Datasets:
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README.md
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dataset_info:
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features:
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- name: image
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 1127
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download_size:
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dataset_size:
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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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---
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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: 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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...
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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)
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