Japan liaotian

README.md

@@ -13,7 +13,7 @@ size_categories:
 source_datasets:
 - original
 task_categories:
-- image-segmentation
+- unconditional-image-generation
 task_ids: []
 pretty_name: crello
 tags:
@@ -528,11 +528,6 @@ configs:
   - [Table of Contents](#table-of-contents)
   - [Dataset Description](#dataset-description)
     - [Dataset Summary](#dataset-summary)
-    - [Associated Projects and Papers](#associated-projects-and-papers)
-      - [LayerD: Decomposing Raster Graphic Designs into Layers](#layerd-decomposing-raster-graphic-designs-into-layers)
-      - [CanvasVAE: Learning to Generate Vector Graphic Documents (Original Context)](#canvasvae-learning-to-generate-vector-graphic-documents-original-context)
-    - [Usage (Loading the dataset)](#usage-loading-the-dataset)
-    - [Sample Usage (LayerD Data Preparation)](#sample-usage-layerd-data-preparation)
     - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
     - [Languages](#languages)
   - [Dataset Structure](#dataset-structure)
@@ -557,22 +552,17 @@ configs:
 
 ## Dataset Description
 
-The Crello dataset is a collection of raster graphic designs originally compiled for the study of vector graphic documents. It contains document meta-data such as canvas size and pre-rendered elements such as images or text boxes. The original templates were collected from [crello.com](https://crello.com) (now [create.vista.com](https://create.vista.com/)) and converted to a low-resolution format suitable for machine learning analysis. More recently, it has been used for research into decomposing raster graphic designs into layers, as presented in the LayerD paper.
-
-### Associated Projects and Papers
-
-#### LayerD: Decomposing Raster Graphic Designs into Layers
-- **Paper:** [LayerD: Decomposing Raster Graphic Designs into Layers](https://huggingface.co/papers/2509.25134)
-- **Project Page:** https://cyberagentailab.github.io/LayerD/
-- **Repository:** https://github.com/CyberAgentAILab/LayerD
-- **Point of Contact:** [Tomoyuki Suzuki](https://tomoyukun.github.io/biography/), Kang-Jun Liu, [Naoto Inoue](https://naoto0804.github.io/), [Kota Yamaguchi](https://sites.google.com/view/kyamagu)
-
-#### CanvasVAE: Learning to Generate Vector Graphic Documents (Original Context)
-- **Paper:** [CanvasVAE: Learning to Generate Vector Graphic Documents](https://arxiv.org/abs/2108.01249)
 - **Homepage:** [CanvasVAE github](https://github.com/CyberAgentAILab/canvas-vae)
+- **Repository:**
+- **Paper:** [CanvasVAE: Learning to Generate Vector Graphic Documents](https://arxiv.org/abs/2108.01249)
+- **Leaderboard:**
 - **Point of Contact:** [Kota Yamaguchi](https://github.com/kyamagu)
 
-### Usage (Loading the dataset)
+### Dataset Summary
+
+The Crello dataset is compiled for the study of vector graphic documents. The dataset contains document meta-data such as canvas size and pre-rendered elements such as images or text boxes. The original templates were collected from [crello.com](https://crello.com) (now [create.vista.com](https://create.vista.com/)) and converted to a low-resolution format suitable for machine learning analysis.
+
+### Usage
 
 ```python
 import datasets
@@ -580,20 +570,9 @@ import datasets
 dataset = datasets.load_dataset("cyberagent/crello", revision="5.0.0")
 ```
 
-### Sample Usage (LayerD Data Preparation)
-
-The LayerD project, which uses this dataset for training its top-layer matting module, provides a script to prepare the Crello dataset. You can convert the Crello dataset for this purpose using the following command from the LayerD repository:
-
-```bash
-uv run python ./tools/generate_crello_matting.py --output-dir </path/to/dataset> --inpainting --save-layers
-```
-
-> [!NOTE]
-> This script downloads [the Crello dataset](https://huggingface.co/datasets/cyberagent/crello) (<20GB) from Hugging Face. Please ensure you have a stable internet connection and sufficient disk space for the first run.
-
 ### Supported Tasks and Leaderboards
 
-The Crello dataset supports unsupervised document generation (as studied by CanvasVAE) and layer decomposition / image segmentation (as studied by LayerD).
+[CanvasVAE](https://arxiv.org/abs/2108.01249) studies unsupervised document generation.
 
 ### Languages
 
@@ -622,56 +601,54 @@ In the following, categorical fields are shown as `categorical` type, but the ac
 
 **Canvas attributes**
 
-| Field | Type | Shape | Description |
-| :------------ | :---------- | :------ | :-------------------------------------------------------------- |
-| id | string | () | Template ID from create.vista.com |
-| group | categorical | () | Broad design groups, such as social media posts or blog headers |
-| format | categorical | () | Detailed design formats, such as Instagram post or postcard |
-| category | categorical | () | Topic category of the design, such as holiday celebration |
-| canvas_width | int64 | () | Canvas pixel width |
-| canvas_height | int64 | () | Canvas pixel height |
-| length | int64 | () | Length of elements |
-| suitability | categorical | (None,) | List of display tags, only `mobile` tag exists |
-| keywords | string | (None,) | List of keywords associated to this template |
-| industries | categorical | (None,) | List of industry tags like `marketingAds` |
-| preview | image | () | Preview image of the template for convenience |
-| cluster_index | int64 | () | Cluster index used to split the dataset; only for debugging |
+| Field         | Type        | Shape   | Description                                                     |
+| ------------- | ----------- | ------- | --------------------------------------------------------------- |
+| id            | string      | ()      | Template ID from create.vista.com                               |
+| group         | categorical | ()      | Broad design groups, such as social media posts or blog headers |
+| format        | categorical | ()      | Detailed design formats, such as Instagram post or postcard     |
+| category      | categorical | ()      | Topic category of the design, such as holiday celebration       |
+| canvas_width  | int64       | ()      | Canvas pixel width                                              |
+| canvas_height | int64       | ()      | Canvas pixel height                                             |
+| length        | int64       | ()      | Length of elements                                              |
+| suitability   | categorical | (None,) | List of display tags, only `mobile` tag exists                  |
+| keywords      | string      | (None,) | List of keywords associated to this template                    |
+| industries    | categorical | (None,) | List of industry tags like `marketingAds`                       |
+| preview       | image       | ()      | Preview image of the template for convenience                   |
+| cluster_index | int64       | ()      | Cluster index used to split the dataset; only for debugging     |
 
