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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    RuntimeError
Message:      File 'STFD_ICASSP2023/Readme.md' is encrypted, password required for extraction
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 2103, in __iter__
                  batch = formatter.format_batch(pa_table)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 472, in format_batch
                  batch = self.python_features_decoder.decode_batch(batch)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 234, in decode_batch
                  return self.features.decode_batch(batch, token_per_repo_id=self.token_per_repo_id) if self.features else batch
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2254, in decode_batch
                  decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id)
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1508, in decode_nested_example
                  return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/image.py", line 188, in decode_example
                  with xopen(path, "rb", download_config=download_config) as f:
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 977, in xopen
                  file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/core.py", line 135, in open
                  return self.__enter__()
                         ^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/core.py", line 103, in __enter__
                  f = self.fs.open(self.path, mode=mode)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/spec.py", line 1293, in open
                  f = self._open(
                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/implementations/zip.py", line 129, in _open
                  out = self.zip.open(path, mode.strip("b"), force_zip64=self.force_zip_64)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/zipfile/__init__.py", line 1675, in open
                  raise RuntimeError("File %r is encrypted, password "
              RuntimeError: File 'STFD_ICASSP2023/Readme.md' is encrypted, password required for extraction

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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

The STFD dataset has been publicly released (Google Drive / Baidu Netdisk (dwmg) / Huggingface). Please send an email to [email protected] using your academic or institutional email address to request the password for extracting the dataset.

The email should include:

  • Your name, affiliation, and homepage (if available)
  • Your supervisor's name, affiliation, and homepage (if available)
  • A brief description of your research purpose

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.


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
Tampering Types Copy-Move, Splicing, Removal, Insertion, Replacement

Tampering Examples

Copy-Move

Copy a text region and paste it to another location within the same image.

Example1 Example2

Splicing

Paste text regions from another image into the target image.

Example1 Example2

Removal

Remove existing text and fill the region using inpainting.

Example1 Example2

Insertion

Insert new text content into blank regions.

Example1 Example2

Replacement

Replace original text with newly generated text.

Example1 Example2

Dataset Structure

STFD/
β”œβ”€β”€ 1_Copy-move/
β”‚   β”œβ”€β”€ tamper/   # tampered screenshots
β”‚   └── masks/    # binary forgery masks
β”œβ”€β”€ 2_Splicing/
β”‚   β”œβ”€β”€ tamper/
β”‚   └── masks/
β”œβ”€β”€ 3_Removal/
β”‚   β”œβ”€β”€ tamper/
β”‚   └── masks/
β”œβ”€β”€ 4_Insertion/
β”‚   β”œβ”€β”€ tamper/
β”‚   └── masks/
└── 5_Replacement/
    β”œβ”€β”€ 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

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 ([email protected]).

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