The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: UnicodeDecodeError
Message: 'utf-8' codec can't decode byte 0xff in position 0: invalid start byte
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 196, in _generate_tables
csv_file_reader = pd.read_csv(file, iterator=True, dtype=dtype, **self.config.pd_read_csv_kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
return function(*args, download_config=download_config, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1279, in xpandas_read_csv
return pd.read_csv(xopen(filepath_or_buffer, "rb", download_config=download_config), **kwargs)
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1026, in read_csv
return _read(filepath_or_buffer, kwds)
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 620, in _read
parser = TextFileReader(filepath_or_buffer, **kwds)
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1620, in __init__
self._engine = self._make_engine(f, self.engine)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1898, in _make_engine
return mapping[engine](f, **self.options)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 93, in __init__
self._reader = parsers.TextReader(src, **kwds)
~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "pandas/_libs/parsers.pyx", line 574, in pandas._libs.parsers.TextReader.__cinit__
File "pandas/_libs/parsers.pyx", line 663, in pandas._libs.parsers.TextReader._get_header
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2053, in pandas._libs.parsers.raise_parser_error
File "<frozen codecs>", line 325, in decode
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xff in position 0: invalid start byteNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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Annotated Textile Fabric Image Dataset for Visual, Composition, and Material Property Analysis
About this dataset
The Annotated Textile Fabric Image Dataset for Visual, Composition, and Material Property Analysis is a curated dataset of textile fabric sample images with structured metadata annotations.
The dataset contains 12,724 images representing 44 unique textile fabric samples. Each fabric sample is described by metadata such as fiber composition, thickness, fabric weight, number of colors, pattern type, number of images, and supplier or curator notes.
The dataset is intended for textile image analysis, computer vision research, image retrieval, visual similarity analysis, metadata-aware analysis, and future machine learning experiments related to fabric composition and material properties.
The metadata include normalized fiber-composition fields such as polyester, polyamide, acrylic, elastane, cotton, and other fiber percentages. Supplier abbreviations were interpreted according to the dataset-specific normalization rules described in fiber_codebook.csv.
No machine learning models are trained or included in this dataset release. This release focuses on dataset structure, annotation quality, image quality statistics, and readiness for future reproducible research.
Users should note that multiple images belong to the same fabric sample. Therefore, any future train/validation/test split should be performed by fabric sample rather than by individual image to avoid data leakage.
Dataset contents
Recommended file structure:
dataset/
├── images/ or fabric sample folders
├── annotations.csv
├── data_dictionary.csv
├── fiber_codebook.csv
└── README.md
Metadata file
The main annotation file should be named:
annotations.csv
Each row describes one textile fabric sample. The relative_path field links the metadata record to the corresponding image folder or image path in the dataset.
Important columns
relative_path: relative path to the image folder or image file.id: stable fabric sample identifier.num_colors: number of visible colors in the fabric sample.notes: raw supplier or curator notes.weight_gsm: fabric weight in grams per square meter.pattern: pattern or layout category, when available.composition: normalized human-readable fiber composition.*_pct: numeric fiber-percentage columns.thickness_mm: measured fabric thickness in millimeters.images: number of images associated with the fabric sample.
See data_dictionary.csv for the full column-level description.
Fiber-code normalization
Supplier abbreviations were interpreted according to the dataset-specific rules:
PA-> acrylic / polyacrylicNY/Nylon-> polyamide / nylonEA/EL/Lycra-> elastanePES/PL-> polyester
See fiber_codebook.csv for the full mapping.
Intended use
This dataset can be used for:
- textile image analysis;
- fabric visual similarity search;
- image retrieval;
- metadata-aware textile analysis;
- dominant-fiber prediction;
- multi-label fiber-composition analysis;
- exploratory material-property prediction;
- dataset validation and reproducible machine learning workflows.
Limitations
- Some metadata fields are derived from supplier notes and may require manual review.
- Some pattern labels are missing.
- Several images belong to the same fabric sample, so image-level random splitting can cause data leakage.
- The dataset should not be used for claims about real-world textile performance without additional laboratory validation.
Recommended split strategy
For future machine learning experiments, split the dataset by id / fabric sample, not by individual image. This prevents images from the same textile sample appearing in both training and test sets.
License
If all images were created by the dataset authors, a suitable open-data license is CC BY 4.0, which allows reuse with attribution. If a more restrictive research-only release is desired, CC BY-NC 4.0 can be considered, but it limits commercial reuse.
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