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  ---
 
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  dataset_info:
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  features:
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  - name: image
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  list: string
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  splits:
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  - name: train
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- num_bytes: 99969468.0
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  num_examples: 555
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  - name: valid
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- num_bytes: 19950509.0
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  num_examples: 114
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  - name: test
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- num_bytes: 25245810.0
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  num_examples: 139
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- download_size: 99748948
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- dataset_size: 145165787.0
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  configs:
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  - config_name: default
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  data_files:
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  path: data/valid-*
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  - split: test
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  path: data/test-*
 
 
 
 
 
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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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  list: string
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  splits:
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  - name: train
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+ num_bytes: 99969538
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  num_examples: 555
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  - name: valid
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+ num_bytes: 19950524
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  num_examples: 114
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  - name: test
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+ num_bytes: 25245828
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  num_examples: 139
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+ download_size: 99748336
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+ dataset_size: 145165890
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  configs:
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  - config_name: default
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  data_files:
 
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  path: data/valid-*
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  - split: test
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  path: data/test-*
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+ task_categories:
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+ - object-detection
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+ pretty_name: Screen2AX-Group
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+ size_categories:
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+ - n<1K
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  ---
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+
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+ # πŸ“¦ Screen2AX-Group
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+
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+ Screen2AX-Group 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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+
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+ This dataset focuses on **UI group detection** from macOS application screenshots and is designed for training and evaluating object detection models.
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+
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+ ---
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+
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+ ## 🧠 Dataset Summary
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+
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+ Each sample in the dataset consists of:
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+ - An application **screenshot** (`image`)
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+ - A dictionary of **UI elements** (`objects`) with 2 keys:
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+ - `bbox` (`List[List[int]]`): List of bounding box coordinates in `[x_min, y_min, x_max, y_max]` format
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+ - `category` (`List[str]`): List of labels indicating the UI group type (`AXGroup`, `AXTabGroup`, `AXToolbar`, etc.)
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+
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+ The dataset supports training deep learning models for object detection tasks specifically tuned for graphical user interfaces (GUIs) on macOS.
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+
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+ **Splits:**
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+ - `train`
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+ - `valid`
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+ - `test`
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+
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+ **Task Category:**
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+ - `object-detection`
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+
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+ ---
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+
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+ ## πŸ“š Usage
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+
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+ ### Load with `datasets` library
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ dataset = load_dataset("MacPaw/Screen2AX-Group")
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+ ```
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+
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+ ### Example structure
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+
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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', 'objects'])
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+
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+ print(sample["objects"])
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+ # {'bbox': [[x_min, y_min, x_max, y_max], ...], 'category': ['AXGroup', ...]}
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+ ```
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+
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+ ---
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+
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+ ## πŸ“œ License
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+
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+ This dataset is licensed under the **Apache 2.0 License**.
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+
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+ ---
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+
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+ ## πŸ”— Related Projects
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+
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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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+ ---
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+
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+ ## ✍️ Citation
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+
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+ If you use this dataset, please cite the Screen2AX paper:
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+
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+ ```bibtex
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+ ...
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+ ```
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+
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+ ---
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+
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+ ## 🌐 MacPaw Research
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+
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+ Learn more at [https://research.macpaw.com](https://research.macpaw.com)