batch_learner: Fixed debugging to use callbacks with HDF5_logger object instances.
advanced_image_processing: Added logging of intermediate arrays using HDF5_logger to implement this. Debug callbacks passed throughout to enable easy logging. Uses vigra for local maxima (deals with plateaus properly and drops edges) via generate_local_maxima_vigra. Similarly packaged the old scikit image function (it messes up plateaus). Added extended_region_local_maxima_properties, which builds on region_properties by providing all the local maxima in the structured array, which means that entries are no longer unique by label, but are unique by local maxima. Also, extended_region_local_maxima_properties returns a structured array with different label names than used before. All relevant properties for missing labels are stored in missing_labels.hdf5. Refactored and renamed LabelImageCentroidProps to ExtendedRegionProps. Now, can be used to do local maxima removal for the watershed results as well. This is currently being done. This also helps further refactor wavelet_denoising. Simplified merge_neuron_sets and fixed some errors in it. Now, merge_neuron_sets uses NumPy arrays to the fullest extent to determine distances and the like. Added a function inside of generate_neurons (array_debug_logger_enumerator) to ensure that debug information is kept per basis image.