|
Download README.md from kixlab/CANVAS: direct link, hf CLI and curl.
- Browser
- Download file 7.71 kB
-
https://huggingface.co/datasets/kixlab/CANVAS/resolve/main/README.md
- Command line
-
hf download hf://datasets/kixlab/CANVAS/README.md
-
curl -L -o README.md https://huggingface.co/datasets/kixlab/CANVAS/resolve/main/README.md
7.71 kB
| license: cc-by-4.0 | |
| language: | |
| - en | |
| tags: | |
| - art | |
| - design | |
| - agent | |
| - tool | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: replication | |
| path: "replication_gt/*.jsonl" | |
| - split: modification | |
| path: | |
| - "modification_gt/task-1/*.jsonl" | |
| - "modification_gt/task-2/*.jsonl" | |
| - "modification_gt/task-3/*.jsonl" | |
| <style> | |
| .figure-tag { | |
| display: inline-flex; | |
| align-items: center; | |
| justify-content: center; | |
| width: 20px; | |
| height: 20px; | |
| margin-right: 6px; | |
| margin-left: 2px; | |
| background: #000; | |
| color: #fff; | |
| font-weight: 700; | |
| font-size: 14px; | |
| line-height: 1; | |
| border-radius: 1px; | |
| vertical-align: middle; | |
| } | |
| </style> | |
| # CANVAS | |
| This repository contains the dataset accompanying the paper [CANVAS: A Benchmark for Vision-Language Models on Tool-Based UI Design (AAAI 2026)](https://canvas.kixlab.org/). | |
| CANVAS designed to evaluate a VLM's capability to generate a UI design with tool invocations in two tasks: <span class="figure-tag">A</span>**Design Replication** and <span class="figure-tag">B</span>**Design Modification**. | |
|  | |
| **A. Design Replication**. Single Tasks involving restoring (implementing) a given UI image as is. | |
| **B. Design Modification**. Multiple Tasks involving modifying or transforming existing UIs. | |
|  | |
| ## Dataset Statistics | |
| CANVAS contains 598 design tasks from 3,327 mobile UI designs across 30 categories. Each design includes an image and a JSON file representing the Figma node structure. This file organizes components (e.g., vector, text, rectangle) in a hierarchical tree with attributes like position, size, and color. | |
|  | |
| <span class="figure-tag">A</span>Frequency of the five most frequent UI design types, with other categories grouped. <span class="figure-tag">B</span>The distribution of node tree depth is similar across the replication and modification sets with a Gaussian-like pattern. <span class="figure-tag">C</span>The node count distribution is also similar across both sets. <span class="figure-tag">D</span>The skewed frequency of node types per design indicates common patterns in component usage. | |
| --- | |
| ## Directory Structure | |
| ``` | |
| canvas | |
| ├── modification_gt/ | |
| │ ├── task-1/ # Attribute Modification | |
| │ ├── task-2/ # Component Insertion | |
| │ └── task-3/ # Mode Change | |
| └── replication_gt/ # UI Replication | |
| ``` | |
| --- | |
| ## Modification Ground Truth (`modification_gt`) | |
| ### Task 1: Attribute Modification | |
| Consists of 5 sub-tasks: | |
| - Type 1: Fill Color Adjustment (20 examples) - `color_adjustment` | |
| - Type 2: Size Adjustment (20 examples) - `size_adjustment` | |
| - Type 3: Text Content Change (20 examples) - `text_content_change` | |
| - Type 4: Corner Radius Change (20 examples) - `corner_radius_change` | |
| - Type 5: Position Adjustment (20 examples) - `position_adjustment` | |
| #### File Structure | |
| Each task scenario consists of a "base" and "target" file pair: | |
| - **base**: UI design before modification | |
| - **target**: UI design after modification | |
| Each scenario comprises 8 files (4 for base, 4 for target): | |
| ``` | |
| {sub_task_type}-gid{id}-{target|base}.json // Full Figma data | |
| {sub_task_type}-gid{id}-{target|base}-meta.json // Metadata | |
| {sub_task_type}-gid{id}-{target|base}.svg // SVG | |
| {sub_task_type}-gid{id}-{target|base}.png // PNG | |
| ``` | |
| Example: `color_adjustment-gid1-base.json` | |
| #### Metadata Structure | |
| Each metadata file (`*-meta.json`) includes: | |
| - `url`: Source Figma file URL | |
| - `license`: License information (typically CC BY 4.0) | |
| - `node_id`: Figma node ID | |
