Dataset: HDR annotated dataset
Dataset processing: https://github.com/MASSIVE-VR-Laboratory/dataset_processing
Supervised object detection requires large scale annotated datasets. However, creating large HDR annotated datasets is a major challenge due to the following reasons:
- There are no large scale HDR datasets publicly available.
- Existing annotation tools do not support HDR images (so there is no way to open these files)
- Video annotation is highly time consuming and resource intensive.
Therefore, to mitigate the above-mentioned challenges, we first shortlisted a set of seven HDR video sequences. From the video sequences, we carefully curated a total of 4080 images which contain some images from Google HDR dataset. The HDR images were then tone-mapped using a scene reproduction operator to create 8-bit representations of the HDR images. The tone-mapped images were then used to annotate the HDR dataset using the “labelimg” annotation tool. The tone-mapped images were discarded to produce a clean dataset with HDR images along with the annotations. Finally, the annotations were converted to COCO JSON format for ease of training and testing.