DOWNLOAD.md

Download

Datasets

We provide the extracted image region features, object tags, and the original text annotations for each downstream tasks.

wget https://biglmdiag.blob.core.windows.net/oscar/datasets/$TASK_NAME.zip
unzip $TASK_NAME.zip -d $DATA_DIR

TASK_NAME could be coco_caption, coco_ir, vqa, GQA, nlvr2.

Pre-trained Models

We provide pre-trained Oscar models of Bert-base and Bert-large structures, with the name starting with base and large, respectively.

wget https://biglmdiag.blob.core.windows.net/oscar/pretrained_models/$MODEL_NAME.zip
unzip $MODEL_NAME.zip -d $MODEL_DIR

MODEL_NAME could be base-vg-labels, large-vg-labels, base-oid-labels, base-no-labels.

The models are trained with both image region features and object tags. The image region features are extracted by the Faster R-CNN with ResNet-101, using object and attribute annotations from Visual Genome. The object tags are from: 1) the same VisualGenome model, named as -vg-labels. Or, 2) the model trained on object annotations from Open Images V5. named as -oid-labels. Or, 3) no object tags provied, serving as baseline, named as -no-labels.

Note

It is recommended to download large files with AzCopy for faster speed. AzCopy executable tools can be downloaded here. Decompress the tar file and put the executable in any path. To download from any URL above, the command is:

path/to/azcopy copy <URL> <local_path>

# for example, downloading coco_caption.zip
path/to/azcopy copy https://biglmdiag.blob.core.windows.net/oscar/datasets/coco_caption.zip <local_path>