---
pretty_name: Vieutopia T2A Privacy Train v1
language:
- en
license: other
size_categories:
- 100K<n<1M
task_categories:
- text-to-image
task_ids:
- text-to-image-generation
annotations_creators:
- machine-generated
source_datasets:
- original
tags:
- text-to-image
- image-generation
- diffusion
- privacy-preserving
- synthetic
configs:
- config_name: samples
  data_files:
  - split: train
    path: data/samples/train/*.parquet
  - split: validation
    path: data/samples/validation/*.parquet
  - split: test
    path: data/samples/test/*.parquet
- config_name: iterations
  data_files:
  - split: train
    path: data/iterations/train/*.parquet
  - split: validation
    path: data/iterations/validation/*.parquet
  - split: test
    path: data/iterations/test/*.parquet
---

# Vieutopia T2A Privacy Train v1

## Dataset Summary
Privacy-safe text-to-image dataset repacked into Parquet shards with embedded image bytes.

- Scope: text-to-image outputs only
- Excluded: image-to-image pipelines (`pix2pix_*`, `pst_*`)
- Privacy: no raw task UUIDs, no user/device fields
- Storage format: parquet shards (`image` as binary bytes), no `image_path` dependency

## Splits
### samples
- train: 117572
- validation: 6532
- test: 6532
- total: 130636

### iterations
- train: 477440
- validation: 52256
- test: 52256
- total: 581952

## Schema
### samples config fields
- `sample_id` (string)
- `task_id_hash` (string)
- `prompt` (string)
- `negative_prompt` (string)
- `width` (int32)
- `height` (int32)
- `has_iteration` (bool)
- `iteration_count` (int32)
- `file_sha256` (string)
- `split` (string)
- `created_date` (string)
- `image` (binary image bytes)

### iterations config fields
- `sample_id` (string)
- `frame_idx` (int32)
- `split` (string)
- `image` (binary image bytes)

## Loading Example
```python
from datasets import load_dataset, Image

samples = load_dataset("quchenyuan/text-to-art-database", "samples")
samples = samples.cast_column("image", Image())

iterations = load_dataset("quchenyuan/text-to-art-database", "iterations")
iterations = iterations.cast_column("image", Image())
```