Update README.md

README.md

@@ -10,12 +10,7 @@ license:
 - cc-by-4.0
 multilinguality:
 - monolingual
-pretty_name: "**COYO** is a large-scale dataset that contains **image-text pairs**\
-  \ as well as many other **meta-attributes** to increase the usability to train various\
-  \ models. Our dataset follows the similar strategy in previous vision-and-language\
-  \ datasets, collecting many informative pairs of alt-text and its associated image\
-  \ in HTML documents. We expect COYO to be used to train popular large-scale foundation\
-  \ models \ncomplementary to other similar datasets."
+pretty_name: COYO-700M
 size_categories:
 - 100M<n<1B
 source_datasets:
@@ -25,12 +20,12 @@ tags:
 task_categories:
 - text-to-image
 - image-to-text
-- zero-shot-image-classification
+- zero-shot-classification
 task_ids:
 - image-captioning
 ---
 
-# Dataset Card for [Dataset Name]
+# Dataset Card for COYO-700M
 
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
@@ -59,63 +54,128 @@ task_ids:
 
 ## Dataset Description
 
-- **Homepage:**
-- **Repository:**
+- **Homepage:** [COYO homepage](https://kakaobrain.com/contents/?contentId=7eca73e3-3089-43cb-b701-332e8a1743fd)
+- **Repository:** [COYO repository](https://github.kakaocorp.com/large-scale/coyo-dataset)
 - **Paper:**
 - **Leaderboard:**
-- **Point of Contact:**
+- **Point of Contact:** [COYO email]([email protected])
 
 ### Dataset Summary
 
-[More Information Needed]
+**COYO-700M** is a large-scale dataset that contains **747M image-text pairs** as well as many other **meta-attributes** to increase the usability to train various models. Our dataset follows the similar strategy in previous vision-and-language datasets, collecting many informative pairs of alt-text and its associated image in HTML documents. We expect COYO to be used to train popular large-scale foundation models 
+complementary to other similar datasets. For more details on the data acquisition process, please refer to the technical paper to be released later.
 
 ### Supported Tasks and Leaderboards
 
-[More Information Needed]
+We empirically validated the quality of COYO dataset by re-implementing popular models such as [ALIGN](https://arxiv.org/abs/2102.05918), [unCLIP](https://arxiv.org/abs/2204.06125), and [ViT](https://arxiv.org/abs/2010.11929). 
+We trained these models on COYO-700M or its subsets from scratch, achieving competitive performance to the reported numbers or generated samples in the original papers. 
+Our pre-trained models and training codes will be released soon along with the technical paper.
 
 ### Languages
 
-[More Information Needed]
+The texts in the COYO-700M dataset consist of English.
 
 ## Dataset Structure
 
 ### Data Instances
 
-[More Information Needed]
+Each instance in COYO-700M represents single image-text pair information with meta-attributes:
+```
+{
+  'id': 841814333321,
+  'url': 'https://blog.dogsof.com/wp-content/uploads/2021/03/Image-from-iOS-5-e1614711641382.jpg',
+  'text': 'A Pomsky dog sitting and smiling in field of orange flowers',
+  'width': 1000,
+  'height': 988,
+  'image_phash': 'c9b6a7d8469c1959',
+  'text_length': 59,
+  'word_count': 11,
+  'num_tokens_bert': 13,
+  'num_tokens_gpt': 12,
+  'num_faces': 0,
+  'clip_similarity_vitb32': 0.4296875,
+  'clip_similarity_vitl14': 0.35205078125,
+  'nsfw_score_opennsfw2': 0.00031447410583496094,
+  'nsfw_score_gantman': 0.03298913687467575,
+  'watermark_score': 0.1014641746878624,
+  'aesthetic_score_laion_v2': 5.435476303100586
+}
+```
 
