The data for the the paper "Measuring Laser Beams with a Neural Network."

See https://github.com/Dipolar-Quantum-Gases/nn-beam-profiling for code pertaining to the dataset and
the paper. Below we show the tree structure for the repository.

The repo contains two separate datasets. One contains simulated Gaussian beams and 
the other contains experimental Gaussian beams with a separate zip file for both.

Each dataset contains a directory for monochrome images (fimg) which are tiffs and a directory (img)
for the RGB .png images which are mapped from the monochrome images using the Viridis colormap. 

Lastly, each dataset has a text directory (text). This contains two .json files (one for the training 
data and one for the validation data) with file paths, labels, fits, regions-of-interest, 
rotated-regions-of-interest, masks and keypoints for all the Gaussian beams. For a more detailed 
explanation of the .json annotations see the github repository at the link above.