update readme for compatability

README.md

@@ -1,111 +1,9 @@
-
-## Large Multi-View Gaussian Model
-
-This is the official implementation of *LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation*.
-
-### [Project Page](https://me.kiui.moe/lgm/) | [Arxiv](https://arxiv.org/abs/2402.05054) | [Weights](https://huggingface.co/ashawkey/LGM) | <a href="https://huggingface.co/spaces/ashawkey/LGM"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Gradio%20Demo-Huggingface-orange"></a>
-
-https://github.com/3DTopia/LGM/assets/25863658/cf64e489-29f3-4935-adba-e393a24c26e8
-
-> [!NOTE]
-> Thanks to [@yxymessi](https://github.com/yxymessi) and [@florinshen](https://github.com/florinshen), we have found that there is a **severe bug in rotation normalization** [here](https://github.com/3DTopia/LGM/blob/main/core/models.py#L43).
-> However, the current model is trained with this wrong code and correcting it leads to some quality degradation. We will work on retraining a correct model in the future.
-> 
-> **If you are going to retrain a model, please correct it to `self.rot_act = lambda x: F.normalize(x, dim=-1)`** !
-
-### Replicate Demo:
-* gaussians: [demo](https://replicate.com/camenduru/lgm) | [code](https://github.com/camenduru/LGM-replicate)
-* mesh: [demo](https://replicate.com/camenduru/lgm-ply-to-glb) | [code](https://github.com/camenduru/LGM-ply-to-glb-replicate)
-
-Thanks to [@camenduru](https://github.com/camenduru)!
-
-### Install
-
-```bash
-# xformers is required! please refer to https://github.com/facebookresearch/xformers for details.
-# for example, we use torch 2.1.0 + cuda 11.8
-pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu118
-pip install -U xformers --index-url https://download.pytorch.org/whl/cu118
-
-# a modified gaussian splatting (+ depth, alpha rendering)
-git clone --recursive https://github.com/ashawkey/diff-gaussian-rasterization
-pip install ./diff-gaussian-rasterization
-
-# for mesh extraction
-pip install git+https://github.com/NVlabs/nvdiffrast
-
-# other dependencies
-pip install -r requirements.txt
-```
-
-### Pretrained Weights
-
-Our pretrained weight can be downloaded from [huggingface](https://huggingface.co/ashawkey/LGM).
-
-For example, to download the fp16 model for inference:
-```bash
-mkdir pretrained && cd pretrained
-wget https://huggingface.co/ashawkey/LGM/resolve/main/model_fp16.safetensors
-cd ..
-```
-
-For [MVDream](https://github.com/bytedance/MVDream) and [ImageDream](https://github.com/bytedance/ImageDream), we use a [diffusers implementation](https://github.com/ashawkey/mvdream_diffusers).
-Their weights will be downloaded automatically.
-
-### Inference
-
-Inference takes about 10GB GPU memory (loading all imagedream, mvdream, and our LGM).
-
-```bash
-### gradio app for both text/image to 3D
-python app.py big --resume pretrained/model_fp16.safetensors
-
-### test
-# --workspace: folder to save output (*.ply and *.mp4)
-# --test_path: path to a folder containing images, or a single image
-python infer.py big --resume pretrained/model_fp16.safetensors --workspace workspace_test --test_path data_test 
-
-### local gui to visualize saved ply
-python gui.py big --output_size 800 --test_path workspace_test/saved.ply
-
-### mesh conversion
-python convert.py big --test_path workspace_test/saved.ply
-```
-
-For more options, please check [options](./core/options.py).
-
-### Training
-
-**NOTE**: 
-Since the dataset used in our training is based on AWS, it cannot be directly used for training in a new environment.
-We provide the necessary training code framework, please check and modify the [dataset](./core/provider_objaverse.py) implementation!
-
-We also provide the **~80K subset of [Objaverse](https://objaverse.allenai.org/objaverse-1.0)** used to train LGM in [objaverse_filter](https://github.com/ashawkey/objaverse_filter).
-
-```bash
-# debug training
-accelerate launch --config_file acc_configs/gpu1.yaml main.py big --workspace workspace_debug
-
-# training (use slurm for multi-nodes training)
-accelerate launch --config_file acc_configs/gpu8.yaml main.py big --workspace workspace
-```
-
-### Acknowledgement
-
-This work is built on many amazing research works and open-source projects, thanks a lot to all the authors for sharing!
-
-- [gaussian-splatting](https://github.com/graphdeco-inria/gaussian-splatting) and [diff-gaussian-rasterization](https://github.com/graphdeco-inria/diff-gaussian-rasterization)
-- [nvdiffrast](https://github.com/NVlabs/nvdiffrast)
-- [dearpygui](https://github.com/hoffstadt/DearPyGui)
-- [tyro](https://github.com/brentyi/tyro)
-
-### Citation
-
-```
-@article{tang2024lgm,
-  title={LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation},
-  author={Tang, Jiaxiang and Chen, Zhaoxi and Chen, Xiaokang and Wang, Tengfei and Zeng, Gang and Liu, Ziwei},
-  journal={arXiv preprint arXiv:2402.05054},
-  year={2024}
-}
-```
+title: LGM
+emoji: 🦀
+colorFrom: red
+colorTo: indigo
+sdk: docker
+sdk_version: 4.20.1
+python_version: 3.10.13
+app_file: app.py
+pinned: false