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@@ -25,10 +25,18 @@ Keywords: Video Inpainting, Video Editing, Video Generation
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  <p align="center">
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- <a href='https://yxbian23.github.io/project/video-painter'><img src='https://img.shields.io/badge/Project-Page-Green'></a> <a href="https://arxiv.org/abs/2503.05639"><img src="https://img.shields.io/badge/arXiv-2503.05639-b31b1b.svg"></a> <a href="https://youtu.be/HYzNfsD3A0s"><img src="https://img.shields.io/badge/YouTube-Video-red?logo=youtube"></a> <a href="https://github.com/TencentARC/VideoPainter"><img src="https://img.shields.io/badge/GitHub-Code-black?logo=github"></a> <a href='https://huggingface.co/datasets/TencentARC/VPData'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Dataset-blue'></a> <a href='https://huggingface.co/datasets/TencentARC/VPBench'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Benchmark-blue'></a> <a href="https://huggingface.co/TencentARC/VideoPainter"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue"></a>
 
 
 
 
 
 
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  </p>
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- **Your like and star mean a lot for us to develop this project!** ❀️
 
 
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  **πŸ“– Table of Contents**
@@ -36,10 +44,15 @@ Keywords: Video Inpainting, Video Editing, Video Generation
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  - [VideoPainter](#videopainter)
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  - [πŸ”₯ Update Log](#-update-log)
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- - [TODO](#todo)
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  - [πŸ› οΈ Method Overview](#️-method-overview)
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  - [πŸš€ Getting Started](#-getting-started)
 
 
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  - [πŸƒπŸΌ Running Scripts](#-running-scripts)
 
 
 
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  - [🀝🏼 Cite Us](#-cite-us)
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  - [πŸ’– Acknowledgement](#-acknowledgement)
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@@ -48,11 +61,13 @@ Keywords: Video Inpainting, Video Editing, Video Generation
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  ## πŸ”₯ Update Log
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  - [2025/3/09] πŸ“’ πŸ“’ [VideoPainter](https://huggingface.co/TencentARC/VideoPainter) are released, an efficient, any-length video inpainting & editing framework with plug-and-play context control.
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  - [2025/3/09] πŸ“’ πŸ“’ [VPData](https://huggingface.co/datasets/TencentARC/VPData) and [VPBench](https://huggingface.co/datasets/TencentARC/VPBench) are released, the largest video inpainting dataset with precise segmentation masks and dense video captions (>390K clips).
 
 
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  ## TODO
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  - [x] Release trainig and inference code
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- - [x] Release evluation code
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  - [x] Release [VideoPainter checkpoints](https://huggingface.co/TencentARC/VideoPainter) (based on CogVideoX-5B)
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  - [x] Release [VPData and VPBench](https://huggingface.co/collections/TencentARC/videopainter-67cc49c6146a48a2ba93d159) for large-scale training and evaluation.
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  - [x] Release gradio demo
@@ -107,10 +122,7 @@ pip install -e .
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  </details>
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  <details>
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- <summary><b>Data Download ⬇️</b></summary>
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-
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-
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- **VPBench and VPData**
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  You can download the VPBench [here](https://huggingface.co/datasets/TencentARC/VPBench), and the VPData [here](https://huggingface.co/datasets/TencentARC/VPData) (as well as the Davis we re-processed), which are used for training and testing the BrushNet. By downloading the data, you are agreeing to the terms and conditions of the license. The data structure should be like:
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@@ -172,11 +184,16 @@ You can download the VPData (only mask and text annotations due to the space lim
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  git lfs install
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  git clone https://huggingface.co/datasets/TencentARC/VPData
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  mv VPBench data
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- cd data
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- unzip video_inpainting.zip
 
 
 
 
 
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  ```
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- Noted: *Due to the space limit, you need to run the following script to download the raw videos of the complete VPData. The format should be consistent with VPData/VPBench above (After download the VPData/VPBench, the script will automatically place the raw videos of VPData into the corresponding dataset directories that have been created by VPBench).*
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  ```
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  cd data_utils
@@ -216,6 +233,13 @@ git clone https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev
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  mv ckpt/FLUX.1-Fill-dev ckpt/flux_inp
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  ```
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  The ckpt structure should be like:
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@@ -237,6 +261,7 @@ The ckpt structure should be like:
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  |-- transformer
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  |-- vae
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  |-- ...
 
