Standardize naming in loaders

[23pointsNorth]

🚀 Feature Request

There has been a few mismatches between the naming conventions and input params. It would be great to standardize those, as to make code re-use much easier. To name a few:

• In COCO segmentation/deteciton there is a difference between the loader expecting data_dir and root_dir.
• The classes capitalization is following different standards as well COCODetectionDataset vs CoCoSegmentationDataSet.
• There is coco_segmentation_dataset_params, but no coco_detection_dataset_params, but coco_detection_{network structure}_dataset_params. Change the segmentation to follow the same standard?
• Similarly dataloaders.coco_segmentation_train vs dataloaders.coco2017_train_yolo_nas.
• define a __str__ representation for the loaders, to avoid <torch.utils.data.dataloader.DataLoader object at 0x7fadc1d16620>
• segmentation has train_loader.dataset.dataset_classes_inclusion_tuples_list, but detection doesn't. A common set of params?

edit: (a few more)

• DetectionMetrics, PoseEstimationMetrics, and PreprocessSegmentationMetricsArgs
• In tutorials/colabs - train_loader, train_dataloader, train_data, val_loader, valid_loader.
• coco2017_rescoring_train is actually using coco2017_pose_rescoring_*
• Fix Fixme in documentation
• In link above PoseEstimationMetrics comment/code section error.
• the metrics_to_watch is "target_IoU" for *_metrics_list that includes BinaryIoU(), but the metric is just "IoU" if it's a multiclass case with the metrics list including IoU().

Proposed Solution (Optional)

No response

[BloodAxe]

Hey. Thanks for the report. Indeed, the naming scheme is not consistent across the config files & models.
And in fact we already started looking into standardizing it. At this point it is hard to give an accurate estimate when exactly this will be introduced.

But you may keep an eye on #1421 ;)