Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 174, in _generate_tables
df = pandas_read_json(f)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 791, in read_json
json_reader = JsonReader(
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 905, in __init__
self.data = self._preprocess_data(data)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 917, in _preprocess_data
data = data.read()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 813, in read_with_retries
out = read(*args, **kwargs)
File "/usr/local/lib/python3.9/codecs.py", line 322, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3422, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2187, in _head
return next(iter(self.iter(batch_size=n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2391, in iter
for key, example in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
for key, pa_table in self._iter_arrow():
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1904, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 499, in _iter_arrow
for key, pa_table in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 346, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 177, in _generate_tables
raise e
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 151, in _generate_tables
pa_table = paj.read_json(
File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
FunUI Benchmark
📖 Introduction
FunUI is a bilingual benchmark designed to fill the gap of comprehensive evaluation datasets in the field of screen understanding.
It encompasses four fundamental tasks and provides a holistic evaluation platform to assess models’ abilities on mobile UI comprehension.
✨ Key Features
Bilingual
- Includes 2,150 Chinese screens and 9,347 English screens from Android devices.
- Annotated with about 14k Chinese samples and 18k English samples.
- The first benchmark that enables systematic evaluation of both Chinese and English screen understanding.
Comprehensive
- Covers multiple dimensions of screen understanding:
- UI Grounding (element localization)
- UI Referring (element identification)
- Screen Question Answering
- Screen Summarization
- Ranges from spatial grounding and entity recognition to integrated analysis of screen content.
- Covers multiple dimensions of screen understanding:
Diverse
- Provides QA pairs involving 120+ icons and widgets.
- Includes complex reasoning questions related to element relations, attributes, arithmetic, and more.
- Poses greater challenges compared to commonly used OCR-related tasks.
📊 Tasks
UI Grounding
- Models are required to localize the target UI element.
UI Referring
- Models identify the specific UI element described in bbox format.
Screen Question Answering
- Models answer diverse questions about screen content.
Screen Summarization
- Models generate summaries of the observed screen.
🚀 Applications
- Automated UI comprehension and interaction.
- Development of intelligent assistants and mobile automation.
- Benchmarking multimodal models for screen understanding.
📜 Citation
If you use FunUI benchmark in your research, please cite our paper:
@article{202408.2137,
title = {UI-Hawk: Unleashing the Screen Stream Understanding for GUI Agents},
author = {Jiwen Zhang and Yaqi Yu and Minghui Liao and Wentao Li and Jihao Wu and Zhongyu Wei},
doi = {10.20944/preprints202408.2137.v1},
url = {https://doi.org/10.20944/preprints202408.2137.v1},
year = 2024,
month = {August},
publisher = {Preprints},
journal = {Preprints}
}
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