mirror of
https://github.com/nerfstudio-project/nerfstudio.git
synced 2026-11-12 02:45:34 +08:00
103 lines
3.4 KiB
Markdown
103 lines
3.4 KiB
Markdown
# Training your first model
|
|
|
|
## Downloading data
|
|
|
|
Download datasets provided by nerfstudio. We support the major datasets and allow users to create their own dataset, described in detail [here](./custom_dataset.md).
|
|
|
|
```
|
|
ns-download-data --dataset=blender
|
|
ns-download-data --dataset=nerfstudio --capture=poster
|
|
```
|
|
|
|
:::{admonition} Tip
|
|
:class: info
|
|
|
|
Use `ns-download-data --help` to view all currently available datasets.
|
|
:::
|
|
|
|
The resulting script should download and unpack the dataset as follows:
|
|
|
|
```
|
|
|─ nerfstudio/
|
|
├─ data/
|
|
| ├─ blender/
|
|
| ├─ fern/
|
|
| ├─ lego/
|
|
...
|
|
|- nerfstudio/
|
|
|- poster
|
|
...
|
|
```
|
|
|
|
## Training a model
|
|
|
|
See which models are available.
|
|
```bash
|
|
ns-train --help
|
|
```
|
|
|
|
Run a vanilla nerf model.
|
|
|
|
```bash
|
|
ns-train vanilla-nerf
|
|
```
|
|
|
|
Run a nerfacto model.
|
|
|
|
```bash
|
|
ns-train nerfacto
|
|
```
|
|
|
|
Run a nerfacto model with different data and port.
|
|
```
|
|
ns-train nerfacto --vis viewer --data data/nerfstudio/poster --viewer.websocket-port 7007
|
|
```
|
|
|
|
:::{admonition} Warning
|
|
:class: warning
|
|
|
|
* You may have to change the ports, and be sure to forward the "websocket-port".
|
|
* All data configurations must go at the end. In this case, `nerfstudio-data` and all of its corresponding configurations come at the end after the model and viewer specification.
|
|
:::
|
|
|
|
## Visualizing training runs
|
|
|
|
If you are using a fast NeRF variant (ie. Nerfacto/Instant-NGP), we recommend using our viewer. See our [viewer docs](viewer_quickstart.md) for a tutorial on using the viewer. The viewer will allow interactive, real-time visualization of training.
|
|
|
|
For slower methods where the viewer is not recommended, we default to [Wandb](https://wandb.ai/site) to log all training curves, test images, and other stats. We also support logging with [Tensorboard](https://www.tensorflow.org/tensorboard). We pre-specify default `--vis` options depending on the model.
|
|
|
|
:::{admonition} Attention
|
|
:class: attention
|
|
|
|
- Currently we only support using a single viewer at a time.
|
|
- To toggle between Wandb, Tensorboard, or our Web-based Viewer, you can specify `--vis VIS_OPTION`, where `VIS_OPTION` is one of {viewer,wandb,tensorboard}.
|
|
:::
|
|
|
|
#### Rendering videos
|
|
We also provide options to render out the scene of a trained model with a custom trajectory and save the output to a video.
|
|
|
|
```bash
|
|
ns-render --load-config={PATH_TO_CONFIG} --traj=spiral --output-path=output.mp4
|
|
```
|
|
|
|
While we provide pre-specified trajectory options, `--traj={spiral, interp, filename}` we can also specify a custom trajectory if we specify `--traj=filename --camera-path-filename {PATH}`.
|
|
|
|
:::{admonition} Tip
|
|
:class: info
|
|
After running the training, the config path is logged to the terminal under "[base_config.py:263] Saving config to:"
|
|
:::
|
|
|
|
:::{admonition} See Also
|
|
:class: seealso
|
|
This quickstart allows you to preform everything in a headless manner.
|
|
We also provide a web-based viewer that allows you to easily monitor training or render out custom trajectories.
|
|
See our [viewer docs](viewer_quickstart.md) for more.
|
|
:::
|
|
|
|
## Evaluating Runs
|
|
Calculate the psnr of your trained model and save to a json file.
|
|
```bash
|
|
ns-eval --load-config={PATH_TO_CONFIG} --output-path=output.json
|
|
```
|
|
|
|
We also provide a train and evaluation script that allows you to do benchmarking on the classical Blender dataset (see our [benchmarking workflow](../developer_guides/debugging_tools/benchmarking.md)). |