Datasets:
File size: 1,349 Bytes
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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("RenxingIntelligence/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"])
```
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