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  ```
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  </details>
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  <p align="center">
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+ <a href='https://yxbian23.github.io/project/video-painter'><img src='https://img.shields.io/badge/Project-Page-Green'></a> &nbsp;
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+ <a href="https://arxiv.org/abs/2503.05639"><img src="https://img.shields.io/badge/arXiv-2503.05639-b31b1b.svg"></a> &nbsp;
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+ <a href="https://github.com/TencentARC/VideoPainter"><img src="https://img.shields.io/badge/GitHub-Code-black?logo=github"></a> &nbsp;
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+ <a href="https://youtu.be/HYzNfsD3A0s"><img src="https://img.shields.io/badge/YouTube-Video-red?logo=youtube"></a> &nbsp;
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+ <a href='https://huggingface.co/datasets/TencentARC/VPData'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Dataset-blue'></a> &nbsp;
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+ <a href='https://huggingface.co/datasets/TencentARC/VPBench'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Benchmark-blue'></a> &nbsp;
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+ <a href="https://huggingface.co/TencentARC/VideoPainter"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue"></a>
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  </p>
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+ **Your star means a lot for us to develop this project!** ⭐⭐⭐
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+
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+ **VPData and VPBench have been fully uploaded (contain 390K mask sequences and video captions). Welcome to use our biggest video segmentation dataset VPData with video captions!** πŸ”₯πŸ”₯πŸ”₯
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  **πŸ“– Table of Contents**
 
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  - [VideoPainter](#videopainter)
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  - [πŸ”₯ Update Log](#-update-log)
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+ - [πŸ“Œ TODO](#todo)
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  - [πŸ› οΈ Method Overview](#️-method-overview)
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  - [πŸš€ Getting Started](#-getting-started)
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+ - [Environment Requirement 🌍](#environment-requirement-)
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+ - [Data Download ⬇️](#data-download-️)
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  - [πŸƒπŸΌ Running Scripts](#-running-scripts)
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+ - [Training 🀯](#training-)
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+ - [Inference πŸ“œ](#inference-)
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+ - [Evaluation πŸ“](#evaluation-)
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  - [🀝🏼 Cite Us](#-cite-us)
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  - [πŸ’– Acknowledgement](#-acknowledgement)
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61
  ## πŸ”₯ Update Log
62
  - [2025/3/09] πŸ“’ πŸ“’ [VideoPainter](https://huggingface.co/TencentARC/VideoPainter) are released, an efficient, any-length video inpainting & editing framework with plug-and-play context control.
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  - [2025/3/09] πŸ“’ πŸ“’ [VPData](https://huggingface.co/datasets/TencentARC/VPData) and [VPBench](https://huggingface.co/datasets/TencentARC/VPBench) are released, the largest video inpainting dataset with precise segmentation masks and dense video captions (>390K clips).
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+ - [2025/3/25] πŸ“’ πŸ“’ The 390K+ high-quality video segmentation masks of [VPData](https://huggingface.co/datasets/TencentARC/VPData) have been fully released.
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+ - [2025/3/25] πŸ“’ πŸ“’ The raw videos of videovo subset have been uploaded to [VPData](https://huggingface.co/datasets/TencentARC/VPData), to solve the raw video link expiration issue.
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  ## TODO
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  - [x] Release trainig and inference code
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+ - [x] Release evaluation code
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  - [x] Release [VideoPainter checkpoints](https://huggingface.co/TencentARC/VideoPainter) (based on CogVideoX-5B)
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  - [x] Release [VPData and VPBench](https://huggingface.co/collections/TencentARC/videopainter-67cc49c6146a48a2ba93d159) for large-scale training and evaluation.
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  - [x] Release gradio demo
 
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  </details>
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  <details>
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+ <summary><b>VPBench and VPData Download ⬇️</b></summary>
 
 
 
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  You can download the VPBench [here](https://huggingface.co/datasets/TencentARC/VPBench), and the VPData [here](https://huggingface.co/datasets/TencentARC/VPData) (as well as the Davis we re-processed), which are used for training and testing the BrushNet. By downloading the data, you are agreeing to the terms and conditions of the license. The data structure should be like:
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  git lfs install
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  git clone https://huggingface.co/datasets/TencentARC/VPData
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  mv VPBench data
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+
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+ # 1. unzip the masks in VPData
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+ python data_utils/unzip_folder.py --source_dir ./data/videovo_masks --target_dir ./data/video_inpainting/videovo
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+ python data_utils/unzip_folder.py --source_dir ./data/pexels_masks --target_dir ./data/video_inpainting/pexels
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+
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+ # 2. unzip the raw videos in Videovo subset in VPData
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+ python data_utils/unzip_folder.py --source_dir ./data/videovo_raw_videos --target_dir ./data/videovo/raw_video
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  ```
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+ Noted: *Due to the space limit, you need to run the following script to download the raw videos of the Pexels subset in VPData. The format should be consistent with VPData/VPBench above (After download the VPData/VPBench, the script will automatically place the raw videos of VPData into the corresponding dataset directories that have been created by VPBench).*
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  ```
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  cd data_utils
 
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  mv ckpt/FLUX.1-Fill-dev ckpt/flux_inp
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  ```
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+ [Optional]You need to download [SAM2](https://huggingface.co/facebook/sam2-hiera-large) for video segmentation in gradio demo:
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+ ```
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+ git lfs install
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+ cd ckpt
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+ wget https://huggingface.co/facebook/sam2-hiera-large/resolve/main/sam2_hiera_large.pt
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+ ```
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+ You can also choose the segmentation checkpoints of other sizes to balance efficiency and performance, such as [SAM2-Tiny](https://huggingface.co/facebook/sam2-hiera-tiny).
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  The ckpt structure should be like:
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  |-- transformer
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  |-- vae
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  |-- ...
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+ |-- sam2_hiera_large.pt
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  ```
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  </details>
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