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| title: RelightVid | |
| emoji: 🎥 | |
| colorFrom: red | |
| colorTo: yellow | |
| sdk: gradio | |
| sdk_version: 5.23.3 | |
| app_file: app.py | |
| license: mit | |
| <!-- # <img src="assets/icon.png" style="vertical-align: -14px;" :height="50px" width="50px"> RelightVid --> | |
| # RelightVid | |
| **[RelightVid: Temporal-Consistent Diffusion Model for Video Relighting](https://arxiv.org/abs/2501.16330)** | |
| </br> | |
| [Ye Fang](https://github.com/Aleafy)\*, | |
| [Zeyi Sun](https://github.com/SunzeY)\*, | |
| [Shangzhan Zhang](https://zhanghe3z.github.io/), | |
| [Tong Wu](https://wutong16.github.io/), | |
| [Yinghao Xu](https://justimyhxu.github.io/), | |
| [Pan Zhang](https://panzhang0212.github.io/), | |
| [Jiaqi Wang](https://myownskyw7.github.io/), | |
| [Gordon Wetzstein](https://web.stanford.edu/~gordonwz/), | |
| [Dahua Lin](http://dahua.site/) | |
| <p style="font-size: 0.6em; margin-top: -1em">*Equal Contribution</p> | |
| <p align="center"> | |
| <a href="https://arxiv.org/abs/2501.16330"><img src="https://img.shields.io/badge/arXiv-Paper-<color>"></a> | |
| <a href="https://sunzey.github.io/Make-it-Real"><img src="https://img.shields.io/badge/Project-Website-red"></a> | |
| <a href="https://www.youtube.com/watch?v=_j-t8592GCM"><img src="https://img.shields.io/static/v1?label=Demo&message=Video&color=orange"></a> | |
| <a href="" target='_blank'> | |
| <img src="https://visitor-badge.laobi.icu/badge?page_id=Aleafy.RelightVid&left_color=gray&right_color=blue"> | |
| </a> | |
| </p> | |
|  | |
| ## 📜 News | |
| <!-- 🚀 [2024/6/8] We release our [inference pipeline of Make-it-Real](#⚡-quick-start), including material matching and generation of albedo-only 3D objects. | |
| 🚀 [2024/6/8] [Material library annotations](#📦-data-preparation) generated by GPT-4V and [data engine](#⚡-quick-start) are released! --> | |
| ✨ [2025/3/12] The [inference code](xxx), [project page](xxx) and [huggingface demo](xxx) are released! | |
| ✨ [2025/1/27] We release the [paper](https://arxiv.org/abs/2501.16330) of RelightVid! | |
| ## 💡 Highlights | |
| - 🔥 We first demonstrate that **GPT-4V** can effectively **recognize and describe materials**, allowing our model to precisely identifies and aligns materials with the corresponding components of 3D objects. | |
| - 🔥 We construct a **Material Library** containing thousands of materials with highly | |
| detailed descriptions readily for MLLMs to look up and assign. | |
| - 🔥 **An effective pipeline** for texture segmentation, material identification and matching, enabling the high-quality application of materials to | |
| 3D assets. | |
| ## 👨💻 Todo | |
| - [ ] Evaluation for Existed and Model-Generated Assets (both code & test assets) | |
| - [ ] More Interactive Demos (huggingface, jupyter) | |
| - [x] Make-it-Real Pipeline Inference Code | |
| - [x] Highly detailed Material Library annotations (generated by GPT-4V) | |
| - [x] Paper and Web Demos | |
| ## 💾 Installation | |
| ```bash | |
| git clone https://github.com/Aleafy/RelightVid.git | |
| cd RelightVid | |
| conda create -n relitv python=3.10 | |
| conda activate relitv | |
| pip install torch==2.1.2 torchvision==0.16.2 --index-url https://download.pytorch.org/whl/cu118 | |
| pip install -r requirements.txt | |
| ``` | |
| ## 📦 Data Preparation | |
| 1. **Annotations**: in `data/material_lib/annotations` [folder](data/material_lib/annotations), include: | |