 **Element attributes**
 
-| Field | Type | Shape | Description |
-| :------------ | :---------- | :----------- | :--------------------------------------------------------------- |
-| type | categorical | (None,) | Element type, such as vector shape, image, or text |
-| left | float32 | (None,) | Element left position |
-| top | float32 | (None,) | Element top position |
-| width | float32 | (None,) | Element width |
-| height | float32 | (None,) | Element height |
-| color | string | (None, None) | RGB color palette of the vector graphic element |
-| opacity | float32 | (None,) | Opacity in [0, 1] range |
-| image | image | (None,) | Pre-rendered preview of the element encoded in PNG format |
-| text | string | (None,) | Text content in UTF-8 encoding for text element |
-| font | categorical | (None,) | Font family name for text element |
-| font_size | float32 | (None,) | Font size (height) in pixels |
-| text_align | categorical | (None,) | Horizontal text alignment, left, center, right for text element |
-| angle | float32 | (None,) | Element rotation angle (degree) w.r.t. the center of the element |
-| font_bold | boolean | (None, None) | Character-wise flag to indicate bold font |
-| font_italic | boolean | (None, None) | Character-wise flag to indicate italic font |
-| text_color | string | (None, None) | Character-wise rgba color |
-| text_line | int64 | (None, None) | Character-wise index of line number |
-| capitalize | boolean | (None,) | Binary flag to capitalize letters |
-| line_height | float32 | (None,) | Scaling parameter to line height, default is 1.0 |
-| letter_spacing | float32 | (None,) | Adjustment parameter for letter spacing, default is 0.0 |
+| Field          | Type        | Shape        | Description                                                      |
+| -------------- | ----------- | ------------ | ---------------------------------------------------------------- |
+| type           | categorical | (None,)      | Element type, such as vector shape, image, or text               |
+| left           | float32     | (None,)      | Element left position                                            |
+| top            | float32     | (None,)      | Element top position                                             |
+| width          | float32     | (None,)      | Element width                                                    |
+| height         | float32     | (None,)      | Element height                                                   |
+| color          | string      | (None, None) | RGB color palette of the vector graphic element                  |
+| opacity        | float32     | (None,)      | Opacity in [0, 1] range                                          |
+| image          | image       | (None,)      | Pre-rendered preview of the element encoded in PNG format        |
+| text           | string      | (None,)      | Text content in UTF-8 encoding for text element                  |
+| font           | categorical | (None,)      | Font family name for text element                                |
+| font_size      | float32     | (None,)      | Font size (height) in pixels                                     |
+| text_align     | categorical | (None,)      | Horizontal text alignment, left, center, right for text element  |
+| angle          | float32     | (None,)      | Element rotation angle (degree) w.r.t. the center of the element |
+| font_bold      | boolean     | (None, None) | Character-wise flag to indicate bold font                        |
+| font_italic    | boolean     | (None, None) | Character-wise flag to indicate italic font                      |
+| text_color     | string      | (None, None) | Character-wise rgba color                                        |
+| text_line      | int64       | (None, None) | Character-wise index of line number                              |
+| capitalize     | boolean     | (None,)      | Binary flag to capitalize letters                                |
+| line_height    | float32     | (None,)      | Scaling parameter to line height, default is 1.0                 |
+| letter_spacing | float32     | (None,)      | Adjustment parameter for letter spacing, default is 0.0          |
 
 `left` and `top` can be negative because elements can be bigger than the canvas size.
 `text_line` indicates the index of the text line.
 For example, the following indicates that `Be` is in the first line and the rest in the next line.
-The newline character `
-` if present is ignored in rendering.
+The newline character `\n` if present is ignored in rendering.
 
 ```
 {
-  "text": "Be
-ambitious!",
+  "text": "Be\nambitious!",
   "text_line": [0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1],
 }
 ```
@@ -760,17 +737,6 @@ We do not re-distribute the original files as we are not allowed by terms.
       year={2021}
     }
 
-If you use the Crello dataset in work related to layer decomposition or the LayerD project, please also cite:
-
-```bibtex
-@inproceedings{suzuki2025layerd,
-  title={LayerD: Decomposing Raster Graphic Designs into Layers},
-  author={Suzuki, Tomoyuki and Liu, Kang-Jun and Inoue, Naoto and Yamaguchi, Kota},
-  booktitle={ICCV},
-  year={2025}
-}
-```
-
 ### Releases
 
 5.1.0: v5.1 release (Oct 31, 2024)
@@ -814,6 +780,7 @@ If you use the Crello dataset in work related to layer decomposition or the Laye
 
 1.0: v1 release (Aug 24, 2021)
 
+
 ### Contributions
 
 Thanks to [@kyamagu](https://github.com/kyamagu) for adding this dataset.