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license: apache-2.0 |
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--- |
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# Vision-Language Pairs Dataset |
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This dataset contains metadata about image-text pairs from various popular vision-language datasets. |
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## Contents |
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- **vision_language_data/all_vision_language_images.csv**: Combined metadata for all images (75629 records) |
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- **vision_language_data/all_vision_language_captions.csv**: Combined captions for all images (86676 records) |
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- **dataset_statistics.csv**: Summary statistics for each dataset |
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- **category_distribution.csv**: Distribution of image categories across datasets |
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- **caption_length_distribution.csv**: Distribution of caption lengths |
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- **caption_style_distribution.csv**: Distribution of caption styles |
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- **category_caption_statistics.csv**: Caption statistics by category |
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- **vision_language_catalog.json**: Searchable catalog with sample image-caption pairs |
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## Datasets Included |
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- **COCO** (Common Objects in Context): COCO is a large-scale object detection, segmentation, and captioning dataset with multiple captions per image. (123287 images) |
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- **Flickr30K** (Flickr 30,000 Images): Flickr30K contains images collected from Flickr with 5 reference captions per image provided by human annotators. (31783 images) |
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- **Visual Genome** (Visual Genome): Visual Genome connects structured image concepts to language with detailed region descriptions and question-answer pairs. (108077 images) |
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- **Conceptual Captions** (Conceptual Captions): Conceptual Captions is a large-scale dataset of image-caption pairs harvested from the web and automatically filtered. (3300000 images) |
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- **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) |
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- **SBU Captions** (SBU Captioned Photo Dataset): The SBU dataset consists of 1 million images with associated captions collected from Flickr. (1000000 images) |
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## Fields Description |
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### Images Table |
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- **image_id**: Unique identifier for the image |
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- **dataset**: Source dataset name |
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- **image_url**: URL to the image (simulated) |
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- **primary_category**: Main content category |
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- **width**: Image width in pixels |
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- **height**: Image height in pixels |
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- **aspect_ratio**: Width divided by height |
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- **caption_count**: Number of captions for this image |
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- **license**: License under which the image is available |
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### Captions Table |
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- **caption_id**: Unique identifier for the caption |
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- **image_id**: ID of the associated image |
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- **dataset**: Source dataset name |
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- **text**: Caption text |
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- **language**: Caption language (default: en) |
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- **style**: Caption style (descriptive, short, or detailed) |
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- **length**: Number of characters in the caption |
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- **word_count**: Number of words in the caption |
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## Usage Examples |
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This metadata can be used for: |
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1. Analyzing the composition of vision-language datasets |
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2. Comparing caption characteristics across different datasets |
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3. Training and evaluating image captioning models |
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4. Studying linguistic patterns in image descriptions |
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5. Developing multimodal AI systems |
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## Data Generation Note |
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This dataset contains synthetic metadata that represents the structure and |
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characteristics of actual vision-language pair collections, but the specific |
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image and caption details are generated for demonstration purposes. |
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Created: 2025-04-26 |
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## Note: |
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## 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. |
