---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: question
    dtype: string
  - name: answer
    sequence: int64
  splits:
  - name: valid
    num_bytes: 7094843893.125
    num_examples: 14631
  - name: train
    num_bytes: 140854221157.57
    num_examples: 289911
  download_size: 51389456693
  dataset_size: 147949065050.695
configs:
- config_name: default
  data_files:
  - split: valid
    path: data/valid-*
  - split: train
    path: data/train-*
license: cc-by-4.0
language:
- en
pretty_name: QA Patches Task Dataset
task_categories:
- image-text-to-text
- visual-question-answering
---
# Dataset Card for Patch-Based Visual Question Answering Dataset

## Dataset Details

### Dataset Description

This dataset contains approximately 305,000 triplets of `question`, `answer`, and `image` designed for patch-based visual reasoning tasks.  

A standard question in this dataset is formatted as follows:

> Image Grid: The image is divided into a 4x4 grid of 16 equal-sized patches. Patches are numbered sequentially from the top-left corner and moving right, then down to the next row.  
> Task: Identify the patch number(s) that contain a potted plant.  
> Response Format: Provide only the relevant patch number(s) as a list (e.g., [3], [5, 12], or [] if none are found).

The dataset is built on top of **COCO-2017**, from which object bounding boxes (bboxes) are used to generate questions and answers.

- **Curated by:** Yurii Potapov
- **Language(s) :** English
- **License:** Annotations and code: CC BY 4.0 (COCO), Images: Flickr Terms of Use

### Dataset Sources

- **Repository:** [Not yet published]
- **Paper:** [Not yet published]
- **Demo:** [More Information Needed]

## Uses

### Direct Use

- Training and evaluating **visual-language models (VLMs)** or other multimodal models.  
- Patch-based object detection and reasoning.  
- Research in **image question answering**, **visual reasoning**, and **multimodal representation learning**.

### Out-of-Scope Use

- Direct commercial redistribution of original COCO images without following Flickr Terms of Use.  
- Use cases where original images are required to be displayed in full, due to copyright restrictions.  

## Dataset Structure

- **question**: A textual description of the task referring to a 4x4 patch grid.  
- **answer**: List of integers representing the patch indices containing the target object(s).  
- **image**: Corresponding COCO-2017 image (PIL Image object or file path).  

The dataset contains no explicit splits; users can generate their own train/validation/test splits as needed.

## Dataset Creation

### Curation Rationale

The dataset was created to facilitate **patch-level visual question answering** and to improve the training of visual-language models using real-world images with structured spatial queries.

### Source Data

The dataset is based on COCO-2017 images and annotations. Bounding boxes from COCO are used to determine which patches contain specific objects (e.g., potted plants).

#### Data Collection and Processing

- Images are sourced from COCO-2017 (Flickr) respecting their Terms of Use.  
- Bounding boxes from COCO are used to automatically generate 4x4 grid questions.  
- Each question asks which patch(es) contain a specific object.  
- Answers are stored as lists of patch indices.  

#### Who are the source data producers?

Original images were contributed by Flickr users and annotated by the COCO Consortium.

### Annotations

#### Annotation process

Annotations (bounding boxes) are sourced from COCO-2017. Patch assignments and questions were automatically generated programmatically based on bounding box locations.

#### Who are the annotators?

Annotations are from COCO annotators; patch-level questions are generated automatically.

#### Personal and Sensitive Information

The dataset does **not contain personal or sensitive information**.

## Bias, Risks, and Limitations

- Images reflect the distribution and biases present in COCO-2017.  
- Models trained on this dataset may inherit biases from the original dataset.  
- Limited to the objects annotated in COCO-2017.  

### Recommendations

Users should be aware of the **copyright limitations of the original images** and provide attribution for COCO annotations. Use transformed or model-generated outputs rather than raw images for publication if possible.

## Glossary

- **Patch**: One of 16 equally sized blocks in a 4x4 grid over an image.  
- **VLM (Visual-Language Model)**: A model that learns joint representations of images and text.  

## Dataset Card Authors

Yurii Potapov

## Dataset Card Contact

yurii.a.potapov@gmail.com