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We provide guidance for preparing the data used by GLIP. Note that not all data are needed for a specific experiments. Please check the Required Data fields in README to download necessary data. All data should by placed under the DATASET folder.

COCO

Download the original COCO data into DATASET/coco folder. The contents should be organized as follows:

train2017
DATASET/coco/train2017
DATASET/coco/annotations/instances_train2017.json
val2017
DATASET/coco/val2017
DATASET/coco/annotations/instances_val2017.json
test2017
DATASET/coco/test2017
DATASET/coco/annotations/image_info_test-dev2017.json
train2014
DATASET/coco/train2014

LVIS

LVIS use the same images as COCO. Thus prepare the COCO images first.

DATASET/coco

Download the following annotation files:

"wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/coco/annotations/lvis_v1_minival_inserted_image_name.json -O DATASET/coco/annotations/lvis_v1_minival_inserted_image_name.json"
"wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/coco/annotations/lvis_od_val.json -O coco/annotations/lvis_od_val.json"

Object Detection in the Wild (ODinW)

Please see the "ODinW / Custom Dataset Evaluation" section in README.md for preparing the Aquarium dataset. We will release all the data in ODinW in the next update.

Objects365

We store Objects365 data in the TSV format. Please see link for a description of the TSV format. We provide the annotation files:

wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/Objects365/objects365_train_vgoiv6.cas2000.yaml -O DATASET/Objects365/objects365_train_vgoiv6.cas2000.yaml
wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/Objects365/train.label.tsv -O DATASET/Objects365/train.label.tsv
wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/Objects365/train.label.linelist.cas.2000.tsv -O DATASET/Objects365/train.label.linelist.cas.2000.tsv
wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/Objects365/train.label.lineidx -O DATASET/Objects365/train.label.lineidx
wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/Objects365/train.hw.tsv -O DATASET/Objects365/train.hw.tsv
wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/Objects365/train.hw.lineidx -O DATASET/Objects365/train.hw.lineidx
wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/Objects365/object365_vgoiv6_class2ind.json -O DATASET/Objects365/object365_vgoiv6_class2ind.json

We cannot host the image data. Please download the original image data and organize them into DATASET/Objects365/images.tsv and DATASET/Objects365/images.lineidx.

Flickr30K

Download the Flickr30K images from Link and put them under DATASET/flickr30k/flickr30k_images/. Download the MDETR annotations and put them under DATASET/mdetr_annotations/. The dataset structure should look like:

DATASET/flickr30k/flickr30k_images/
DATASET/mdetr_annotations/final_flickr_separateGT_*

MixedGrounding

This is the grounding dataset curated by MDETR. Please prepare the COCO train2014 data and put them under DATASET/coco/train2014. Prepare the GQA images and put them under DATASET/gqa/images/.

Then download the annotation files. The original MDETR annotation file contains COCO images; we provide a version without COCO images: wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/mdetr_annotations/final_mixed_train_no_coco.json -O DATASET/mdetr_annotations/final_mixed_train_no_coco.json.

The dataset structure should look like:

"DATASET/coco/train2014" 
"DATASET/gqa/images"
"DATASET/mdetr_annotations/final_mixed_train_no_coco.json",

GCC

Goolge conceptual captions with pseudo-grounding annotations. To be released in the next update.