The not-MNIST dataset comprises of some freely accessible fonts and symbols extracted to create a dataset similar to MNIST. The dataset is divided into two parts: a relatively small hand-cleaned portion of approximately 19k samples and a larger uncleaned portion of 500k samples. There are ten classes, with letters A-J drawn from various fonts.
Download not-MNIST Dataset in Python
Instead of downloading the not-MNIST dataset in Python, you can effortlessly load it in Python via our open-source package Hub with just one line of code.
Load not-MNIST-small Dataset in Python
ds = hub.load('hub://activeloop/not-mnist-small')
Load not-MNIST-large Dataset in Python
ds = hub.load('hub://activeloop/not-mnist-large')
not-MNIST Dataset Structure
not-MNIST Data Fields
image: tensor containing the 28x28 image.
label: tensor containing labels that represent letters from A to J.
How to use not-MNIST Dataset with PyTorch and TensorFlow in Python
Train a model on not-MNIST dataset with PyTorch in Python
Hub users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license. If you're a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!