Update README.md

README.md

@@ -1,198 +1,46 @@
----
-library_name: diffusers
----
+# [SV3D-diffusers](https://github.com/chenguolin/sv3d-diffusers)
 
-# Model Card for Model ID
+![](assets/sv3doutputs.gif)
 
-<!-- Provide a quick summary of what the model is/does. -->
+This repo (https://github.com/chenguolin/sv3d-diffusers) provides scripts about:
 
+1. Spatio-temporal UNet (`SV3DUNetSpatioTemporalConditionModel`) and pipeline (`StableVideo3DDiffusionPipeline`) modified from [SVD](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_video_diffusion/pipeline_stable_video_diffusion.py) for [SV3D](https://sv3d.github.io) in the [diffusers](https://github.com/huggingface/diffusers) convention.
 
+2. Converting the [Stability-AI](https://github.com/Stability-AI/generative-models)'s [SV3D-p UNet checkpoint](https://huggingface.co/stabilityai/sv3d) to the [diffusers](https://github.com/huggingface/diffusers) convention.
 
-## Model Details
+3. Infering the `SV3D-p` model with the [diffusers](https://github.com/huggingface/diffusers) library to synthesize a 21-frame orbital video around a 3D object from a single-view image (preprocessed by removing background and centering first).
 
-### Model Description
+Converted SV3D-p checkpoints have been uploaded to HuggingFace🤗 [chenguolin/sv3d-diffusers](https://huggingface.co/chenguolin/sv3d-diffusers).
 
-<!-- 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.
+## 🚀 Usage
+```bash
+git clone https://github.com/chenguolin/sv3d-diffusers.git
+# Please install PyTorch first according to your CUDA version
+pip3 install -r requirements.txt
+# If you can't access to HuggingFace🤗, try:
+# export HF_ENDPOINT=https://hf-mirror.com
+python3 infer.py --output_dir out/ --image_path assets/images/sculpture.png --elevation 10 --half_precision --seed -1
+```
+The synthesized video will save at `out/` as a `.gif` file.
 
-- **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]
+## 📸 Results
+> Image preprocessing and random seed for different implementations are different, so the results are presented only for reference.
 
-<!-- Provide the basic links for the model. -->
+| Implementation | sculpture |  bag   | kunkun |
+| :------------- | :------:  | :----: | :----: |
+| **SV3D-diffusers (Ours)** | ![](assets/sculpture.gif) | ![](assets/bag.gif) | ![](assets/kunkun.gif) |
+| **Official SV3D**  | ![](assets/sculpture_official.gif) | ![](assets/bag_official.gif) | ![](assets/kunkun_official.gif) |
 
-- **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]
+## 📚 Citation
+If you find this repo helpful, please consider giving this repository a star 🌟 and citing the original SV3D paper.
+```
+@inproceedings{voleti2024sv3d,
+   author={Voleti, Vikram and Yao, Chun-Han and Boss, Mark and Letts, Adam and Pankratz, David and Tochilkin,  Dmitrii and Laforte, Christian and Rombach, Robin and Jampani, Varun},
+   title={{SV3D}: Novel Multi-view Synthesis and {3D} Generation from a Single Image using Latent Video Diffusion},
+   booktitle={European Conference on Computer Vision (ECCV)},
+   year={2024},
+}
+```