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README.md

@@ -1,13 +1,417 @@
+# DragAnything
+
+### <div align="center"> DragAnything: Motion Control for Anything using Entity Representation <div> 
+
+<div align="center">
+  <a href="https://weijiawu.github.io/draganything_page/"><img src="https://img.shields.io/static/v1?label=Project%20Page&message=Github&color=blue&logo=github-pages"></a> &ensp;
+  <a href="https://arxiv.org/abs/2403.07420/"><img src="https://img.shields.io/static/v1?label=Paper&message=Arxiv&color=red&logo=arxiv"></a> &ensp;
+</div>
+
+<p align="center">
+<img src="./assets/1709656085862.jpg" width="800px"/>  
+<br>
+</p>
+
+
+## :notes: **Updates**
+
+<!--- [ ] Mar. 13, 2024. Release the train code in **three month**.-->
+- [x] Mar. 24, 2024. Support interactive demo with gradio.
+- [x] Mar. 13, 2024. Release the inference code.
+- [x] Mar. 12, 2024. Rep initialization.
+
+
 ---
-title: Dragreal
-emoji: 🐠
-colorFrom: indigo
-colorTo: blue
-sdk: gradio
-sdk_version: 4.23.0
-app_file: app.py
-pinned: false
-license: mit
+
+## 🐱 Abstract
+We introduce DragAnything, which utilizes an entity representation to achieve motion control for any object in controllable video generation. Comparison to existing motion control methods, DragAnything offers several advantages. Firstly, trajectory-based is more user-friendly for interaction, when acquiring other guidance signals (\eg{} masks, depth maps) is labor-intensive. Users only need to draw a line~(trajectory) during interaction. Secondly, our entity representation serves as an open-domain embedding capable of representing any object, enabling the control of motion for diverse entities, including background. Lastly, our entity representation allows simultaneous and distinct motion control for multiple objects. Extensive experiments demonstrate that our DragAnything achieves state-of-the-art performance for FVD, FID, and User Study, particularly in terms of object motion control, where our method surpasses the previous state of the art (DragNUWA) by 26% in human voting.
+
 ---
+## User-Trajectory Interaction with SAM
+<table class="center">
+<tr>
+      <td style="text-align:center;"><b>Input Image</b></td>
+  <td style="text-align:center;"><b>Drag point with SAM</b></td>
+    <td style="text-align:center;"><b>2D Gaussian Trajectory</b></td>
+      <td style="text-align:center;"><b>Generated Video</b></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709660422197.jpg" width="177" height="100"></td>
+  <td><img src="./assets/1709660459944.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image28 (3).gif" width="177" height="100"></td>              
+  <td><img src="./assets/image28 (2).gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709660422197.jpg" width="177" height="100"></td>
+  <td><img src="./assets/1709660471568.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image2711.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image27 (1)1.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709660422197.jpg" width="177" height="100"></td>
+  <td><img src="./assets/1709660965701.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image29111.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image29 (1)1.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709660422197.jpg" width="177" height="100"></td>
+  <td><img src="./assets/1709661150250.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image30 (1)1.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image3011.gif" width="177" height="100"></td>
+</tr>
+
+</table>
+
+
+## Comparison with DragNUWA
+<table class="center">
+<tr>
+      <td style="text-align:center;"><b>Model</b></td>
+  <td style="text-align:center;"><b>Input Image and Drag</b></td>
+    <td style="text-align:center;"><b>Generated Video</b></td>
+      <td style="text-align:center;"><b>Visualization for Pixel Motion</b></td>
+</tr>
+<tr>
+  <td style="text-align:center;"><b>DragNUWA</b></td>
+  <td><img src="./assets/1709661872632.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image63111.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image6411.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td style="text-align:center;"><b>Ours</b></td>
+  <td><img src="./assets/1709662077471.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image65111.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image6611.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td style="text-align:center;"><b>DragNUWA</b></td>
+  <td><img src="./assets/1709662293661.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image77.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image76.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td style="text-align:center;"><b>Ours</b></td>
+  <td><img src="./assets/1709662429867.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image75.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image74.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td style="text-align:center;"><b>DragNUWA</b></td>
+  <td><img src="./assets/1709662596207.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image84.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image85.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td style="text-align:center;"><b>Ours</b></td>
+  <td><img src="./assets/1709662724643.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image87.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image88.gif" width="177" height="100"></td>
+</tr>
+
+
+
+</table>
+
+
+
+## More Demo
+
+
+<table class="center">
+<tr>
+  <td style="text-align:center;"><b>Drag point with SAM</b></td>
+  <td style="text-align:center;"><b>2D Gaussian</b></td>
+    <td style="text-align:center;"><b>Generated Video</b></td>
+      <td style="text-align:center;"><b>Visualization for Pixel Motion</b></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709656550343.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image188.gif" width="177" height="100"></td>
