---
license: apache-2.0
---

# Vision-Language Pairs Dataset

This dataset contains metadata about image-text pairs from various popular vision-language datasets.

## Contents

- **vision_language_data/all_vision_language_images.csv**: Combined metadata for all images (75629 records)
- **vision_language_data/all_vision_language_captions.csv**: Combined captions for all images (86676 records)
- **dataset_statistics.csv**: Summary statistics for each dataset
- **category_distribution.csv**: Distribution of image categories across datasets
- **caption_length_distribution.csv**: Distribution of caption lengths
- **caption_style_distribution.csv**: Distribution of caption styles
- **category_caption_statistics.csv**: Caption statistics by category
- **vision_language_catalog.json**: Searchable catalog with sample image-caption pairs

## Datasets Included

- **COCO** (Common Objects in Context): COCO is a large-scale object detection, segmentation, and captioning dataset with multiple captions per image. (123287 images)
- **Flickr30K** (Flickr 30,000 Images): Flickr30K contains images collected from Flickr with 5 reference captions per image provided by human annotators. (31783 images)
- **Visual Genome** (Visual Genome): Visual Genome connects structured image concepts to language with detailed region descriptions and question-answer pairs. (108077 images)
- **Conceptual Captions** (Conceptual Captions): Conceptual Captions is a large-scale dataset of image-caption pairs harvested from the web and automatically filtered. (3300000 images)
- **CC3M** (Conceptual 3 Million): CC3M is a dataset of 3 million image-text pairs collected from the web, useful for vision-language pretraining. (3000000 images)
- **SBU Captions** (SBU Captioned Photo Dataset): The SBU dataset consists of 1 million images with associated captions collected from Flickr. (1000000 images)

## Fields Description

### Images Table
- **image_id**: Unique identifier for the image
- **dataset**: Source dataset name
- **image_url**: URL to the image (simulated)
- **primary_category**: Main content category
- **width**: Image width in pixels
- **height**: Image height in pixels
- **aspect_ratio**: Width divided by height
- **caption_count**: Number of captions for this image
- **license**: License under which the image is available

### Captions Table
- **caption_id**: Unique identifier for the caption
- **image_id**: ID of the associated image
- **dataset**: Source dataset name
- **text**: Caption text
- **language**: Caption language (default: en)
- **style**: Caption style (descriptive, short, or detailed)
- **length**: Number of characters in the caption
- **word_count**: Number of words in the caption

## Usage Examples

This metadata can be used for:

1. Analyzing the composition of vision-language datasets
2. Comparing caption characteristics across different datasets
3. Training and evaluating image captioning models
4. Studying linguistic patterns in image descriptions
5. Developing multimodal AI systems

## Data Generation Note

This dataset contains synthetic metadata that represents the structure and 
characteristics of actual vision-language pair collections, but the specific
image and caption details are generated for demonstration purposes.

Created: 2025-04-26


## Note:
## All files are packaged into a ZIP archive called vision_language_pairs_data.zip for easy download, with expected size in the 150-200MB range, making it suitable for research and educational purposes.