Update README.md

README.md

@@ -52,8 +52,115 @@ dataset = load_dataset("google/imageinwords", token="YOUR_HF_ACCESS_TOKEN", name
 <li><a href="https://huggingface.co/spaces/google/imageinwords-explorer">Dataset-Explorer</a></li>
 
 
+## Dataset Description
 
+- **Homepage:** https://google.github.io/imageinwords/
+- **Point of Contact:** iiw-dataset@google.com
 
+### 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
+
+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 generated image description
+ - `metrics/Comprehensiveness`
+ - `metrics/Specificity`
+ - `metrics/Hallucination`
+ - `metrics/First few line(s) as tldr`
+ - `metrics/Human Like`
+
+DOCCI:
+ - `image`
+ - `image/url`
+ - `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
+DCI | 112
+DOCCI    | 100
+LocNar    | 1000
+CS3600    | 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
+
+```
+@inproceedings{Garg2024IIW,
+  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},
+  title         = {{ImageInWords: Unlocking Hyper-Detailed Image Descriptions}},
+  booktitle     = {arXiv},
+  year          = {2024}
+```