| - `sub_task_type`: Sub-task type (e.g., "color_adjustment") | |
| - `instruction`: Text instruction describing the required modification | |
| ### Task 2: Component Insertion | |
| Adding a component to an existing UI. | |
| #### File Structure | |
| Each task scenario consists of a triplet of "base", "target", and "component" files: | |
| - **base**: UI design before modification | |
| - **target**: UI design after modification | |
| - **component**: The UI component being added | |
| Each scenario comprises 12 files (4 for base, 4 for target, 4 for component): | |
| ``` | |
| gid{id}-target.json // Full Figma data | |
| gid{id}-target-meta.json // Metadata | |
| gid{id}-target.svg // SVG | |
| gid{id}-target.png // PNG | |
| gid{id}-base.json // Full Figma data | |
| gid{id}-base-meta.json // Metadata | |
| gid{id}-base.svg // SVG | |
| gid{id}-base.png // PNG | |
| gid{id}-component.json // Full Figma data | |
| gid{id}-component-meta.json // Metadata | |
| gid{id}-component.svg // SVG | |
| gid{id}-component.png // PNG | |
| ``` | |
| Example: `gid1-base.json` | |
| #### Metadata Structure | |
| Each metadata file (`*-meta.json`) includes: | |
| - `url`: Source Figma file URL | |
| - `license`: License information (typically CC BY 4.0) | |
| - `node_id`: Figma node ID | |
| - `instruction`: Text instruction describing how to add the component | |
| ### Task 3: Mode Change | |
| Day & Night Screen State Change. | |
| Total of 100 examples (10 image groups x 10 pairs). | |
| #### File Structure | |
| Each task scenario consists of a "base" and "target" file pair: | |
| - **base**: UI design before modification | |
| - **target**: UI design after modification | |
| Each scenario comprises 8 files (4 for base, 4 for target): | |
| ``` | |
| gid{group_id}-{subindex}-target.json // Full Figma data | |
| gid{group_id}-{subindex}-target-meta.json // Metadata | |
| gid{group_id}-{subindex}-target.svg // SVG | |
| gid{group_id}-{subindex}-target.png // PNG | |
| gid{group_id}-{subindex}-base.json // Full Figma data | |
| gid{group_id}-{subindex}-base-meta.json // Metadata | |
| gid{group_id}-{subindex}-base.svg // SVG | |
| gid{group_id}-{subindex}-base.png // PNG | |
| ``` | |
| Example: `gid10-1-base.json` | |
| #### Metadata Structure | |
| Each metadata file (`*-meta.json`) includes: | |
| - `url`: Source Figma file URL | |
| - `license`: License information (typically CC BY 4.0) | |
| - `node_id`: Figma node ID | |
| - `gid`: Image group ID | |
| - `subindex`: Pair index within the image group (1-10) | |
| - `instruction`: Text instruction describing the required modification | |
| --- | |
| ## Replication Ground Truth (`replication_gt`) | |
| Tasks involving restoring (implementing) a given UI image as is. | |
| Total of 298 examples. | |
| #### File Structure | |
| In this dataset, there is no distinction between "base" and "target"; each UI design is an independent data point. | |
| Each data point consists of 4 files: | |
| ``` | |
| gid{group_id}-{index}.json // Full Figma data | |
| gid{group_id}-{index}-meta.json // Metadata | |
| gid{group_id}-{index}.svg // SVG | |
| gid{group_id}-{index}.png // PNG | |
| ``` | |
| Example: `gid1-5.json` | |
| #### Metadata Structure | |
| Each metadata file (`*-meta.json`) includes: | |
| - `url`: Source Figma file URL | |
| - `license`: License information (typically CC BY 4.0) | |
| - `node_id`: Figma node ID | |
| - `type_id`: UI type ID | |
| - `type_name`: UI category name (e.g., "Maps & Location") | |
| - `json_node_depth`: Depth of the Figma node tree | |
| - `json_node_count`: Total number of nodes | |
| - `json_node_type_count`: Count by node type (FRAME, GROUP, VECTOR, TEXT, etc.) | |
| - `difficulty`: Difficulty level (e.g., "standard") | |
| ## BibTex | |
| If you use this dataset, please cite: | |
| ``` | |
| @article{jeong2025canvas, | |
| title={CANVAS: A Benchmark for Vision-Language Models on Tool-Based User Interface Design}, | |
| author={Daeheon Jeong and Seoyeon Byun and Kihoon Son and Dae Hyun Kim and Juho Kim}, | |
| year={2025}, | |
| eprint={2511.20737}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CV}, | |
| url={https://arxiv.org/abs/2511.20737}, | |
| } | |
| ``` |