+  <td><img src="./assets/image190.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image189.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709657635807.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image187 (1).gif" width="177" height="100"></td>
+  <td><img src="./assets/image186.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image185.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709658516913.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image158.gif" width="177" height="100"></td>
+  <td><img src="./assets/image159.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image160.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709658781935.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image163.gif" width="177" height="100"></td>
+  <td><img src="./assets/image161.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image162.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709659276722.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image165.gif" width="177" height="100"></td>
+  <td><img src="./assets/image167.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image166.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709659787625.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image172.gif" width="177" height="100"></td>
+  <td><img src="./assets/Our_Motorbike_cloud_floor.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image171.gif" width="177" height="100"></td>
+</tr>
+
+
+</table>
+
+
+##  Various Motion Control 
+<table class="center">
+<tr>
+  <td style="text-align:center;"><b>Drag point with SAM</b></td>
+  <td style="text-align:center;"><b>2D Gaussian</b></td>
+    <td style="text-align:center;"><b>Generated Video</b></td>
+      <td style="text-align:center;"><b>Visualization for Pixel Motion</b></td>
+</tr>
+
+<tr>
+  <td><img src="./assets/1709663429471.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image265.gif" width="177" height="100"></td>
+  <td><img src="./assets/image265 (1).gif" width="177" height="100"></td>              
+  <td><img src="./assets/image268.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709663831581.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image274.gif" width="177" height="100"></td>
+  <td><img src="./assets/image274 (1).gif" width="177" height="100"></td>              
+  <td><img src="./assets/image276.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td style="text-align:center;" colspan="4"><b>(a) Motion Control for Foreground</b></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709664593048.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image270.gif" width="177" height="100"></td>
+  <td><img src="./assets/image270 (1).gif" width="177" height="100"></td>              
+  <td><img src="./assets/image269.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709664834397.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image271.gif" width="177" height="100"></td>
+  <td><img src="./assets/image271 (1).gif" width="177" height="100"></td>              
+  <td><img src="./assets/image272.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td style="text-align:center;" colspan="4"><b>(b) Motion Control for Background</b></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709665073460.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image279.gif" width="177" height="100"></td>
+  <td><img src="./assets/image278.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image277.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709665252573.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image282.gif" width="177" height="100"></td>
+  <td><img src="./assets/image280.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image281.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td style="text-align:center;" colspan="4"><b>(c) Simultaneous Motion Control for Foreground  and Background
+</b></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709665505339.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image283.gif" width="177" height="100"></td>
+  <td><img src="./assets/image283 (1).gif" width="177" height="100"></td>              
+  <td><img src="./assets/image285.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709666205795.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image286.gif" width="177" height="100"></td>
+  <td><img src="./assets/image288.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image287.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709666401284.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image289.gif" width="177" height="100"></td>
+  <td><img src="./assets/image290.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image291.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td><img src="./assets/1709666772216.jpg" width="177" height="100"></td>
+  <td><img src="./assets/image294.gif" width="177" height="100"></td>
+  <td><img src="./assets/image293.gif" width="177" height="100"></td>              
+  <td><img src="./assets/image292.gif" width="177" height="100"></td>
+</tr>
+<tr>
+  <td style="text-align:center;" colspan="4"><b>(d) Motion Control for Camera Motion
+</b></td>
+</tr>
+
+</table>
+
+## 🔧 Dependencies and Dataset Prepare
+
+### Dependencies
+- Python >= 3.10 (Recommend to use [Anaconda](https://www.anaconda.com/download/#linux) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html))
+- [PyTorch >= 1.13.0+cu11.7](https://pytorch.org/)
+
+```Shell
+git clone https://github.com/Showlab/DragAnything.git
+cd DragAnything
+
+conda create -n DragAnything python=3.8
+conda activate DragAnything
+pip install -r environment.txt
+```
+
+### Dataset Prepare
+
+Download [VIPSeg](https://github.com/VIPSeg-Dataset/VIPSeg-Dataset) and [Youtube-VOS](https://youtube-vos.org/) to the ```./data``` directory.
+
+### Motion Trajectory Annotataion Prepare
+You can use our preprocessed annotation files or choose to process your own motion trajectory annotation files using [Co-Track](https://github.com/facebookresearch/co-tracker?tab=readme-ov-file#installation-instructions).
