Dataset: Object condensation: one-stage grid-free multi-object reconstruction in physics detectors, graph, and image data

This dataset is the dataset used to train and test the object condensation particle flow approach described in arxiv:2002.03605. The data can be read with DeepJetCore 3.1 (https://github.com/DL4Jets/DeepJetCore)<br> The entries in the truth array are of dimension (batch, 200, N_truth). The truth inputs are: isElectron,<br> isGamma,<br> isPositron,<br> true_energy,<br> true_x,<br> true_y The entries in the feature array are of dimension (batch, 200, N_features), with the features being: rechit_energy,<br> rechit_x,<br> rechit_y,<br> rechit_z,<br> rechit_layer,<br> rechit_detid The "train.zip" file contains the training sample<br> The "test.zip" file the test sample The main test sample is identical to the training sample in composition, but statistically independent.<br> Other samples can be found in subfolders: test/flatNpart: sample with flat distribution of additional particles in the event w.r.t. each individual particle<br> Test/hiNPart: sample with up to 15 particles per event