Update README.md

README.md

@@ -1,113 +1,14 @@
-<h1 align="center">
-  <span style="color:#2196f3;"><b>MiniMax</b></span><span style="color:#f06292;"><b>-Remover</b></span>: Taming Bad Noise Helps Video Object Removal
-</h1>
-
-<p align="center">
-  Bojia Zi<sup>*</sup>,
-  Weixuan Peng<sup>*</sup>,
-  Xianbiao Qi<sup>†</sup>,
-  Jianan Wang, Shihao Zhao, Rong Xiao, Kam-Fai Wong<br>
-  <sup>*</sup> Equal contribution. <sup>†</sup> Corresponding author.
-</p>
-
-<p align="center">
-  <a href="https://huggingface.co/zibojia/minimax-remover"><img alt="Huggingface Model" src="https://img.shields.io/badge/%F0%9F%A4%97%20Huggingface-Model-brightgreen"></a>
-  <a href="https://github.com/zibojia/MiniMax-Remover"><img alt="Github" src="https://img.shields.io/badge/MiniMaxRemover-github-black"></a>
-  <a href="https://huggingface.co/spaces/zibojia/MiniMaxRemover"><img alt="Huggingface Space" src="https://img.shields.io/badge/%F0%9F%A4%97%20Huggingface-Space-1e90ff"></a>
-  <a href="https://arxiv.org/abs/2505.24873"><img alt="arXiv" src="https://img.shields.io/badge/MiniMaxRemover-arXiv-b31b1b"></a>
-  <a href="https://www.youtube.com/watch?v=KaU5yNl6CTc"><img alt="YouTube" src="https://img.shields.io/badge/Youtube-video-ff0000"></a>
-  <a href="https://minimax-remover.github.io"><img alt="Demo Page" src="https://img.shields.io/badge/Website-Demo%20Page-yellow"></a>
-</p>
-
----
-
-## 🚀 Overview
-
-**MiniMax-Remover** is a fast and effective video object remover based on minimax optimization. It operates in two stages: the first stage trains a remover using a simplified DiT architecture, while the second stage distills a robust remover with CFG removal and fewer inference steps.
-
----
-
-## ✨ Features: 
-
-* **Fast:** Requires only 6 inference steps and does not use CFG, making it highly efficient.
-
-* **Effective:** Seamlessly removes objects from videos and generates high-quality visual content.
-
-* **Robust:** Maintains robustness by preventing the regeneration of undesired objects or artifacts within the masked region, even under varying noise conditions.
-
----
-
-## 🛠️ Installation
-
-All dependencies are listed in `requirements.txt`.
-
-```bash
-pip install -r requirements.txt
-```
-
 ---
-
-## 🏃‍♂️ Gradio Demo
-
-<p align="center">
-  <a href="https://youtu.be/1V7Ov4vmnBc" target="_blank">
-    <img src="./imgs/gradio_demo.gif" alt="firstpage" style="width:80%;" />
-  </a>
-</p>
-
-You can use this gradio demo to remove objects. Note that you don't need to compile the sam2.
-```bash
-cd gradio_demo
-python3 test.py
-```
-
----
-
-## 📂 Download
-
-```shell
-huggingface-cli download zibojia/minimax-remover --include vae transformer scheduler --local-dir .
-```
-
----
-
-## ⚡ Quick Start
-
-### Minimal Example
-
-```python
-import torch
-from diffusers.utils import export_to_video
-from decord import VideoReader
-from diffusers.models import AutoencoderKLWan
-from transformer_minimax_remover import Transformer3DModel
-from diffusers.schedulers import UniPCMultistepScheduler
-from pipeline_minimax_remover import Minimax_Remover_Pipeline
-
-random_seed = 42
-video_length = 81
-device = torch.device("cuda:0")
-
-# Load model weights separately
-vae = AutoencoderKLWan.from_pretrained("./vae", torch_dtype=torch.float16)
-transformer = Transformer3DModel.from_pretrained("./transformer", torch_dtype=torch.float16)
-scheduler = UniPCMultistepScheduler.from_pretrained("./scheduler")
-
-images = # images in range [-1, 1]
-masks = # masks in range [0, 1]
-
-# Initialize the pipeline (pass the loaded weights as objects)
-pipe = Minimax_Remover_Pipeline(vae=vae, transformer=transformer, \
-    scheduler=scheduler, torch_dtype=torch.float16
-).to(device)
-
-result = pipe(images=images, masks=masks, num_frames=video_length, height=480, width=832, \
-    num_inference_steps=12, generator=torch.Generator(device=device).manual_seed(random_seed), iterations=6 \
-).frames[0]
-export_to_video(result, "./output.mp4")
-```
+title: MiniMax Remover
+emoji: ⚡
+colorFrom: purple
+colorTo: red
+sdk: gradio
+sdk_version: 5.34.1
+app_file: app.py
+pinned: false
+license: cc-by-nc-2.0
+short_description: MiniMax-Remover is a fast and effective video object remover
 ---
 
-## 📧 Contact
-
-Feel free to send an email to [[email protected]](mailto:[email protected]) if you have any questions or suggestions.
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference