else:
raise ValueError('All logs must share the same dataset to be compared')
else:
plot_dataset = config.dataset[:5]
# Plot the training loss and accuracy
compare_trainings(logs, logs_names)
# Plot the validation
if plot_dataset.startswith('Shape'):
compare_convergences_multisegment(logs, logs_names)
elif plot_dataset.startswith('S3DIS'):
dataset = S3DISDataset()
compare_convergences_segment(dataset, logs, logs_names)
elif plot_dataset.startswith('Model'):
dataset = ModelNet40Dataset()
compare_convergences_classif(dataset, logs, logs_names)
elif plot_dataset.startswith('Scann'):
dataset = ScannetDataset()
compare_convergences_segment(dataset, logs, logs_names)
elif plot_dataset.startswith('Seman'):
dataset = Semantic3DDataset()
compare_convergences_segment(dataset, logs, logs_names)
elif plot_dataset.startswith('NPM3D'):
dataset = NPM3DDataset()
compare_convergences_segment(dataset, logs, logs_names)
else:
raise ValueError('Unsupported dataset : ' + plot_dataset)