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DATASET.md

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DATASET

The following is adapted from Danfei Xu and neural-motifs.

Note that our codebase intends to support attribute-head too, so our VG-SGG.h5 and VG-SGG-dicts.json are different with their original versions in Danfei Xu and neural-motifs. We add attribute information and rename them to be VG-SGG-with-attri.h5 and VG-SGG-dicts-with-attri.json. The code we use to generate them is located at datasets/vg/generate_attribute_labels.py. Although, we encourage later researchers to explore the value of attribute features, in our paper "Unbiased Scene Graph Generation from Biased Training", we follow the conventional setting to turn off the attribute head in both detector pretraining part and relationship prediction part for fair comparison, so does the default setting of this codebase.

Download:

  1. Download the VG images part1 (9 Gb) part2 (5 Gb). Extract these images to the file datasets/vg/VG_100K. If you want to use other directory, please link it in DATASETS['VG_stanford_filtered']['img_dir'] of maskrcnn_benchmark/config/paths_catelog.py.
  2. Download the scene graphs and extract them to datasets/vg/VG-SGG-with-attri.h5, or you can edit the path in DATASETS['VG_stanford_filtered_with_attribute']['roidb_file'] of maskrcnn_benchmark/config/paths_catalog.py.