* NERFSTUDIO_METHOD_CONFIGS allow method specification as callabale (function or class)
* docs - NERFSTUDIO_METHOD_CONFIGS accepts function or derived class
To prevent abusing of root privilege, please use custom user privilege to start.
If not, sometimes the Docker images may be started with the permissions of root or other users. If you modify the mounted files in the container , it will cause permission errors or other errors.
Co-authored-by: Matthew Tancik <matt@lumalabs.ai>
* added pytorch omnicv implementation in order to not use GPL equi2pers
* renamed rotation matrix function to decrease confusion
* fixed docstrings
* fixed linting
* removed pyequilib from dependencies
* Update pixel_samplers.py
Now uses the specified batch_size param in sample_method()
* black
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Co-authored-by: Matthew Tancik <matt@lumalabs.ai>
* Use torch_compile with Zoe for compatibility
torch_compile module support
Previously the compatibility utility torch.compile worked for functions, but not for modules as torch.compile was originally employed here.
* torch_compile -> Any
* nerfbusters dataparser
* nerfbuster dataparser and visualization of eval views
* resolved some errors from pyright
* enable ns-process-data to take two videos as input and use one for eval and the other for train
* resolve some pyright issues
* instead of data being a tuple, I added eval_data as another argument
* implemented train eval split for all cases
* implemented train eval split for all cases
* reverting equi changes
* reverting reality capture changes
* raise valueerror
* revert comment
* added split override code back to dataparser
* reverted one change
* using image border now
* adding docs
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Co-authored-by: Ethan Weber <eweb0124@gmail.com>
Use ns-process-data images --no-same-dimensions ... to handle images sets with different dimensions properly. (Fast downscaling assumes image dimensions are the same.)
* Remove system-level CUDA install from Linux install instructions
* Remove system-level CUDA from Windows install instructions
* Un-flip CUDA 11.7 / 11.8
* Fix pixel sampler cpu bottleneck
cpu usage reduced 1700% -> 100%, and even more if using multi-gpu training
* Convert to config option
* Change optional to bool
* Moved Volinga as an external method
* Update external_methods.py for black
* Formatted with black
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Co-authored-by: jperezh <jperezh@arquimea.com>
* Render VR180 video
Adding the VR180 camera model to render VR180 video and images. I condensed the omnidirectional stereo and VR180 render post processing in the render script. I have updated the documentation for VR180 support.
* Condensing formatting of camera types
Condensing the if statement for camera type intrinsics.
* Implement nerfacto alpha transparency training
* Stop adding all ones alpha channel and clean up blend_background
* Make background_color a required argument in blend_background
* Enable alpha transparent training by default
* Improve background_color typing
* Blend uniform background color for metric computation
* Fix typing error
* Clean up typing
* Fix background_color to outputs assignment
* Model outputs returns unblended RGB (black bg) for random bg
* Update renderers
* Fix comments
* Add support for transparent BG for other methods
* Minor refac
* Fix get_background_color
* Fix typing error for blend_background
* Fix comments
* Export utils support transparency
* Pylint fix
* Fix pcd export masking
* Filter pcd view directions based on opacity
* Clean up get_rgba_image
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Co-authored-by: Jonas Kulhanek <jonas.kulhanek@live.com>
* Fix arguments that are not passed from config to NerfactoField
* Add comments
* Reset base_res and features_per_level config of nerfacto-big and nerfacto-huge to default to match the original behavior
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Co-authored-by: Matthew Tancik <matt@lumalabs.ai>
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