Note: The data is on Azure Storage Blob, a SAS with Read permission is provided. Please append the following SAS at the end of each link to download:
?sp=r&st=2023-08-28T01:12:41Z&se=3023-08-28T09:12:41Z&sv=2022-11-02&sr=c&sig=6R1YmWluiXmPLsdVn1rDUpeBp2SYBMxDjc6KoKNlY8Q%3DWe 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 $DATA_DIRTASK_NAME could be coco_caption, coco_ir, vqa, GQA, nlvr2.
We provide pre-trained Oscar models of Bert-base and Bert-large structures, with the name starting with base and large, respectively.
wget https://biglmdiag.blob.core.windows.net/oscar/pretrained_models/$MODEL_NAME.zip
unzip $MODEL_NAME.zip -d $MODEL_DIRMODEL_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.
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>