The currently supported datasets are - Pascal VOC, MS-COCO, ImageNet-DET and ImageNet-VID
The datasets should be stored in the following directory structure
VidDet/
└── datasets/
├── ImageNetDET (170.8 GB)
├── ImageNetVID (409.9 GB)
├── MSCoco (84.9 GB)
├── PascalVOC (9.8 GB)
└── # version controlled files
The datasets can be downloaded from my Google Drive:
It's possible to combine all four datasets into one larger dataset with the utilisation of the CombinedDetection() dataset specified in combined.py
Following ideas from YOLO-9k with utilising the WordNet structure classes have been manually matched across datasets, furthermore a hierarchical tree structure has been generated for the classes. This is visualised below and is specified in trees/, with the main tree (inclusive of ImageNet-DET) specified in trees/filtered_det.tree
These are the training split statistics, also samples in ImageNet-VID are calculated on a clip basis not a frame basis
