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110 lines
3.0 KiB
Markdown
110 lines
3.0 KiB
Markdown
# Using custom data
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Training model on existing datasets is only so fun. If you would like to train on self captured data you will need to process the data into an existing format. Specifically we need to know the camera poses for each image. [COLMAP](https://github.com/colmap/colmap) is a standard tool for extracting poses. It is possible to use other methods like [SLAM](https://en.wikipedia.org/wiki/Simultaneous_localization_and_mapping) or hardware recorded poses. We intend to add documentation for these other methods in the future.
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## Nerfstudio dataset
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To assist running on custom data we have a script that will process a video or folder of images into a format that is compatible with nerfstudio. We use [COLMAP](https://colmap.github.io) and [FFmpeg](https://ffmpeg.org/download.html) in our data processing script, please have these installed. We have provided a quickstart to installing COLMAP below, FFmpeg can be downloaded from [here](https://ffmpeg.org/download.html)
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To process your data run:
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```bash
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ns-process-data --data {FOLDER_OR_VIDEO} --output-dir {PROCESSED_DATA_DIR}
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```
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A full set of arguments can be found {doc}`here</reference/cli/ns_process_data>`.
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:::{admonition} Tip
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:class: info
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- COLMAP can be finicky. Try your best to capture overlapping, non-blurry images.
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:::
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### Training on your data
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Simply specify that you are using the `nerfstudio` dataparser and point the data directory to your processed data.
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```bash
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ns-train instant-ngp nerfstudio-data --data {PROCESSED_DATA_DIR}
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```
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### Installing COLMAP
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There are many ways to install COLMAP, unfortunately it can sometimes be a bit finicky. If the following commands do not work, please refer to the [COLMAP installation guide](https://colmap.github.io/install.html) for additional installation methods. COLMAP install issues are common! Feel free to ask for help in on our [Discord](https://discord.gg/NHGtYRAW).
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::::::{tab-set}
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:::::{tab-item} Linux
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We recommend trying `apt`:
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```
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sudo apt install colmap
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```
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If that doesn't work, you can try VKPG:
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::::{tab-set}
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:::{tab-item} CUDA
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```bash
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git clone https://github.com/microsoft/vcpkg
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cd vcpkg
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./bootstrap-vcpkg.sh
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./vcpkg install colmap[cuda]:x64-linux
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```
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:::
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:::{tab-item} CPU
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```bash
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git clone https://github.com/microsoft/vcpkg
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cd vcpkg
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./bootstrap-vcpkg.sh
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./vcpkg install colmap:x64-linux
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```
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:::
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::::
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If that doesn't work, you will need to build from source. Refer to the [COLMAP installation guide](https://colmap.github.io/install.html) for details.
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:::::
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:::::{tab-item} OSX
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```bash
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git clone https://github.com/microsoft/vcpkg
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cd vcpkg
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./bootstrap-vcpkg.sh
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./vcpkg install colmap
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```
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:::::{tab-item} Windows
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::::{tab-set}
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:::{tab-item} CUDA
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```bash
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git clone https://github.com/microsoft/vcpkg
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cd vcpkg
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./bootstrap-vcpkg.sh
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./vcpkg install colmap[cuda]:x64-windows
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```
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:::
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:::{tab-item} CPU
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```bash
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git clone https://github.com/microsoft/vcpkg
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cd vcpkg
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./bootstrap-vcpkg.sh
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./vcpkg install colmap:x64-windows
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```
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:::::
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::::::
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