Datasets:

google
/

imageinwords

@@ -1,170 +1 @@
----
-annotations_creators:
-- expert-generated
-- crowdsourced
-license: cc-by-4.0
-task_categories:
-- image-to-text
-- text-to-image
-- object-detection
-language:
-- en
-size_categories:
-- 1K<n<10K
-tags:
-- iiw
-- imageinwords
-- image-descriptions
-- image-captions
-- detailed-descriptions
-- hyper-detailed-descriptions
-- object-descriptions
-- object-detection
-- object-labels
-pretty_name: ImageInWords
-multilinguality:
-- monolingual
----
-<h2>ImageInWords: Unlocking Hyper-Detailed Image Descriptions</h2>
-Please visit the [webpage](https://google.github.io/imageinwords) for all the information about the IIW project, data downloads, visualizations, and much more.
-<img src="https://github.com/google/imageinwords/blob/main/static/images/Abstract/1_white_background.png?raw=true">
-<img src="https://github.com/google/imageinwords/blob/main/static/images/Abstract/2_white_background.png?raw=true">
-Please reach out to [email protected] for thoughts/feedback/questions/collaborations.
-<h3>&#129303;Hugging Face&#129303;</h3>
-<li><a href="https://huggingface.co/datasets/google/imageinwords">Dataset</a></li>
-```python
-from datasets import load_dataset
-# `name` can be one of: IIW-400, DCI_Test, DOCCI_Test, CM_3600, LocNar_Eval
-# refer: https://github.com/google/imageinwords/tree/main/datasets
-dataset = load_dataset('google/imageinwords', token=None, name="IIW-400", trust_remote_code=True)
-```
-<li><a href="https://huggingface.co/spaces/google/imageinwords-explorer">Dataset-Explorer</a></li>
-## Dataset Description
-- **Paper:** [arXiv](https://arxiv.org/abs/2405.02793)
-- **Homepage:** https://google.github.io/imageinwords/
-- **Point of Contact:** [email protected]
-- **Dataset Explorer:** [ImageInWords-Explorer](https://huggingface.co/spaces/google/imageinwords-explorer)
-### Dataset Summary
-ImageInWords (IIW), a carefully designed human-in-the-loop annotation framework for curating hyper-detailed image descriptions and a new dataset resulting from this process.
-We validate the framework through evaluations focused on the quality of the dataset and its utility for fine-tuning with considerations for readability, comprehensiveness, specificity, hallucinations, and human-likeness.
-This Data Card describes a mixture of human annotated and machine generated data intended to help create and capture rich, hyper-detailed image descriptions.
-IIW dataset has two parts: human annotations and model outputs. The main purposes of this dataset are:
-  1) to provide samples from SoTA human authored outputs to promote discussion on annotation guidelines to further improve the quality
-  2) to provide human SxS results and model outputs to promote development of automatic metrics to mimic human SxS judgements.
-### Supported Tasks
-Text-to-Image, Image-to-Text, Object Detection
-### Languages
-English
-## Dataset Structure
-### Data Instances
-### Data Fields
-For details on the datasets and output keys, please refer to our [GitHub data](https://github.com/google/imageinwords/tree/main/datasets) page inside the individual folders.
-IIW:
- - `image/key`
- - `image/url`
- - `IIW`: Human generated image description
- - `IIW-P5B`: Machine generated image description
- - `iiw-human-sxs-gpt4v` and `iiw-human-sxs-iiw-p5b`: human SxS metrics
-   - metrics/Comprehensiveness
-   - metrics/Specificity
-   - metrics/Hallucination
-   - metrics/First few line(s) as tldr
-   - metrics/Human Like
-DCI:
- - `image`
- - `image/url`
- - `ex_id`
- - `IIW`: Human authored image description
- - `metrics/Comprehensiveness`
- - `metrics/Specificity`
- - `metrics/Hallucination`
- - `metrics/First few line(s) as tldr`
- - `metrics/Human Like`
-DOCCI:
- - `image`
- - `image/thumbnail_url`
- - `IIW`: Human generated image description
- - `DOCCI`: Image description from DOCCI
- - `metrics/Comprehensiveness`
- - `metrics/Specificity`
- - `metrics/Hallucination`
- - `metrics/First few line(s) as tldr`
- - `metrics/Human Like`
-LocNar:
- - `image/key`
- - `image/url`
- - `IIW-P5B`: Machine generated image description
-CM3600:
- - `image/key`
- - `image/url`
- - `IIW-P5B`: Machine generated image description
-Please note that all fields are string.
-### Data Splits
-Dataset | Size
----| ---:
-IIW-400     | 400
-DCI_Test | 112
-DOCCI_Test    | 100
-LocNar_Eval    | 1000
-CM_3600    | 1000
-### Annotations
-#### Annotation process
-Some text descriptions were written by human annotators and some were generated by machine models.
-The metrics are all from human SxS.
-### Personal and Sensitive Information
-The images that were used for the descriptions and the machine generated text descriptions are checked (by algorithmic methods and manual inspection) for S/PII, pornographic content, and violence and any we found may contain such information have been filtered.
-We asked that human annotators use an objective and respectful language for the image descriptions.
-### Licensing Information
-CC BY 4.0
-### Citation Information
-```
-@misc{garg2024imageinwords,
-      title={ImageInWords: Unlocking Hyper-Detailed Image Descriptions},
-      author={Roopal Garg and Andrea Burns and Burcu Karagol Ayan and Yonatan Bitton and Ceslee Montgomery and Yasumasa Onoe and Andrew Bunner and Ranjay Krishna and Jason Baldridge and Radu Soricut},
-      year={2024},
-      eprint={2405.02793},
-      archivePrefix={arXiv},
-      primaryClass={cs.CV}
-}
-```


1	+ یک عکس زیبا کنار ساحل```