 ### Data Fields
 
-[More Information Needed]
+| name                     | type    | description                                                                                                                                                                                |
+|--------------------------|---------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| id                       | long    | Unique 64-bit integer ID generated by [monotonically_increasing_id()](https://spark.apache.org/docs/3.1.3/api/python/reference/api/pyspark.sql.functions.monotonically_increasing_id.html) |
+| url                      | string  | The image URL extracted from the `src` attribute of the `<img>` tag                                                                                                                        |
+| text                     | string  | The text extracted from the `alt` attribute of the `<img>` tag                                                                                                                             |
+| width                    | integer | The width of the image                                                                                                                                                                     |
+| height                   | integer | The height of the image                                                                                                                                                                    | 
+| image_phash              | string  | The [perceptual hash(pHash)](http://www.phash.org/) of the image                                                                                                                           |
+| text_length              | integer | The length of the text                                                                                                                                                                     |
+| word_count               | integer | The number of words seperated by spaces.                                                                                                                                                   |
+| num_tokens_bert          | integer | The number of tokens using [BertTokenizer](https://huggingface.co/docs/transformers/model_doc/bert#transformers.BertTokenizer)                                                             |
+| num_tokens_gpt           | integer | The number of tokens using [GPT2TokenizerFast](https://huggingface.co/docs/transformers/model_doc/gpt2#transformers.GPT2TokenizerFast)                                                     |
+| num_faces                | integer | The number of faces in the image detected by [SCRFD](https://insightface.ai/scrfd)                                                                                                         |
+| clip_similarity_vitb32   | float   | The cosine similarity between text and image(ViT-B/32) embeddings by [OpenAI CLIP](https://github.com/openai/CLIP)                                                                         |
+| clip_similarity_vitl14   | float   | The cosine similarity between text and image(ViT-L/14) embeddings by [OpenAI CLIP](https://github.com/openai/CLIP)                                                                         |
+| nsfw_score_opennsfw2     | float   | The NSFW score of the image by [OpenNSFW2](https://github.com/bhky/opennsfw2)                                                                                                              |
+| nsfw_score_gantman       | float   | The NSFW score of the image by [GantMan/NSFW](https://github.com/GantMan/nsfw_model)                                                                                                       | 
+| watermark_score          | float   | The watermark probability of the image by our internal model                                                                                                                               |
+| aesthetic_score_laion_v2 | float   | The aesthetic score of the image by [LAION-Aesthetics-Predictor-V2](https://github.com/christophschuhmann/improved-aesthetic-predictor)                                                    |
 
 ### Data Splits
 
-[More Information Needed]
+Data was not split, since the evaluation was expected to be performed on more widely used downstream task(s).
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-[More Information Needed]
+Similar to most vision-and-language datasets, our primary goal in the data creation process is to collect many pairs of alt-text and image sources in HTML documents crawled from the web. Therefore, We attempted to eliminate uninformative images or texts with minimal cost and improve our dataset's usability by adding various meta-attributes. Users can use these meta-attributes to sample a subset from COYO-700M and use it to train the desired model. For instance, the *num_faces* attribute could be used to make a subset like *COYO-Faces* and develop a privacy-preserving generative model.
 
 ### Source Data
 
 #### Initial Data Collection and Normalization
 
-[More Information Needed]
+We collected about 10 billion pairs of alt-text and image source in HTML documents in [CommonCrawl](https://commoncrawl.org/) from Oct. 2020 to Aug. 2021. and eliminated uninformative pairs through the image and/or text level filtering process with minimal cost.
+
+**Image Level**
+* Include all image formats that Pillow library can decode
+* Less than 5KB image size are dropped
+* Images with aspect ratio is greater than 3.0 are dropped
+* Images with min(width, height) < 200 are dropped
+* Images are dropped if the score of [OpenNSFW2](https://github.com/yahoo/open_nsfw) or [GantMan/NSFW](https://github.com/GantMan/nsfw_model) is higher than 0.5
+* Based on the image [pHash](http://www.phash.org/) value, we removed all duplicate images from external public datasets.
+    * ImageNet-1K/21K, Flickr-30K, MS-COCO, CC-3M, CC-12M
+
+**Text Level**
+* We collected only english text using [cld3](https://github.com/google/cld3)
+* Consecutive whitespace characters are replaced with a single whitespace and whitespace before and after the sentence are removed
+    * e.g. `"\n            \n                Load image into Gallery viewer, valentine&amp;#39;s day roses\n            \n" → "Load image into Gallery viewer, valentine&amp;#39;s day roses"`
+* Any text with a length of 5 or less has been dropped
+* Text that does not have a noun form has been dropped
+* Text less than 3 words or more than 256 words and text over 1000 words were dropped
+* All texts appearing more than 10 times have been dropped
+    * e.g. `“thumbnail for”, “image for”, “picture of”`
+
+**Image-Text Level**
+* Based on (image_phash, text), duplicated samples has been dropped
+    * Different text may exist for the same image URL.
 
 #### Who are the source language producers?
 
-[More Information Needed]
+[Common Crawl](https://commoncrawl.org/) is the data source for COYO-700M.
 
 ### Annotations
 
 #### Annotation process
 
-[More Information Needed]
+The dataset was built in a fully automated process that did not require human annotation.
 
 #### Who are the annotators?
 
-[More Information Needed]
+No human annotation
 
 ### Personal and Sensitive Information
 
@@ -129,11 +189,11 @@ task_ids:
 
 ### Discussion of Biases
 
-[More Information Needed]
+It will be described in a paper to be released soon.
 
 ### Other Known Limitations
 
-[More Information Needed]
+It will be described in a paper to be released soon.
 
 ## Additional Information