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Robust Vision Challenge 2020 - Object Detection Devkit

Dataset Download

We provide a devkit to download, extract, and convert the challenge datasets into a unified format. This is done by first specifying the target root directory for all RVC datasets using an environment variable

export RVC_DATA_DIR=/path/to/rvc_dataroot

Now you can execute the download script download_obj_det.sh which will download most of the RVC datasets.

You need to manually register and download the Mapillary Vistas (Research Edition) dataset: https://www.mapillary.com/dataset/vistas

You will receive an email with download instructions. Save/Move the downloaded zip file into the folder ${RVC_DATA_DIR}/mvd.

After successfully downloading all datasets, execute this script to extract and delete clean up files: extract_and_cleanup.sh

Dataset remapping

RVC does not force you to remap the datasets in a certain way. We do provide a "best-effort" mapping, which can be a good starting point. This mapping will contain overlapping classes and some dataset entries might miss relevant labels (as they were annotated using different policies/mixed hierarchical levels). Combine and remap datasets by executing the script

remap_obj_det.sh

Dataset Format / Training

The above step creates a joint training and a separate joint validation json file in COCO Object Detection format (only bbox entries, without "segmentation" entries):

http://cocodataset.org/#format-data

The "file_name" tag of each image entry has been prepended with the relative path calculated from RVC_DATA_DIR. These files can directly be used in your object detector training framework.

Result Submission

This repo will be updated as soon as the submission support is ready. See robustvision.net for news.