Datasets:
metadata
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': A
'1': B
'2': C
'3': D
'4': E
'5': F
'6': G
'7': H
'8': I
'9': J
splits:
- name: train
num_bytes: 6842235.510231657
num_examples: 14979
- name: test
num_bytes: 1715013.5296924065
num_examples: 3745
download_size: 8865158
dataset_size: 8557249.039924063
task_categories:
- image-classification
- image-to-image
- text-to-image
- image-to-text
tags:
- mnist
- notmnist
pretty_name: notMNIST
size_categories:
- 10K<n<100K
Dataset Card for "notMNIST"
Overview
The notMNIST dataset is a collection of images of letters from A to J in various fonts. It is designed as a more challenging alternative to the traditional MNIST dataset, which consists of handwritten digits. The notMNIST dataset is commonly used in machine learning and computer vision tasks for character recognition.
Dataset Information
- Number of Classes: 10 (A to J)
- Number of Samples: 187,24
- Image Size: 28 x 28 pixels
- Color Channels: Grayscale
Dataset Structure
The dataset is split into a training set and a test set. Each class has its own subdirectory containing images of that class. The directory structure is as follows:
notMNIST/
|-- train/
| |-- A/
| |-- B/
| |-- ...
| |-- J/
|
|-- test/
| |-- A/
| |-- B/
| |-- ...
| |-- J/
Acknowledgements
http://yaroslavvb.blogspot.com/2011/09/notmnist-dataset.html https://www.kaggle.com/datasets/lubaroli/notmnist