jingheya
/

lotus-depth-g-v2-0-disparity

Depth Estimation

Diffusers

Safetensors

DirectDiffusionY0Pipeline

Model card Files Files and versions Community

jingheya commited on Nov 13

Commit

85d9eaa

•

1 Parent(s): 00dc43b

Update README.md

Browse files

Files changed (1) hide show

README.md +26 -192

README.md CHANGED Viewed

@@ -1,198 +1,32 @@
 ---
 library_name: diffusers
 ---
-# Model Card for Model ID
 <!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-[More Information Needed]
-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-[More Information Needed]
-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
-<!-- This should link to a Dataset Card if possible. -->
-[More Information Needed]
-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-[More Information Needed]
-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-[More Information Needed]
-### Results
-[More Information Needed]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
 library_name: diffusers
+license: apache-2.0
+pipeline_tag: depth-estimation
 ---
+# Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction
 <!-- Provide a quick summary of what the model is/does. -->
+This model belongs to the family of official Lotus models.
+[![Paper](https://img.shields.io/badge/Project-Website-pink?logo=googlechrome&logoColor=white)](https://lotus3d.github.io/)
+[![Paper](https://img.shields.io/badge/arXiv-Paper-b31b1b?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2409.18124)
+[![HuggingFace Demo](https://img.shields.io/badge/🤗%20HuggingFace-Demo-yellow)](https://huggingface.co/spaces/haodongli/Lotus)
+[![GitHub](https://img.shields.io/github/stars/EnVision-Research/Lotus?style=default&label=GitHub%20★&logo=github)](https://github.com/EnVision-Research/Lotus)
+Developed by:
+[Jing He](https://scholar.google.com/citations?hl=en&user=RsLS11MAAAAJ)<span style="color:red;">&#10033;</span>,
+[Haodong Li](https://haodong-li.com/)<span style="color:red;">&#10033;</span>,
+[Wei Yin](https://yvanyin.net/),
+[Yixun Liang](https://yixunliang.github.io/),
+[Leheng Li](https://len-li.github.io/),
+[Kaiqiang Zhou](),
+[Hongbo Zhang](),
+[Bingbing Liu](https://scholar.google.com/citations?user=-rCulKwAAAAJ&hl=en),
+[Ying-Cong Chen](https://www.yingcong.me/)&#9993;
+![teaser](assets/badges/teaser_1.jpg)
+![teaser](assets/badges/teaser_2.jpg)
+## Usage
+Please refer to this [page](https://github.com/EnVision-Research/Lotus).