The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: KeyError
Message: 'label'
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 257, in get_rows_or_raise
return get_rows(
File "/src/services/worker/src/worker/utils.py", line 198, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 235, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1383, in __iter__
example = _apply_feature_types_on_example(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1075, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1852, in encode_example
return encode_nested_example(self, example)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1229, in encode_nested_example
{
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1229, in <dictcomp>
{
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 323, in zip_dict
yield key, tuple(d[key] for d in dicts)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 323, in <genexpr>
yield key, tuple(d[key] for d in dicts)
KeyError: 'label'Need help to make the dataset viewer work? Open a discussion for direct support.
Facial Hair Classification Dataset
The Facial Hair Classification Dataset is a comprehensive collection of high-resolution images showcasing individuals with and without a beard. The dataset includes a diverse range of individuals of various ages, ethnicities, and genders.
The dataset also contains images of individuals without facial hair, serving as a valuable reference for comparison and contrast. These images showcase clean-shaven faces, enabling research into distinguishing facial hair patterns from those without any beard growth.
Each image in the dataset is carefully curated to showcase the subject's face prominently and with optimal lighting conditions, ensuring clarity and accuracy in the classification and analysis of facial hair presence.
Types of photos in the dataset:
- beard - photos of people with a beard.
- no beard - photos of people without a beard.
The Facial Hair Classification Dataset offers a robust collection of images that accurately represent the diverse range of facial hair styles found in the real world. This dataset provides ample opportunities for training facial recognition algorithms, identifying facial hair patterns, and conducting research on facial hair classification and analysis.
Get the dataset
This is just an example of the data
Leave a request on https://trainingdata.pro/data-market to discuss your requirements, learn about the price and buy the dataset.
Content
The dataset is splitted in three folders: train, validate and test to build a classification model.
Each of these folders includes:
- beard folder: includes photos of people with a beard
- no_beard folder: includes photos of people without a beard
File with the extension .csv
- file: link to access the media file,
- type: does a person has or has not a beard
Files for Facial Hair Classification might be collected in accordance with your requirements.
TrainingData
More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets
TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets
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