---
dataset_info:
  features:
    - name: source
      dtype: image
    - name: mask
      dtype: image
    - name: target
      dtype: image
    - name: caption
      dtype: string
    - name: category
      dtype: string
  splits:
    - name: train
      num_examples: 89927
    - name: validation
      num_examples: 4989
    - name: test
      num_examples: 5009
license: cc-by-nc-4.0
task_categories:
  - image-to-image
tags:
  - virtual-try-on
  - fashion
  - clothing
---

# OpenVTON

A large-scale virtual try-on dataset containing ~100K clothing image pairs with garment masks.

## Dataset Structure

Each sample contains:
- **source**: Garment image (clothing item)
- **mask**: Garment segmentation mask
- **target**: Person wearing the garment (ground truth)
- **caption**: Text description of the clothing
- **category**: Clothing category (e.g., pants, jeans, shirt)

## Splits

| Split | Samples |
|-------|---------|
| Train | 89,927 |
| Validation | 4,989 |
| Test | 5,009 |
| **Total** | **99,925** |

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("your_username/OpenVTON")
sample = dataset["train"][0]
sample["source"].show()  # garment image
sample["mask"].show()    # segmentation mask
sample["target"].show()  # person wearing garment
print(sample["caption"])
print(sample["category"])
```