---
title: PrismLayersPro
canonical_url: "https://www.modelscope.cn/datasets/artplus/PrismLayersPro"
md_url: "https://www.modelscope.cn/datasets/artplus/PrismLayersPro.md"
repository: artplus/PrismLayersPro
last_updated: 2026-01-10
license: apache-2.0
storage_size: "99 GB"
downloads: 5638
stars: 5
---

# PrismLayersPro

> PrismLayersPro - artplus 在 ModelScope 开源的数据集。PrismLayers: Open Data for High-Quality Multi-Layer Transparent Image Generative Models

artplus/PrismLayersPro 是 ModelScope 魔搭社区上的数据集，存储大小 99 GB，采用 apache-2.0 许可。

- **Repository**: artplus/PrismLayersPro
- **License**: apache-2.0
- **Storage size**: 99 GB
- **Downloads**: 5638
- **Stars**: 5
- **Last updated**: 2026-01-10

Source: https://www.modelscope.cn/datasets/artplus/PrismLayersPro

---

# PrismLayers: Open Data for High-Quality Multi-Layer Transparent Image Generative Models

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/681f211189050843b62d602d/UHqd3ireAfXsMNppMce0X.jpeg)

We introduce **PrismLayersPro**, a 20K high-quality multi-layer transparent image dataset with rewritten style captions and human filtering.
**PrismLayersPro** is curated from our 200K dataset, **PrismLayers**, generated via MultiLayerFLUX.

### Dataset Structure

#### 📑 Dataset Splits (by Style)

The PrismLayersPro dataset is divided into 21 splits based on visual **style categories**.  
Each split contains images sharing a consistent aesthetic (e.g., `toy`, `ink`, `anime`) and can be accessed individually via the `split` argument in the `load_dataset` function.

| Style               | # Samples |
| ------------------- | --------- |
| 3D                  | 313       |
| Pokemon             | 830       |
| anime               | 717       |
| cartoon             | 943       |
| doodle_art          | 1065      |
| furry               | 1038      |
| ink                 | 1155      |
| kid_crayon_drawing  | 1001      |
| line_draw           | 1221      |
| melting_gold        | 946       |
| melting_silver      | 1532      |
| metal_textured      | 747       |
| neon_graffiti       | 527       |
| papercut_art        | 848       |
| pixel_art           | 830       |
| pop_art             | 782       |
| sand_painting       | 929       |
| steampunk           | 857       |
| toy                 | 1627      |
| watercolor_painting | 875       |
| wood_carving        | 1263      |
| total               | 20046     |

Below we show the structure of a single data sample from one style-specific split (e.g., `toy`).

Each image is composed of multiple RGBA layers, each with its own caption and layout information.

```
Example structure of a single sample (supports up to 50 layers):

{
  "id": "sample_000001",
  "style_category": "toy",
  "whole_caption": "A colorful toy robot in a futuristic setting.",
  "whole_image": <PIL.Image (RGBA)>,
  "base_caption": "Futuristic neon-lit city background.",
  "base_image": <PIL.Image (RGBA)>,
  "layer_count": 6,  # actual number of layers in this sample

  # Repeated layer fields for up to 50 layers
  "layer_00": <PIL.Image (RGBA)>,
  "layer_00_caption": "Robot head with red visor",
  "layer_00_box": [x, y, w, h],
  "layer_00_width_dst": 256,
  "layer_00_height_dst": 256,

  "layer_01": <PIL.Image (RGBA)>,
  "layer_01_caption": "Robot body with silver armor",
  "layer_01_box": [x, y, w, h],
  "layer_01_width_dst": 256,
  "layer_01_height_dst": 256,

  ...

  "layer_49": <PIL.Image (RGBA)>,
  "layer_49_caption": "Shadow overlay with transparent gradient",
  "layer_49_box": [x, y, w, h],
  "layer_49_width_dst": 128,
  "layer_49_height_dst": 128
}
```

### Dataset Stats

The figure below provides an overview of the dataset statistics.

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/681f211189050843b62d602d/c-63ILQddVgBl1DXhRcBp.jpeg)

## Load the dataset

<!-- Address questions around how the dataset is intended to be used. -->

To load the dataset, install the library `datasets` with `pip install datasets`. Then,

```
from datasets import load_dataset

dataset = load_dataset("artplus/PrismLayersPro", split="3D")
```

to download and load the style `3D`, for example.

# Citation

```text
@article{chen2025prismlayers,
  title={PrismLayers: Open Data for High-Quality Multi-Layer Transparent Image Generative Models},
  author={Chen, Junwen and Jiang, Heyang and Wang, Yanbin and Wu, Keming and Li, Ji and Zhang, Chao and Yanai, Keiji and Chen, Dong and Yuan, Yuhui},
  journal={arXiv preprint arXiv:2505.22523},
  year={2025}
}
```