Add application file

README.md

@@ -1,106 +1,15 @@
-<div align="center">
-    <h1>
-    STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution
-    </h1>
-    <div>
-        <a href='https://github.com/CSRuiXie' target='_blank'>Rui Xie<sup>1*</sup></a>,&emsp;
-        <a href='https://github.com/yhliu04' target='_blank'>Yinhong Liu<sup>1*</sup></a>,&emsp;
-        <a href='https://scholar.google.com/citations?user=Uhp3JKgAAAAJ&hl=zh-CN&oi=sra' target='_blank'>Chen Zhao<sup>1</sup></a>,&emsp;
-        <a href='https://scholar.google.com/citations?hl=zh-CN&user=yWq1Fd4AAAAJ' target='_blank'>Penghao Zhou<sup>2</sup></a>,&emsp;
-        <a href='https://scholar.google.com/citations?hl=zh-CN&user=Ds5wwRoAAAAJ' target='_blank'>Zhenheng Yang<sup>2</sup></a><br>
-        <a href='https://scholar.google.com/citations?hl=zh-CN&user=w03CHFwAAAAJ' target='_blank'>Jun Zhou<sup>3</sup></a>,&emsp;
-        <a href='https://cszn.github.io/' target='_blank'>Kai Zhang<sup>1</sup></a>,&emsp;
-        <a href='https://jessezhang92.github.io/' target='_blank'>Zhenyu Zhang<sup>1</sup></a>,&emsp;
-        <a href='https://scholar.google.com.hk/citations?user=6CIDtZQAAAAJ&hl=zh-CN' target='_blank'>Jian Yang<sup>1</sup></a>,&emsp;
-        <a href='https://tyshiwo.github.io/index.html' target='_blank'>Ying Tai<sup>1&#8224</sup></a>
-    </div>
-    <div>
-        <sup>1</sup>Nanjing University,&emsp;<sup>2</sup>ByteDance,&emsp; <sup>3</sup>Southwest University
-    </div>
-    <div>
-        <h4 align="center">
-            <a href="https://nju-pcalab.github.io/projects/STAR" target='_blank'>
-                <img src="https://img.shields.io/badge/🌟-Project%20Page-blue">
-            </a>
-            <a href="https://arxiv.org/abs/2407.07667" target='_blank'>
-                <img src="https://img.shields.io/badge/arXiv-2312.06640-b31b1b.svg">
-            </a>
-            <a href="https://youtu.be/hx0zrql-SrU" target='_blank'>
-                <img src="https://img.shields.io/badge/Demo%20Video-%23FF0000.svg?logo=YouTube&logoColor=white">
-            </a>
-        </h4>
-    </div>
-</div>
-
-
-### 🔆 Updates
-- **2024.12.01**  The pretrained STAR model (I2VGen-XL version) and inference code have been released.
-
-
-## 🔎 Method Overview
-![STAR](assets/overview.png)
-
-
-## 📷 Results Display
-![STAR](assets/teaser.png)
-![STAR](assets/real_world.png)
-👀 More visual results can be found in our [Project Page](https://nju-pcalab.github.io/projects/STAR) and [Video Demo](https://youtu.be/hx0zrql-SrU).
-
-
-## ⚙️ Dependencies and Installation
-```
-## git clone this repository
-git clone https://github.com/NJU-PCALab/STAR.git
-cd STAR
-
-## create an environment
-conda create -n star python=3.10
-conda activate star
-pip install -r requirements.txt
-sudo apt-get update && apt-get install ffmpeg libsm6 libxext6  -y
-```
-
-## 🚀 Inference
-#### Step 1: Download the pretrained model STAR from [HuggingFace](https://huggingface.co/SherryX/STAR).
-We provide two verisions, `heavy_deg.pt` for heavy degraded videos and `light_deg.pt` for light degraded videos (e.g., the low-resolution video downloaded from video websites).
-
-You can put the weight into `pretrained_weight/`.
-
-
-#### Step 2: Prepare testing data
-You can put the testing videos in the `input/video/`.
-
-As for the prompt, there are three options: 1. No prompt. 2. Automatically generate a prompt [using Pllava](https://github.com/hpcaitech/Open-Sora/tree/main/tools/caption#pllava-captioning). 3. Manually write the prompt. You can put the txt file in the `input/text/`.
-
-
-#### Step 3: Change the path
-You need to change the paths in `video_super_resolution/scripts/inference_sr.sh` to your local corresponding paths, including `video_folder_path`, `txt_file_path`, `model_path`, and `save_dir`.
-
-
-#### Step 4: Running inference command
-```
-bash video_super_resolution/scripts/inference_sr.sh
-```
-
-
-## ❤️ Acknowledgments
-This project is based on [I2VGen-XL](https://github.com/ali-vilab/VGen), [VEnhancer](https://github.com/Vchitect/VEnhancer) and [CogVideoX](https://github.com/THUDM/CogVideo). Thanks for their awesome works.
-
-
-## 🎓Citations
-If our project helps your research or work, please consider citing our paper:
-
-```
-@misc{xie2024addsr,
-      title={AddSR: Accelerating Diffusion-based Blind Super-Resolution with Adversarial Diffusion Distillation}, 
-      author={Rui Xie and Ying Tai and Kai Zhang and Zhenyu Zhang and Jun Zhou and Jian Yang},
-      year={2024},
-      eprint={2404.01717},
-      archivePrefix={arXiv},
-      primaryClass={cs.CV}
-}
-```
-
-
-## 📧 Contact
-If you have any inquiries, please don't hesitate to reach out via email at `[email protected]`
+title: STAR
+emoji: 🌟
+colorFrom: red
+colorTo: yellow
+sdk: gradio
+sdk_version: 4.37.2
+app_file: app.py
+pinned: false
+disable_embedding: true
+tags:
+  - Video Super-Resolution
+  - Video Restoration
+  - Video-to-Video
+  - Text-to-Video Model
+short_description: Video super-resolution with text-to-video model