The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: RuntimeError
Message: Dataset scripts are no longer supported, but found stl10.py
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1207, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1167, in dataset_module_factory
raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
RuntimeError: Dataset scripts are no longer supported, but found stl10.pyNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for STL-10
Dataset Details
Dataset Description
The STL-10 dataset is an image recognition dataset for developing unsupervised feature learning, deep learning, self-taught learning algorithms. It is inspired by the CIFAR-10 dataset but with some modifications. In particular, each class has fewer labeled training examples than in CIFAR-10, but a very large set of unlabeled examples is provided to learn image models prior to supervised training.
Dataset Sources
- Homepage: https://cs.stanford.edu/~acoates/stl10/
- Paper: Coates, A., Ng, A., & Lee, H. (2011, June). An analysis of single-layer networks in unsupervised feature learning. In Proceedings of the fourteenth international conference on artificial intelligence and statistics (pp. 215-223). JMLR Workshop and Conference Proceedings.
Dataset Structure
Labeled
Total images: 13,000
Classes: 10 categories (airplane, bird, car, cat, deer, dog, horse, monkey, ship, truck)
Splits:
Train: 5,000 images
Test: 8,000 images
Image specs: 96x96 pixels, RGB
Unlabeled
Total images: 100,000
Classes: all labels are -1
Example Usage
Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("randall-lab/stl10", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/stl10", split="test", trust_remote_code=True)
# dataset = load_dataset("randall-lab/stl10", split="unlabeled", trust_remote_code=True)
# Access a sample from the dataset
example = dataset[0]
image = example["image"]
label = example["label"]
image.show() # Display the image
print(f"Label: {label}")
Citation
BibTeX:
@inproceedings{coates2011analysis, title={An analysis of single-layer networks in unsupervised feature learning}, author={Coates, Adam and Ng, Andrew and Lee, Honglak}, booktitle={Proceedings of the fourteenth international conference on artificial intelligence and statistics}, pages={215--223}, year={2011}, organization={JMLR Workshop and Conference Proceedings} }
- Downloads last month
- 47