Datasets:
BSD100

Task Categories: other
Multilinguality: monolingual
Size Categories: unknown
Language Creators: found
Annotations Creators: machine-generated
Source Datasets: original
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Cannot get the split names for the dataset.
Error code:   SplitsNamesError
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 376, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                File "/tmp/modules-cache/datasets_modules/datasets/eugenesiow--BSD100/53c5145dfbb9c5d6f81944c22d88071dc230c4ac26010009794d7c4dc147f52b/BSD100.py", line 111, in _split_generators
                  hr_data_dir = dl_manager.download_and_extract(self.config.hr_url)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 946, in download_and_extract
                  return self.extract(self.download(url_or_urls))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 909, in extract
                  urlpaths = map_nested(self._extract, path_or_paths, map_tuple=True)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 420, in map_nested
                  return function(data_struct)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 914, in _extract
                  protocol = _get_extraction_protocol(urlpath, use_auth_token=self.download_config.use_auth_token)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 390, in _get_extraction_protocol
                  raise NotImplementedError(
              NotImplementedError: Extraction protocol for TAR archives like 'https://huggingface.co/datasets/eugenesiow/BSD100/resolve/main/data/BSD100_HR.tar.gz' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/responses/splits.py", line 79, in get_splits_response
                  split_full_names = get_dataset_split_full_names(dataset, hf_token)
                File "/src/services/worker/src/worker/responses/splits.py", line 39, in get_dataset_split_full_names
                  return [
                File "/src/services/worker/src/worker/responses/splits.py", line 42, in <listcomp>
                  for split in get_dataset_split_names(dataset, config, use_auth_token=hf_token)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 426, in get_dataset_split_names
                  info = get_dataset_config_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 381, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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YAML Metadata Error: "licenses" is deprecated. Use "license" instead.
YAML Metadata Error: "languages" is deprecated. Use "language" instead.

Dataset Card for BSD100

Dataset Summary

BSD is a dataset used frequently for image denoising and super-resolution. Of the subdatasets, BSD100 is aclassical image dataset having 100 test images proposed by Martin et al. (2001). The dataset is composed of a large variety of images ranging from natural images to object-specific such as plants, people, food etc. BSD100 is the testing set of the Berkeley segmentation dataset BSD300.

Install with pip:

pip install datasets super-image

Evaluate a model with the super-image library:

from datasets import load_dataset
from super_image import EdsrModel
from super_image.data import EvalDataset, EvalMetrics

dataset = load_dataset('eugenesiow/BSD100', 'bicubic_x2', split='validation')
eval_dataset = EvalDataset(dataset)
model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=2)
EvalMetrics().evaluate(model, eval_dataset)

Supported Tasks and Leaderboards

The dataset is commonly used for evaluation of the image-super-resolution task.

Unofficial super-image leaderboard for:

Languages

Not applicable.

Dataset Structure

Data Instances

An example of validation for bicubic_x2 looks as follows.

{
    "hr": "/.cache/huggingface/datasets/downloads/extracted/BSD100_HR/3096.png",
    "lr": "/.cache/huggingface/datasets/downloads/extracted/BSD100_LR_x2/3096.png"
}

Data Fields

The data fields are the same among all splits.

  • hr: a string to the path of the High Resolution (HR) .png image.
  • lr: a string to the path of the Low Resolution (LR) .png image.

Data Splits

name validation
bicubic_x2 100
bicubic_x3 100
bicubic_x4 100

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

No annotations.

Who are the annotators?

No annotators.

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

Licensing Information

You are free to download a portion of the dataset for non-commercial research and educational purposes. In exchange, we request only that you make available to us the results of running your segmentation or boundary detection algorithm on the test set as described below. Work based on the dataset should cite the Martin et al. (2001) paper.

Citation Information

@inproceedings{martin2001database,
  title={A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics},
  author={Martin, David and Fowlkes, Charless and Tal, Doron and Malik, Jitendra},
  booktitle={Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001},
  volume={2},
  pages={416--423},
  year={2001},
  organization={IEEE}
}

Contributions

Thanks to @eugenesiow for adding this dataset.

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Models trained or fine-tuned on eugenesiow/BSD100