Multiclass detection

[jrbtaylor]

Thanks for making the code public.

I noticed none of the example config files is set for detecting multiple classes (i.e. car, pedestrian and cyclist as 3 separate classes). I tried modifying one of the included configs by appending to "classes" and "num_clusters" in dataset_config but it crashed building the dataset. I think the related lines are 178-179 of avod.datasets.kitti.kitti_dataset:

            elif self.classes == ['Car', 'Pedestrian', 'Cyclist']:
                self.classes_name = 'All'

then 'All' is passed to get_anchor_info in avod.core.mini_batch_utils, which tries to find the preprocessed dataset files for 'All', which is not created in the preprocessing - instead it creates 3 directories for 'car', 'pedestrian' and 'cyclist'. I think there's either a mismatch between the preprocessing and training code, or I'm missing something in the config file that's unclear.

Is it possible to include one of the config files from your thesis work where you did multiclass detection on KITTI?