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--- |
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license: apache-2.0 |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: accessibility |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 653490753.125 |
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num_examples: 1127 |
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download_size: 618157948 |
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dataset_size: 653490753.125 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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task_categories: |
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- object-detection |
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language: |
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- en |
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tags: |
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- accessibility |
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- macOS |
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- hierarchy |
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pretty_name: Screen2AX-Tree |
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size_categories: |
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- 1K<n<10K |
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--- |
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# 📦 Screen2AX-Tree |
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Screen2AX-Tree is part of the **Screen2AX** dataset suite, a research-driven collection for advancing accessibility in macOS applications using computer vision and deep learning. |
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This dataset provides **hierarchical accessibility annotations** of macOS application screenshots, structured as serialized trees. It is designed for training models that reconstruct accessibility hierarchies from visual input. |
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--- |
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## 🧠 Dataset Summary |
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Each sample in the dataset consists of: |
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- An application **screenshot** (`image`) |
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- A serialized **accessibility tree** (`accessibility`): A JSON-formatted string representing the UI structure, including roles, bounds, and child relationships. |
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**Task Category:** |
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- `object-detection` (structured / hierarchical) |
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**Language:** |
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- English (`en`) |
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--- |
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## 📚 Usage |
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### Load with `datasets` library |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("MacPaw/Screen2AX-Tree") |
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``` |
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### Example structure |
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```python |
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sample = dataset["train"][0] |
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print(sample.keys()) |
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# dict_keys(['image', 'accessibility']) |
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print(sample["accessibility"]) |
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# '{ "role": "AXWindow", "children": [ ... ] }' |
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``` |
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You can parse the accessibility field as JSON to work with the structured hierarchy: |
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```python |
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import json |
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tree = json.loads(sample["accessibility"]) |
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``` |
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--- |
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## 📜 License |
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This dataset is licensed under the **Apache 2.0 License**. |
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--- |
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## 🔗 Related Projects |
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- [Screen2AX Main Project Page](https://github.com/MacPaw/Screen2AX) |
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- [Screen2AX HuggingFace Collection](https://huggingface.co/collections/MacPaw/screen2ax-687dfe564d50f163020378b8) |
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--- |
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## ✍️ Citation |
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If you use this dataset, please cite the Screen2AX paper: |
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```bibtex |
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@misc{muryn2025screen2axvisionbasedapproachautomatic, |
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title={Screen2AX: Vision-Based Approach for Automatic macOS Accessibility Generation}, |
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author={Viktor Muryn and Marta Sumyk and Mariya Hirna and Sofiya Garkot and Maksym Shamrai}, |
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year={2025}, |
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eprint={2507.16704}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.LG}, |
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url={https://arxiv.org/abs/2507.16704}, |
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} |
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``` |
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--- |
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## 🌐 MacPaw Research |
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Learn more at [https://research.macpaw.com](https://research.macpaw.com) |
