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2 changes: 1 addition & 1 deletion
2
docs/tutorials/data/creating_dataset.md → docs/quickstart/custom_dataset.md
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# Installation | ||
# Training First Model | ||
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### Create environment | ||
## Downloading data | ||
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We reccomend using conda to manage dependencies. Make sure to install [Conda](https://docs.conda.io/en/latest/miniconda.html) before preceding. | ||
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```bash | ||
conda create --name nerfstudio -y python=3.8.13 | ||
conda activate nerfstudio | ||
python -m pip install --upgrade pip | ||
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``` | ||
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### Dependencies | ||
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Install pytorch with CUDA (this repo has been tested with CUDA 11.3) and [tiny-cuda-nn](https://github.com/NVlabs/tiny-cuda-nn) | ||
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```bash | ||
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html | ||
pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch | ||
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``` | ||
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### Installing nerfstudio | ||
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Easy option: | ||
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```bash | ||
pip install nerfstudio | ||
``` | ||
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If you would want the latest and greatest: | ||
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```bash | ||
git clone [email protected]:plenoptix/nerfstudio.git | ||
cd nerfstudio | ||
pip install -e . | ||
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``` | ||
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### Optional Installs | ||
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#### Tab completion (bash & zsh) | ||
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This needs to be rerun when the CLI changes, for example if nerfstudio is updated. | ||
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```bash | ||
ns-install-cli | ||
``` | ||
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### Development packages | ||
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```bash | ||
pip install -e.[dev] | ||
pip install -e.[docs] | ||
``` | ||
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# Downloading data | ||
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Download the original NeRF Blender dataset. We support the major datasets and allow users to create their own dataset, described in detail [here](https://docs.nerf.studio/en/latest/tutorials/data/index.html). | ||
Download the original NeRF Blender dataset. We support the major datasets and allow users to create their own dataset, described in detail [here TODO]. | ||
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``` | ||
ns-download-data --dataset=blender | ||
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@@ -78,7 +23,7 @@ Use `--help` to view all currently available datasets. The resulting script shou | |
... | ||
``` | ||
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# Training a model | ||
## Training a model | ||
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To run with all the defaults, e.g. vanilla nerf method with the blender lego image | ||
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@@ -100,27 +45,27 @@ Run with nerfstudio data. You'll may have to change the ports, and be sure to fo | |
ns-train nerfacto --vis viewer --viewer.zmq-port 8001 --viewer.websocket-port 8002 nerfstudio-data --pipeline.datamanager.dataparser.data-directory data/nerfstudio/poster --pipeline.datamanager.dataparser.downscale-factor 4 | ||
``` | ||
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# Visualizing training runs | ||
## Visualizing training runs | ||
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If you using a fast NeRF variant (ie. Instant-NGP), we reccomend using our viewer. See our [viewer docs](../tutorials/viewer/viewer_quickstart.md) for more details. The viewer will allow interactive visualization of training in realtime. | ||
If you using a fast NeRF variant (ie. Instant-NGP), we reccomend using our viewer. See our [viewer docs](viewer_quickstart.md) for more details. The viewer will allow interactive visualization of training in realtime. | ||
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Additionally, if you run everything with the default configuration, by default, we use [TensorBoard](https://www.tensorflow.org/tensorboard) to log all training curves, test images, and other stats. Once the job is launched, you will be able to track training by launching the tensorboard in `outputs/blender_lego/vanilla_nerf/<timestamp>/<events.tfevents>`. | ||
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```bash | ||
tensorboard --logdir outputs | ||
``` | ||
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# Rendering a Trajectory | ||
## Rendering a Trajectory | ||
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To evaluate the trained NeRF, we provide an evaluation script that allows you to do benchmarking (see our [benchmarking workflow](../tooling/benchmarking.md)) or to render out the scene with a custom trajectory and save the output to a video. | ||
To evaluate the trained NeRF, we provide an evaluation script that allows you to do benchmarking (see our [benchmarking workflow](../developer_guides/benchmarking.md)) or to render out the scene with a custom trajectory and save the output to a video. | ||
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```bash | ||
ns-eval render-trajectory --load-config=outputs/blender_lego/instant_ngp/2022-07-07_230905/config.yml --traj=spiral --output-path=output.mp4 | ||
``` | ||
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Please note, 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 trajectories. See our [viewer docs](../tutorials/viewer/viewer_quickstart.md) for more. | ||
Please note, 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 trajectories. See our [viewer docs](viewer_quickstart.md) for more. | ||
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# FAQ | ||
## FAQ | ||
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- [TinyCUDA installation errors out with cuda mismatch](tiny-cuda-error) | ||
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|
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Original file line number | Diff line number | Diff line change |
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# Installation | ||
|
||
### Create environment | ||
|
||
We reccomend using conda to manage dependencies. Make sure to install [Conda](https://docs.conda.io/en/latest/miniconda.html) before preceding. | ||
|
||
```bash | ||
conda create --name nerfstudio -y python=3.8.13 | ||
conda activate nerfstudio | ||
python -m pip install --upgrade pip | ||
|
||
``` | ||
|
||
### Dependencies | ||
|
||
Install pytorch with CUDA (this repo has been tested with CUDA 11.3) and [tiny-cuda-nn](https://github.com/NVlabs/tiny-cuda-nn) | ||
|
||
```bash | ||
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html | ||
pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch | ||
|
||
``` | ||
|
||
### Installing nerfstudio | ||
|
||
Easy option: | ||
|
||
```bash | ||
pip install nerfstudio | ||
``` | ||
|
||
If you would want the latest and greatest: | ||
|
||
```bash | ||
git clone [email protected]:plenoptix/nerfstudio.git | ||
cd nerfstudio | ||
pip install -e . | ||
|
||
``` | ||
|
||
### Optional Installs | ||
|
||
#### Tab completion (bash & zsh) | ||
|
||
This needs to be rerun when the CLI changes, for example if nerfstudio is updated. | ||
|
||
```bash | ||
ns-install-cli | ||
``` | ||
|
||
### Development packages | ||
|
||
```bash | ||
pip install -e.[dev] | ||
pip install -e.[docs] | ||
``` |
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@@ -0,0 +1 @@ | ||
# Setting up Viewer |
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