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(The following contents are from [the ViLT repo](https://github.com/dandelin/ViLT/blob/master/DATA.md).)
# Dataset Preparation
We utilize seven datsets: Google Conceptual Captions (GCC), Stony Brook University Captions (SBU), Visual Genome (VG), COCO Captions (COCO), Flickr 30K Captions (F30K), Visual Question Answering v2 (VQAv2), and Natural Language for Visual Reasoning 2 (NLVR2).
We do not distribute datasets because of the license issue.
Please download the datasets by yourself.
We use `pyarrow` to serialize the datasets, conversion scripts are located in `vilt/utils/write_*.py`.
Please organize the datasets as follows and run `make_arrow` functions to convert the dataset to pyarrow binary file.
## GCC
https://ai.google.com/research/ConceptualCaptions/download
GCC provides tuples of image url and caption, note that a quite portion of the urls are unaccessible now.
Write your own download script and organize the dataset as following structure.
root
βββ images_train
β βββ 0000 # First four letters of image name
β β βββ 0000000 # Image Binary
β β βββ 0000001
β β βββ ...
β βββ 0001
β β βββ 0001000
β β βββ 0001001
β β βββ ...
β βββ ...
βββ images_val
β βββ 0000
β β βββ ...
β βββ ...
βββ train_annot.json # List of (image_file_path, caption) tuple
βββ val_annot.json # List of (image_file_path, caption) tuple
```python
from vlmo.utils.write_conceptual_caption import make_arrow
make_arrow(root, arrows_root)
```
## SBU
http://www.cs.virginia.edu/~vicente/sbucaptions/
Similar to GCC, SBU also provides tuples of image url and caption, and also a quite portion of the urls are unaccessible now.
Write your own download script and organize the dataset as following structure.
root
βββ images_train
β βββ 0000 # First four letters of image name
β β βββ 0000000 # Image Binary
β β βββ 0000001
β β βββ ...
β βββ 0001
β β βββ 0001000
β β βββ 0001001
β β βββ ...
β βββ ...
βββ annot.json # List of (image_file_path, caption) tuple
```python
from vlmo.utils.write_sbu import make_arrow
make_arrow(root, arrows_root)
```
## VG
http://visualgenome.org/api/v0/api_home.html
Download [image part1](https://cs.stanford.edu/people/rak248/VG_100K_2/images.zip), [image part2](https://cs.stanford.edu/people/rak248/VG_100K_2/images2.zip) and [region descriptions](http://visualgenome.org/static/data/dataset/region_descriptions.json.zip)
root
βββ images
β βββ VG_100K
β β βββ 10.jpg
β β βββ 107899.jpg
β β βββ ...
β βββ VG_100K_2
β β βββ 1.jpg
β β βββ 100.jpg
β β βββ ...
β βββ ...
βββ annotations
βββ region_descriptions.json
```python
from vlmo.utils.write_vg import make_arrow
make_arrow(root, arrows_root)
```
## COCO
https://cocodataset.org/#download
Download [2014 train images](http://images.cocodataset.org/zips/train2014.zip), [2014 val images](http://images.cocodataset.org/zips/val2014.zip) and [karpathy split](https://cs.stanford.edu/people/karpathy/deepimagesent/caption_datasets.zip)
root
βββ train2014
β βββ COCO_train2014_000000000009.jpg
| βββ ...
βββ val2014
| βββ COCO_val2014_000000000042.jpg
| βββ ...
βββ karpathy
βββ dataset_coco.json
```python
from vlmo.utils.write_coco_karpathy import make_arrow
make_arrow(root, arrows_root)
```
## F30K
http://bryanplummer.com/Flickr30kEntities/
Sign [flickr images request form](https://forms.illinois.edu/sec/229675) and download [karpathy split](https://cs.stanford.edu/people/karpathy/deepimagesent/caption_datasets.zip)
root
βββ flickr30k-images
β βββ 1000092795.jpg
| βββ ...
βββ karpathy
βββ dataset_flickr30k.json
```python
from vlmo.utils.write_f30k_karpathy import make_arrow
make_arrow(root, arrows_root)
```
## VQAv2
https://visualqa.org/download.html
Download COCO [2014 train images](http://images.cocodataset.org/zips/train2014.zip), [2014 val images](http://images.cocodataset.org/zips/val2014.zip), [2015 test images](http://images.cocodataset.org/zips/test2015.zip), annotations ([train](https://s3.amazonaws.com/cvmlp/vqa/mscoco/vqa/v2_Annotations_Train_mscoco.zip), [val](https://s3.amazonaws.com/cvmlp/vqa/mscoco/vqa/v2_Annotations_Val_mscoco.zip)), and questions ([train](https://s3.amazonaws.com/cvmlp/vqa/mscoco/vqa/v2_Questions_Train_mscoco.zip), [val](https://s3.amazonaws.com/cvmlp/vqa/mscoco/vqa/v2_Questions_Val_mscoco.zip), [test](https://s3.amazonaws.com/cvmlp/vqa/mscoco/vqa/v2_Questions_Test_mscoco.zip))
root
βββ train2014
β βββ COCO_train2014_000000000009.jpg
| βββ ...
βββ val2014
| βββ COCO_val2014_000000000042.jpg
| βββ ...
βββ test2015
| βββ COCO_test2015_000000000001.jpg
| βββ ...
βββ v2_OpenEnded_mscoco_train2014_questions.json
βββ v2_OpenEnded_mscoco_val2014_questions.json
βββ v2_OpenEnded_mscoco_test2015_questions.json
βββ v2_OpenEnded_mscoco_test-dev2015_questions.json
βββ v2_mscoco_train2014_annotations.json
βββ v2_mscoco_val2014_annotations.json
```python
from vlmo.utils.write_vqa import make_arrow
make_arrow(root, arrows_root)
```
## NLVR2
Clone the [repository](https://github.com/lil-lab/nlvr) and sign the [request form](https://goo.gl/forms/yS29stWnFWzrDBFH3) to download the images.
root
βββ images/train
β βββ 0
β β βββ train-10108-0-img0.png
β β βββ ...
β βββ 1
β β βββ train-10056-0-img0.png
β β βββ ...
β βββ ...
βββ dev
β βββ dev-0-0-img0.png
| βββ ...
βββ test1
β βββ test1-0-0-img0.png
| βββ ...
βββ nlvr
βββ nlvr2
βββ README.md
```python
from vlmo.utils.write_nlvr2 import make_arrow
make_arrow(root, arrows_root)
```
## WikiBK (Text only data)
```python
from vlmo.utils.write_wikibk import make_arrow
make_arrow(root, arrows_root)
```
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