Single-Molecule Localization Microscopy (SMLM) 2D Digits 123 and TOL letters and grid dataset processed for machine-learning

The digits and letters dataset was adapted from Huijben, Teun Adrianus Petrus Maria; Heydarian, Hamidreza; Rieger, B. (Bernd); Stallinga, S. (Sjoerd); Jungmann, R. (Ralf) et. al. (2021): Single-Molecule Localization Microscopy (SMLM) 2D Digits 123 and TOL letters datasets. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/14074091.v1 under CC BY-NC 4.0 clusternet_hcf.tar.gz contains the files for ClusterNet-HCF clusternet_lcf.tar.gz contains the files for ClusterNet-LCF The salient folders in these are: config - configuration files preprocessed - train and test files in Apache .parquet format - these files could be used to re-train a different network using the pipeline models - contains the trained model output - results processed - train, validation and test files in Pytorch Geometric format scripts Note: the test files are the RESERVED TEST SET FILES the train and validation set together constitute the data that was used in cross-validation the clusters contain the handcrafted features. To reproduce/visualise results follow the instructions at https://github.com/oubino/locpix_points/