The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label STFD@f50bfecc62ab50fa3fde3ac94e59fcd604782051
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2567, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2102, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2134, in _iter_arrow
pa_table = cast_table_to_features(pa_table, self.features)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2197, in cast_table_to_features
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1795, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1995, in cast_array_to_feature
return feature.cast_storage(array)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1172, in cast_storage
[self._strval2int(label) if label is not None else None for label in storage.to_pylist()]
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1101, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label STFD@f50bfecc62ab50fa3fde3ac94e59fcd604782051Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
STFD Dataset
This folder contains the STFD (Screenshot Text Forgery Dataset) used in the paper:
Learning to Locate the Text Forgery in Smartphone Screenshots Zeqin Yu, Bin Li, Yuzhen Lin, Jinhua Zeng, Jishen Zeng ICASSP 2023
Project page: https://github.com/ZeqinYu/STFL-Net
STFD is designed for text image forgery localization (T-IFL) in smartphone screenshots. The dataset contains tampered screenshots and their corresponding pixel-level forgery masks.
Dataset Structure
STFD/
├── 1_Copy-move/
│ ├── tamper/ # tampered screenshots
│ └── masks/ # binary forgery masks
├── 2_Splicing/
│ ├── tamper/
│ └── masks/
├── 3_Removal/
│ ├── tamper/
│ └── masks/
├── 4_Insertion/
│ ├── tamper/
│ └── masks/
└── 5_Replacement/
├── tamper/
└── masks/
Each image in tamper/ has a corresponding mask with the same filename in masks/.
Example:
tamper/ffa3cedd4317633601c6fb82d94fc783.png
masks/ffa3cedd4317633601c6fb82d94fc783.png
The mask is a binary image, where:
- 0 = non-tampered region
- 255 = tampered region
Tampering Types
STFD contains five common screenshot text manipulation operations:
- Copy-Move: copy a text region and paste it to another location within the same image.
- Splicing: paste text regions from another image into the target image.
- Removal: remove existing text and fill the region using inpainting.
- Insertion: insert new text content into blank regions.
- Replacement: replace original text with newly generated text.
Screenshot Sources
The screenshots were captured from real devices to reflect realistic usage scenarios.
| Category | Description |
|---|---|
| Systems | Android, HarmonyOS, iOS, Windows |
| Scenes | Chat, Social Media, Mobile Payment, E-commerce, Online Banking, Maps & Transportation, Web Browsing, System Interfaces, Documents |
| Devices | Realme Q3 Pro, Oppo Reno1, Honor 9, Honor V30, Vivo X21s, Samsung Note20 Ultra, Vivo X60, Honor 30-1, Xiaomi 9, Honor V20, Nova 8, OnePlus 9, Huawei Mate30, Honor 30-2, Honor 20 Pro, iPhone 7, iPad Air 3, iPad 2020, iPhone 12, iPhone XS, iPhone 11, iPhone SE2, iPhone 14 Pro, MacBook Air 2015, MacBook Pro 2017, Win10 Dell Optiplex 7080, Win11 Xiaomi Air14, Win10 Xiaomi Air14 |
| Format | PNG / JPEG |
Citation
If you use this dataset in your research, please cite:
@inproceedings{yu2023learning,
title = {Learning to Locate the Text Forgery in Smartphone Screenshots},
author = {Yu, Zeqin and Li, Bin and Lin, Yuzhen and Zeng, Jinhua and Zeng, Jishen},
booktitle = {ICASSP 2023–2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages = {1--5},
year = {2023},
organization = {IEEE}
}
License and Notice
This dataset is released for academic research purposes only.
All images are collected from real-world scenarios and have been manually screened to remove sensitive information.
If you believe that any image may contain unintended information leakage, please notify us so that we can remove it promptly. We kindly ask users not to redistribute such images.
For any concerns, please contact: Zeqin Yu (kimjyu@foxmail.com).
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