Update README.md

README.md

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 <h1 align="center">Marigold Disparity v0.1 Model Card</h1>
 
-<!-- This model represents the internal test checkpoint of affine-invariant disparity version (train_marigold_affine_disparity_iter_24000). -->
+This model is the internal test checkpoint of affine-invariant disparity version 
+<!-- (train_marigold_affine_disparity_iter_24000). -->
 
 
 <p align="center">
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 <a title="arXiv" href="https://arxiv.org/abs/2505.09358" 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;">
+<!-- <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> -->
 <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>
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 This is a model card for the `marigold-disparity-affine-v0-1` 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 our papers, in inverse depth (disparity) space:
+described in our papers, in **inverse depth (disparity) space**:
 - [CVPR'2024 paper](https://hf.co/papers/2312.02145) titled "Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation"
 - [Journal extension](https://hf.co/papers/2505.09358) titled "Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis"
 
 ### Using the model
-- 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.
+- This model is for internal test.
 - 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.
+- **Developed by:** [Bingxin Ke](http://www.kebingxin.com/), [Anton Obukhov](https://www.obukhov.ai/), [Shengyu Huang](https://shengyuh.github.io/), [Nando Metzger](https://nandometzger.github.io/), [Rodrigo Caye Daudt](https://rcdaudt.github.io/), [Konrad Schindler](https://scholar.google.com/citations?user=FZuNgqIAAAAJ).
+- **Model type:** Generative latent diffusion-based affine-invariant disparity (inverse 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/2505.09358), [Code](https://github.com/prs-eth/marigold).
+- **License:** [Apache License License Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).
 - **Cite as:**
 
 ```bibtex