Website" href="https://marigoldcomputervision.github.io/" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/badge/%E2%99%A5%20Project%20-Website-blue" alt="Website">
+</a>
+<a title="arXiv" href="https://arxiv.org/abs/2312.02145" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/badge/%F0%9F%93%84%20Read%20-Paper-AF3436" alt="arXiv">
+</a>
+<a title="Social" href="https://twitter.com/antonobukhov1" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/twitter/follow/:?label=Subscribe%20for%20updates!" alt="Social">
+</a>
+<a title="License" href="https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/badge/License-OpenRAIL++-929292" alt="License">
+</a>
+</p>
+
+This is a model card for the `marigold-depth-v1-1` model for monocular depth estimation from a single image. 
+The model is fine-tuned from the `stable-diffusion-2` [model](https://huggingface.co/stabilityai/stable-diffusion-2) as 
+described in 
+<span style="color:red;">a follow-up of our [CVPR'2024 paper](https://arxiv.org/abs/2312.02145) titled "Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation".</span>
+
+- Play with the interactive [Hugging Face Spaces demo](https://huggingface.co/spaces/prs-eth/marigold): check out how the model works with example images or upload your own.
+- Use it with [diffusers](https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage) to compute the results with a few lines of code.
+- Get to the bottom of things with our [official codebase](https://github.com/prs-eth/marigold).
+
+## Model Details
+- **Developed by:** [Bingxin Ke](http://www.kebingxin.com/), [Kevin Qu](https://ch.linkedin.com/in/kevin-qu-b3417621b), [Tianfu Wang](https://tianfwang.github.io/), [Nando Metzger](https://nandometzger.github.io/), [Shengyu Huang](https://shengyuh.github.io/), [Bo Li](https://www.linkedin.com/in/bobboli0202), [Anton Obukhov](https://www.obukhov.ai/), [Konrad Schindler](https://scholar.google.com/citations?user=FZuNgqIAAAAJ).
+- **Model type:** Generative latent diffusion-based affine-invariant monocular depth estimation from a single image.
+- **Language:** English.
+- **License:** [CreativeML Open RAIL++-M License](https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL).
+- **Model Description:** This model can be used to generate an estimated depth map of an input image. 
+  - **Resolution**: Even though any resolution can be processed, the model inherits the base diffusion model's effective resolution of roughly **768** pixels. 
+    This means that for optimal predictions, any larger input image should be resized to make the longer side 768 pixels before feeding it into the model.
+  - **Steps and scheduler**: This model was designed for usage with the **DDIM** scheduler and between **1 and 50** denoising steps.
+  - **Outputs**:
+    - **Affine-invariant depth map**: The predicted values are between 0 and 1, interpolating between the near and far planes of the model's choice.
+    - **Uncertainty map**: Produced only when multiple predictions are ensembled with ensemble size larger than 2.
+- **Resources for more information:** [Project Website](https://marigoldcomputervision.github.io/), [Paper](https://arxiv.org/abs/2312.02145), [Code](https://github.com/prs-eth/marigold).
+- **Cite as:**
+
+<span style="color:red;">Placeholder for the citation block of the follow-up paper</span>
+
+```bibtex
+@InProceedings{ke2023repurposing,
+      title={Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation},
+      author={Bingxin Ke and Anton Obukhov and Shengyu Huang and Nando Metzger and Rodrigo Caye Daudt and Konrad Schindler},
+      booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+      year={2024}
+}
+```