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README.md

@@ -9,214 +9,4 @@ app_file: app.py
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 license: apache-2.0
 short_description: Unified Video Editing with Temporal Reasoner
----
-
-<div align="center">
-
-  <h1 style="margin: 0; font-size: 2.4em;">
-    Unified Video Editing with Temporal Reasoner
-  </h1>
-
-  <h4 style="margin: 15px 0; color: #2c3e50;">
-    👁️ See &rarr; 🧠 Reason &rarr; ✏️ Edit
-  </h4>
-
-  <h4 style="margin: 15px 0; color: #2c3e50;">
-    🚀 A Chain of Frames video editing method enbale temporal reasoning and 4x video length extrapolation with just 50k training pairs!
-  </h4>
-
-  [![Hugging Face Daily Paper](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Daily%20Paper-yellow)](https://huggingface.co/papers/2512.07469)
-  [![arXiv](https://img.shields.io/badge/arXiv-2512.07469-b31b1b.svg)](https://arxiv.org/abs/2512.07469)
-  [![Project Page](https://img.shields.io/badge/Project-Page-green)](https://videocof.github.io)
-  [![Hugging Face Model](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-yellow)](https://huggingface.co/XiangpengYang/VideoCoF)
-  ![visitors](https://visitor-badge.laobi.icu/badge?page_id=videocof.VideoCoF&left_color=green&right_color=red)
-
-</div>
-
-<div align="center">
-  <b>
-    <a href="https://scholar.google.com/citations?user=reiIeYMAAAAJ">Xiangpeng Yang</a><sup>1</sup>,
-    <a href="https://horizonwind2004.github.io/">Ji Xie</a><sup>2</sup>,
-    <a href="https://scholar.google.com/citations?user=OvfI_HMAAAAJ">Yiyuan Yang</a><sup>1</sup>,
-    <a href="https://scholar.google.com/citations?user=zfeWd6gAAAAJ">Yan Huang</a><sup>1</sup>,
-    <a href="https://scholar.google.com/citations?user=sCuACdkAAAAJ">Min Xu</a><sup>1</sup>,
-    <a href="https://scholar.google.com/citations?user=sCuACdkAAAAJ">Qiang Wu</a><sup>1</sup>
-  </b>
-  <br>
-  <span style="font-size: 1em; color: #555;"><sup>1</sup>University of Technology Sydney, <sup>2</sup>Zhejiang University</span>
-</div>
-
-<br>
-
-## 💿 Introduction
-
-https://github.com/user-attachments/assets/26f7d347-3d6c-43cf-9645-6eb5906f6ad6
-
-## 🔥 News
-
-- **2025.12.09**: Paper available on arXiv.
-- **2025.12.08**: Release the inference code and videocof-50k weight.
-- **2025.12.06**: 🔥 Project Page and README updated!
-
-
-## 📑 Table of Contents
-
-- [🔧 Quick Start](#-quick-start)
-- [🏆 Model Zoo](#-model-zoo)
-- [🍭 Results](#-results)
-- [🎨 Edit Comparison](#-edit-comparison)
-- [🚧 TODO](#-todo)
-- [🙏 Acknowledgments](#-acknowledgments)
-- [📜 License](#-license)
-- [📮 Contact](#-contact)
-- [📄 Citation](#-citation)
-
-## 🔧 Quick Start
-
-1.  **Clone the repository:**
-
-    ```bash
-    git clone https://github.com/videocof/VideoCoF.git
-    cd VideoCoF
-    ```
-
-2.  **Install dependencies:**
-
-    ```bash
-    # 1. Create and activate a conda environment
-    conda create -n videocof python=3.10
-    conda activate videocof
-
-    # 2. Install PyTorch (Choose version compatible with your CUDA)
-    # For standard GPUs (CUDA 12.1):
-    pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/cu121
-    
-    # For Hopper GPUs (e.g., H100/H800) requiring fast inference:
-    # pip install torch==2.8.0 torchvision==0.23.0 torchaudio==2.8.0 --index-url https://download.pytorch.org/whl/cu128
-    
-    # 3. Install other dependencies
-    pip install -r requirements.txt
-    ```
-
-    **Note on Flash Attention:**
-    We recommend using **FlashAttention-3** (currently beta) for optimal performance, especially on NVIDIA H100/H800 GPUs. 
-    If you are using these GPUs, please follow the [official FlashAttention-3 installation guide](https://github.com/Dao-AILab/flash-attention?tab=readme-ov-file#flashattention-3-beta-release) after installing the compatible PyTorch version (e.g., PyTorch 2.8 + CUDA 12.8).