| - Highly-detailed descriptions by GPT-4V: offering thorough descriptions of the material’s visual characteristics and rich semantic information. | |
| - Category-tree: Divided into a hierarchical structure with coarse and fine granularity, it includes over 80 subcategories. | |
| 2. **PBR Maps**: You can download the complete PBR data collection at [Huggingface](https://huggingface.co/datasets/gvecchio/MatSynth/tree/main), or download the data used in our project at [OpenXLab](https://openxlab.org.cn/datasets/YeFang/MatSynth/tree/main) (Recommended). (If you have any questions, please refer to [issue#5](https://github.com/Aleafy/Make_it_Real/issues/5)) | |
| 3. **Material Images(optinal)**: You can download the material images file [here](https://drive.google.com/file/d/1ob7CV6JiaqFyjuCzlmSnBuNRkzt2qMSG/view?usp=sharing), to check and visualize the material appearance. | |
| <pre> | |
| Make_it_Real | |
| └── data | |
| └── material_lib | |
| ├── annotations | |
| ├── mat_images | |
| └── pbr_maps | |
| └── train | |
| ├── Ceremic | |
| ├── Concrete | |
| ├── ... | |
| └── Wood | |
| </pre> | |
| ## ⚡ Quick Start | |
| #### Inference | |
| ```bash | |
| python main.py --obj_dir <object_dir> --exp_name <unique_exp_name> --api_key <your_own_gpt4_api_key> | |
| ``` | |
| - To ensure proper network connectivity for GPT-4V, add proxy environment settings in [main.py](https://github.com/Aleafy/Make_it_Real/blob/feb3563d57fbe18abbff8d4abfb48f71cc8f967b/main.py#L18) (optional). Also, please verify the reachability of your [API host](https://github.com/Aleafy/Make_it_Real/blob/feb3563d57fbe18abbff8d4abfb48f71cc8f967b/utils/gpt4_query.py#L68). | |
| - Result visualization (blender engine) is located in the `output/refine_output` dir. You can compare the result with that in `output/ori_output`. | |
| #### Annotation Engine | |
| ```bash | |
| cd scripts/gpt_anno | |
| python gpt4_query_mat.py | |
| ``` | |
| `Note`: Besides functinoning as annotation engine, you can also use this code ([gpt4_query_mat.py](https://github.com/Aleafy/Make_it_Real/blob/main/scripts/gpt_anno/gpt4_query_mat.py)) to test the GPT-4V connection simply. | |
| <!-- [annotation code](scripts/gpt_anno) --> | |
| <!-- #### Evalutation --> | |
| ## ❤️ Acknowledgments | |
| - [MatSynth](https://huggingface.co/datasets/gvecchio/MatSynth/tree/main): a Physically Based Rendering (PBR) materials dataset, which offers extensive high-resolusion tilable pbr maps to look up. | |
| - [TEXTure](https://github.com/TEXTurePaper/TEXTurePaper): Wonderful text-guided texture generation model, and the codebase we built upon. | |
| - [SoM](https://som-gpt4v.github.io/): Draw visual cues on images to facilate GPT-4V query better. | |
| - [Material Palette](https://github.com/astra-vision/MaterialPalette): Excellent exploration of material extraction and generation, offers good insights and comparable setting. | |
| ## ✒️ Citation | |
| If you find our work helpful for your research, please consider giving a star ⭐ and citation 📝 | |
| ```bibtex | |
| @misc{fang2024makeitreal, | |
| title={Make-it-Real: Unleashing Large Multimodal Model for Painting 3D Objects with Realistic Materials}, | |
| author={Ye Fang and Zeyi Sun and Tong Wu and Jiaqi Wang and Ziwei Liu and Gordon Wetzstein and Dahua Lin}, | |
| year={2024}, | |
| eprint={2404.16829}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CV} | |
| } | |
| ``` | |