nss_data_generation.md

Generating new training data

To train the Neural Super Sampling model, you will first need to capture training data from your game engine in the format expected by the model.

The data capture guide explains how to capture data from your game and how to convert it into the expected format. This guide also contains recommendations regarding dataset size and types of game data that should be captured.

Once you have captured data from your game engine, and it is in the expected format, then you can use the provided script here to convert captured EXR frames to Safetensors.

This script can be run using the following:

python -m scripts.safetensors_generator.safetensors_writer -src="path/to/exr/root/dir" -reader=EXRv101 -extension=exr

These Safetensors files can then be cropped by running the script passing in the directory containing the uncropped Safetensors as the source:

python -m scripts.safetensors_generator.safetensors_writer -src="path/to/safetensors/root/dir" -reader=cropper -extension=safetensors

Additional optional flags:

Flag	Description	Default
-dst	Path to root folder of destination	./output/safetensors
-threads	Number of parallel threads to use	1
-extension	File extension of the source data	"exr"
-overwrite	Overwrite data in destination if it already exists	False
-linear-truth	Whether the ground truth is already linear; assumes Karis TM if not	True
-logging_output_dir	Path to folder for logging output	./output
-reader	Name of the data reader to use	"EXRv101"
-crop_size	Crop size in outDims	256

Please see the documentation here for more details on the expected dataset format and layout.