-
-
-3.  **Download Models:**
-
-    **Wan-2.1-T2V-14B Pretrained Weights:**
-        
-        ```bash
-        git lfs install
-        git clone https://huggingface.co/Wan-AI/Wan2.1-T2V-14B
-        
-        # Or using huggingface-cli:
-        # hf download Wan-AI/Wan2.1-T2V-14B --local-dir Wan2.1-T2V-14B
-        ```
-
-    **VideoCoF Checkpoint:**
-        
-        ```bash
-        git lfs install
-        git clone https://huggingface.co/XiangpengYang/VideoCoF videocof_weight
-
-        # Or using huggingface-cli:
-        # hf download XiangpengYang/VideoCoF --local-dir videocof_weight
-        ```
-
-4.  **Inference:**
-
-    For single inference tasks:
-
-    ```bash
-    # Object Removal
-    sh scripts/obj_rem.sh
-
-    # Object Addition
-    sh scripts/obj_add.sh
-
-    # Local Style Transfer
-    sh scripts/local_style.sh
-    ```
-
-    For parallel inference:
-
-    ```bash
-    sh scripts/parallel_infer.sh
-    ```
-
-## 🏆 Model Zoo
-
-Our models are available on Hugging Face:
-
-| Model Name | Description | Link |
-|------------|-------------|------|
-| VideoCoF-Base | Base model trained on 50k video pairs | [Hugging Face](https://huggingface.co/XiangpengYang/VideoCoF) |
-
-## 🍭 Results
-
-### Why We Need Reasoning Before Editing?
-![](assets/motivation_v2.gif)
-
-Current video editing methods typically follow two paths:
-1.  **Expert models**: Rely on external masks for precision but sacrifice unification.
-2.  **Unified in-context learning models**: Mask-free but often struggle with spatial accuracy due to the lack of explicit cues.
-
-**VideoCoF** bridges this gap by predicting reasoning tokens before generating the target video tokens.
-
-### Key Capabilities
-
-1.  **Seeing, Reasoning, Editing**: VideoCoF adopts a "seeing, reasoning, editing" approach, ensuring edits are applied accurately to the intended targets.
-2.  **Length Extrapolation**: Trained on only **50k** data (33 frames), VideoCoF demonstrates robust multi-shot editing and length generalization (e.g., 4&times; length extrapolation).
-3.  **Diverse Editing Tasks**: Supports fine-grained (instance and part level, spatial aware) Object Removal, Object Addition, Object Swap, and Local Style Transfer.
-
-### Gallery Highlights
-
-> Please refer to our [Project Page](https://videocof.github.io) for the full gallery.
-
-*   **Object Removal**: Remove people or objects based on text prompts.
-*   **Object Addition**: Add elements like animals, objects, or people.
-*   **Object Swap**: Change specific attributes or objects.
-*   **Local Style Transfer**: Modify texture, materials or colors.
-
-## 🚧 TODO
-
-- [x] Release paper.
-- [x] Release inference code and weights.
-- [ ] Release training code.
-- [ ] Release training data.
-- [ ] Add Hugging Face demo.
-
-## 🙏 Acknowledgments
-
-We thank the authors of related works and the open-source community [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun) and [Wan](https://github.com/Wan-Video/Wan2.1) for their contributions.
-
-## 📜 License
-
-This project is licensed under the [Apache License 2.0](LICENSE).
-
-## 📮 Contact
-
-For any questions, please feel free to reach out to the author Xiangpeng Yang [@knightyxp](https://github.com/knightyxp), email: knightyxp@gmail.com/Xiangpeng.Yang@student.uts.edu.au
-
-## 📄 Citation
-
-If you find this work useful for your research, please consider citing:
-
-```bibtex
-@article{yang2025videocof,
-  title={Unified Video Editing with Temporal Reasoner},
-  author={Yang, Xiangpeng and Xie, Ji and Yang, Yiyuan and Huang, Yan and Xu, Min and Wu, Qiang},
-  journal={arXiv preprint arXiv:2512.07469},
-  year={2025}
-}
-```
-
-<div align="center">
-  ⭐ **If you find this project helpful, please consider giving it a star!** ⭐
-</div>
-
-## ⭐️ Star History
-
-[![Star History Chart](https://api.star-history.com/svg?repos=knightyxp/VideoCoF&type=Date&legend=top-left)](https://star-history.com/#knightyxp/VideoCoF&Date)
+---