+
+
+If you choose to generate motion trajectory annotations yourself, you need to follow the processing steps outlined in [Co-Track](https://github.com/facebookresearch/co-tracker?tab=readme-ov-file#installation-instructions).
+
+```Shell
+cd ./utils/co-tracker
+pip install -e .
+pip install matplotlib flow_vis tqdm tensorboard
+
+mkdir -p checkpoints
+cd checkpoints
+wget https://huggingface.co/facebook/cotracker/resolve/main/cotracker2.pth
+cd ..
+
+```
+Then, modify the corresponding ```video_path```, ```ann_path```, and ```save_path``` in the ```Generate_Trajectory_for_VIPSeg.sh``` file, and run the command. The corresponding trajectory annotations will be saved as .json files in the save_path directory.
+
+```Shell
+Generate_Trajectory_for_VIPSeg.sh
+
+```
+
+### Trajectory visualization
+You can run the following command for visualization.
+
+```Shell
+cd .utils/
+python vis_trajectory.py
+```
+
+### Pretrained Model Preparation
+
+We adopt the [ChilloutMix](https://civitai.com/models/6424/chilloutmix) as pretrained model for extraction of entity representation, please download the diffusers version:
+
+```bash 
+mkdir -p utils/pretrained_models
+cd utils/pretrained_models
+
+# Diffusers-version ChilloutMix to utils/pretrained_models
+git-lfs clone https://huggingface.co/windwhinny/chilloutmix.git
+```
+
+And you can download our pretrained model for the controlnet:
+```bash 
+mkdir -p model_out/DragAnything
+cd model_out/DragAnything
+
+# Diffusers-version DragAnything to model_out/DragAnything
+git-lfs clone https://huggingface.co/weijiawu/DragAnything
+```
+
+
+
+## :paintbrush: Train(Awaiting release) <!-- omit in toc -->
+
+### 1) Semantic Embedding Extraction
+
+```Shell
+cd .utils/
+python extract_semantic_point.py
+```
+
+### 2) Train DragAnything
+
+For VIPSeg
+```Shell
+sh ./script/train_VIPSeg.sh
+```
+
+For YouTube VOS
+```Shell
+sh ./script/train_youtube_vos.sh
+```
+
+## :paintbrush: Evaluation <!-- omit in toc -->
+
+### Evaluation for [FID](https://github.com/mseitzer/pytorch-fid)
+
+```Shell
+cd utils
+sh Evaluation_FID.sh
+```
+
+### Evaluation for [Fréchet Video Distance (FVD)](https://github.com/hyenal/relate/blob/main/extras/README.md)
+
+```Shell
+cd utils/Eval_FVD
+sh compute_fvd.sh
+```
+
+### Evaluation for Eval_ObjMC
+
+```Shell
+cd utils/Eval_ObjMC
+python ./ObjMC.py
+```
+
+
+
+## :paintbrush: Inference for single video <!-- omit in toc -->
+
+
+```Shell
+python demo.py
+```
+
+or run the interactive inference with gradio (install the ```gradio==3.50.2```).
+```Shell
+cd ./script
+```
+download the weight of ```sam_vit_h_4b8939.pth``` from [SAM](https://github.com/facebookresearch/segment-anything?tab=readme-ov-file#model-checkpoints)
+
+```Shell
+python gradio_run.py
+```
+
+
+### :paintbrush: Visulization of pixel motion for the generated video <!-- omit in toc -->
+
+```Shell
+cd utils/co-tracker
+python demo.py
+```
+
+
+
+## 📖BibTeX
+    @misc{wu2024draganything,
+          title={DragAnything: Motion Control for Anything using Entity Representation}, 
+          author={Weijia Wu, Zhuang Li, Yuchao Gu, Rui Zhao, Yefei He, David Junhao Zhang, Mike Zheng Shou, Yan Li, Tingting Gao, Di Zhang},
+          year={2024},
+          eprint={2403.07420},
+          archivePrefix={arXiv},
+          primaryClass={cs.CV}
+    }
+    
+    
+## 🤗Acknowledgements
+- Thanks to [Diffusers](https://github.com/huggingface/diffusers) for the wonderful work and codebase.
+- Thanks to [svd-temporal-controlnet](https://github.com/CiaraStrawberry/svd-temporal-controlnet) for the wonderful work and codebase.
+- Thanks to chaojie for building [ComfyUI-DragAnything](https://github.com/chaojie/ComfyUI-DragAnything).
+
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference