Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 174, in _generate_tables
                  df = pandas_read_json(f)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 791, in read_json
                  json_reader = JsonReader(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 905, in __init__
                  self.data = self._preprocess_data(data)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 917, in _preprocess_data
                  data = data.read()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 813, in read_with_retries
                  out = read(*args, **kwargs)
                File "/usr/local/lib/python3.9/codecs.py", line 322, in decode
                  (result, consumed) = self._buffer_decode(data, self.errors, final)
              UnicodeDecodeError: 'utf-8' codec can't decode byte 0xff in position 0: invalid start byte
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3422, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2187, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2391, in iter
                  for key, example in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1904, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 499, in _iter_arrow
                  for key, pa_table in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 346, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 177, in _generate_tables
                  raise e
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 151, in _generate_tables
                  pa_table = paj.read_json(
                File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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This dataset repackages a subset of [google/docci] images and descriptions for Mini-LLaVA training/inference. We only reorganized files and converted metadata to data/docci_converted.json. Original content and copyright remain with the DOCCI authors.

Attribution: Onoe et al., DOCCI: Descriptions of Connected and Contrasting Images, ECCV 2024.
Original dataset: google/docci (CC BY 4.0).

Changes from the original: file renaming, directory layout, and metadata JSON conversion.

Original README.md is shown below.


annotations_creators: - expert-generated - crowdsourced language: - en language_creators: - other license: - cc-by-4.0 multilinguality: - monolingual pretty_name: DOCCI size_categories: - 10K<n<100K source_datasets: - original tags: [] task_categories: - text-to-image - image-to-text task_ids: - image-captioning

Dataset Card for DOCCI

Dataset Summary

DOCCI (Descriptions of Connected and Contrasting Images) is a collection of images paired with detailed descriptions. The descriptions explain the key elements of the images, as well as secondary information such as background, lighting, and settings. The images are specifically taken to help assess the precise visual properties of images. DOCCI also includes many related images that vary in having key differences from the others. All descriptions are manually annotated to ensure they adequately distinguish each image from its counterparts.

Supported Tasks

Text-to-Image and Image-to-Text generation

Languages

English

Dataset Structure

Data Instances

{
    'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=1536x2048>,
    'example_id': 'qual_dev_00000',
    'description': 'An indoor angled down medium close-up front view of a real sized stuffed dog with white and black colored fur wearing a blue hard hat with a light on it. A couple inches to the right of the dog is a real sized black and white penguin that is also wearing a blue hard hat with a light on it. The dog is sitting, and is facing slightly towards the right while looking to its right with its mouth slightly open, showing its pink tongue. The dog and penguin are placed on a gray and white carpet, and placed against a white drawer that has a large gray cushion on top of it. Behind the gray cushion is a transparent window showing green trees on the outside.'
}

Data Fields

Name Explanation
image PIL.JpegImagePlugin.JpegImageFile
example_id The unique ID of an example follows this format: <SPLIT_NAME>_<EXAMPLE_NUMBER>.
description Text description of the associated image.

Data Splits

Dataset Train Test Qual Dev Qual Test
DOCCI 9,647 5,000 100 100
DOCCI-AAR 4,932 5,000 -- --

Dataset Creation

Curation Rationale

DOCCI is designed as an evaluation dataset for both text-to-image (T2I) and image-to-text (I2T) generation. Please see our paper for more details.

Source Data

Initial Data Collection

All images were taken by one of the authors and their family.

Annotations

Annotation process

All text descriptions were written by human annotators. We do not rely on any automated process in our data annotation pipeline. Please see Appendix A of our paper for details about image curation.

Personal and Sensitive Information

We manually reviewed all images for personally identifiable information (PII), removing some images and blurring detected faces, phone numbers, and URLs to protect privacy. For text descriptions, we instructed annotators to exclude any PII, such as people's names, phone numbers, and URLs. After the annotation phase, we employed automatic tools to scan for PII, ensuring the descriptions remained free of such information.

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Licensing Information

CC BY 4.0

Citation Information

@inproceedings{OnoeDocci2024,
  author        = {Yasumasa Onoe and Sunayana Rane and Zachary Berger and Yonatan Bitton and Jaemin Cho and Roopal Garg and
    Alexander Ku and Zarana Parekh and Jordi Pont-Tuset and Garrett Tanzer and Su Wang and Jason Baldridge},
  title         = {{DOCCI: Descriptions of Connected and Contrasting Images}},
  booktitle     = {ECCV},
  year          = {2024}
}
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