This repository contains the source code that is part of the supplemental material for the EGSR 2021 Paper: Sampling Clear Sky Models using Truncated Gaussian Mixtures. The contents are:

• Python script for the fitting process
• Reference implementation as a PBRTv3 plugin for infinite area light sources.
• Pre-trained models for Preetham and Hosek sky models.
• Test renderings for various scenes

Some additional quick links

• Author version of the paper
• Video presentation (TBD) (12 min)

• Overview
• Usage Instructions
• How to Cite
• Acknowledgments

The folders are:

• cpp_sky_gen_code, contains C++ source code for the generation of radiance and luminance maps for the Hosek and Preetham models. See README.txt for the compilation of the tool. A compiled executable is also provided for convenience.
• dataset, contains a subset of the dataset for the Hosek and Preetham sky models
• pbrt, containing the PBRT-v3 code for plugging in the tGMM source code
• python_fitting_code, encompassing the Python 3 source code for the fitting process and visualisation utilities
• screenshots, including all rendered images that were included in the paper plus additional ones, for reference. The file naming convention is: <sampling_method>_<importance_sampling>. For example: barcelona-pavilion_23_4_4_gmm_mis, elevation: 23, turbidity: 4, spp: 4, Sampling method: tGMM, MIS enabled: Yes. To reduce content size, files have been converted to PNG format.

To build the sky maps tool:

• Open a Visual Studio x64 command line console.

• Change directory to the cpp_sky_gen_code folder.

• Dependencies

  • TinyEXR (header only - included)
  • FreeImage (compiled, included for Windows|x64)

• Dependencies Folder

  • include folder for FreeImage and TinyEXR headers
  • lib/x64 for FreeImage.lib and FreeImage.dll
  • The FreeImage.dll needs to be manually copied to the executable folder

• Run the following command for MSVC:

  cl /O2 /MT /D "_CONSOLE" /D "_UNICODE" /D "UNICODE" SunSky.cpp SunSkyTool.cpp /I "include" /link /LIBPATH:"lib/x64" "FreeImage.lib"

or

• Run the following command for Clang:

  * clang++.exe -O2 SunSky.cpp SunSkyTool.cpp -Iinclude -L"lib/x64" -o SunSky.exe -lFreeImage

This generates the executable 'SunSky.exe'

To generate sky maps and dataset, Go to cpp_sky_gen_code folder and run:

SunSky.exe -s Hosek -p    (for Hosek)
SunSky.exe -s Preetham -p (for Preetham)

To run the scripts that generate the dataset and perform the fitting process, go to the python_fitting_code\skymodel folder and run main.py.

The provided functionality for the script is:

python main.py -h
usage: main.py [-h] 
               [--generateDataset input directory output_directory]
               [--best_num_gaussians min_value max_value] 
               [--fit] 
               [--plot]
               [--visualize_model model name max_GMMs_to_show]
               [--skymapdir skymap directory] 
               [--outdir output directory]

optional arguments:
  -h, --help            show this help message and exit
  --generateDataset input directory output_directory, -g input directory output_directory
                        Generates the dataset for the fitting process.
  --best_num_gaussians min_value max_value, -b min_value max_value
                        Performs fitting and stores the best GMM count.
                        Expects min max arguments.
  --fit, -f             Fits the .tiff skymap files in the skymap dir
  --plot, -p            Plots the result during fitting
  --visualize_model model name max_GMMs_to_show, -v model name max_GMMs_to_show
                        Visualises up to 'max_GMMs' from the model
  --skymapdir skymap directory, -s skymap directory
                        Sky Model PDF directory. Default is
                        ../../dataset/hosek/hosek_sky_luminance
  --outdir output directory, -o output directory
                        Output directory. Default is fit

For example, to generate luminance sky maps:

python main.py --generateDataset ..\..\dataset\hosek\hosek_sky ..\..\dataset\hosek\hosek_sky_luminance

Additionally, to run the fitting process (output at fit\model.csv):

python main.py --fit --skymapdir ..\..\dataset\hosek\hosek_sky_luminance --outdir fit

Simply replace the files in the pbrt source code directory. The important files are:

• infinite_gmm, containing the tGMM infinite light implementation
• infinite_uniform, containing the naive uniform sampling for comparison purposes

The license is Apache 2.0. If you use the contents of this repository for your work, please cite it as described below:

In our work, we have used the source code~\cite{Vitsas_EGSR_2021}, available at 'https://github.com/cgaueb/tgmm_sky_sampling'.

@inproceedings{vitsas2021tgmm,
    booktitle = {Eurographics Symposium on Rendering - DL-only Track},
    editor = {Bousseau, Adrien and McGuire, Morgan},
    title = {{Sampling Clear Sky Models using Truncated Gaussian Mixtures}},
    author = {Vitsas, Nick and Vardis, Konstantinos and Papaioannou, Georgios},
    year = {2021},
    publisher = {The Eurographics Association},
    ISSN = {1727-3463},
    ISBN = {978-3-03868-157-1},
    DOI = {10.2312/sr.20211288}
}

Note: A proper bibtex will be uploaded when the paper gets published.

The provided sky map generation utility is based on a modified version of the excellent library by Andrew Willmott available here. The breakfast room scene was downloaded from Benedikt Bitterli’s rendering resources. All remaining scenes were obtained from the PBRT-v3 scene repository.