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The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 299, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 83, in _split_generators
                  raise ValueError(
              ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 353, in get_dataset_split_names
                  info = get_dataset_config_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 304, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Vis-IR: Unifying Search With Visualized Information Retrieval

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Overview

VIRA (Vis-IR Aggregation), a large-scale dataset comprising a vast collection of screenshots from diverse sources, carefully curated into captioned and questionanswer formats.

Statistics

There are three types of data in VIRA: caption data, query-to-screenshot (q2s) data, and screenshot+query-to-screenshot (sq2s) data. The table below provides a detailed breakdown of the data counts for each domain and type.

image/png

Organization Structure

The dataset is organized in the following structure:

Domain/  
β”œβ”€β”€ caption.jsonl: a screenshot image path and its corresponding caption 
β”œβ”€β”€ q2s.jsonl: a query, a positive screenshot and eight negative screenshots
β”œβ”€β”€ sq2s.jsonl: a query, a query screenshot, a positive screenshot and eight negative screenshots
β”œβ”€β”€ Domain.tar.gz.partaa 
β”œβ”€β”€ Domain.tar.gz.partab
β”œβ”€β”€ Domain.tar.gz.partac
... 

Download Images

We have released all the images. Due to the large total size, they are split into multiple parts. You can download the images using the script below:

#!/bin/bash

FOLDER="Chart" # β€œNews” "PDFA" "Papers" "Product" "Readmes" "Wiki"
BASE_URL="https://huggingface.co/datasets/marsh123/VIRA/resolve/main/${FOLDER}"

mkdir -p "$FOLDER"
cd "$FOLDER"

for first in {a..z}; do
  for second in {a..z}; do
    part="${first}${second}"
    file="${FOLDER}.tar.gz.part${part}"
    url="${BASE_URL}/${file}"

    echo "Trying: $url"
    if curl --output /dev/null --silent --head --fail "$url"; then
      wget --continue "$url"
    else
      echo "No more parts after part${part}"
      break 2  
    fi
  done
done

echo "Merging parts..."
cat "${FOLDER}.tar.gz.part"* > "${FOLDER}.tar.gz"

echo "Extracting..."
tar -xzvf "${FOLDER}.tar.gz"

echo "Cleaning up..."
rm "${FOLDER}.tar.gz.part"*
rm "${FOLDER}.tar.gz"

echo "βœ… Done!"

License

VIRA is licensed under the MIT License.

Citation

If you find this dataset useful, please cite:

@article{liu2025any,
  title={Any Information Is Just Worth One Single Screenshot: Unifying Search With Visualized Information Retrieval},
  author={Liu, Ze and Liang, Zhengyang and Zhou, Junjie and Liu, Zheng and Lian, Defu},
  journal={arXiv preprint arXiv:2502.11431},
  year={2025}
}
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