https://github.com/lsongx/nerfplayer-nerfstudio
https://github.com/lsongx/nerfplayer-nerfstudio
Last synced: 10 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/lsongx/nerfplayer-nerfstudio
- Owner: lsongx
- Created: 2023-06-13T22:15:51.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-11-03T22:36:42.000Z (6 months ago)
- Last Synced: 2024-11-03T23:24:17.413Z (6 months ago)
- Language: Python
- Size: 36.1 KB
- Stars: 45
- Watchers: 4
- Forks: 5
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-dynamic-NeRF - [Code
README
# NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields
This is an nerfstudio framework based implementation for [NeRFPlayer](https://lsongx.github.io/projects/nerfplayer.html).
[](https://www.youtube.com/watch?v=flVqSLZWBMI)
# Installation
NeRFPlayer follows the integration guidelines described [here](https://docs.nerf.studio/en/latest/developer_guides/new_methods.html) for custom methods within nerfstudio.
### 0. Install Nerfstudio dependencies
[Follow these instructions](https://docs.nerf.studio/en/latest/quickstart/installation.html) up to and including "tinycudann" to install dependencies and create an environment
### 1. Clone this repo
```git clone https://github.com/lsongx/nerfplayer-nerfstudio.git```
### 2. Install this repo as a python package
Navigate to this folder and run `python -m pip install -e .`
### 3. Run `ns-install-cli`
### Checking the install
Run `ns-train -h`: you should see a list of "subcommands" with `nerfplayer-nerfacto` and `nerfplayer-ngp` included among them.
# Using NeRFPlayer
Now that NeRFPlayer is installed you can play with it.
## Preparing data
- Currently only [DyCheck](https://hangg7.com/dycheck/) dataset is supported.
- Download [DyCheck data](https://drive.google.com/drive/folders/1cBw3CUKu2sWQfc_1LbFZGbpdQyTFzDEX).
- You can capture your own scenes by following [DyCheck's guide](https://github.com/KAIR-BAIR/dycheck/blob/main/docs/RECORD3D_CAPTURE.md).
## Run
- Launch training with `ns-train nerfplayer-ngp --data `. This specifies a data folder to use.
- example: `ns-train nerfplayer-ngp --data dycheck/mochi-high-five/`
- Connect to the viewer by forwarding the viewer port, and click the link to `viewer.nerf.studio` provided in the output of the train script
# Misc
### Issues
Please open Github issues (under this repo, not under nerfstudio) for any installation/usage problems you run into.
#### Known TODOs
- [ ] Multi-camera datasets: DyNeRF, ImmersiveVideo
- [ ] Decomposition in NeRFPlayer. Under nerfstudio's framework, we got NaN soon if a decomposition module is used.