Image classification is a fundamental computer vision task that involves categorizing images into predefined classes or labels. This task is critical for a wide range of applications, including object recognition, scene understanding, and medical diagnosis, among others. In this article, we will be exploring the 10 best datasets for image classification in 2023.
Dataset Name | Type of Images | Size | Popularity | Download Link | Description |
---|---|---|---|---|---|
CIFAR-10 | Natural Images | 50,000 Training Images and 10,000 Test Images | Very Popular | https://www.cs.toronto.edu/~kriz/cifar.html | The CIFAR-10 dataset consists of natural images in 10 classes, such as airplanes, cars, birds, and horses. |
CIFAR-100 | Natural Images | 50,000 Training Images and 10,000 Test Images | Very Popular | https://www.cs.toronto.edu/~kriz/cifar.html | The CIFAR-100 dataset is similar to CIFAR-10, but with 100 classes and more fine-grained classification. |
MNIST | Handwritten Digits | 60,000 Training Images and 10,000 Test Images | Very Popular | http://yann.lecun.com/exdb/mnist/ | The MNIST dataset is a classic dataset in computer vision and contains hand-written digits. |
Fashion-MNIST | Fashion Images | 60,000 Training Images and 10,000 Test Images | Popular | https://github.com/zalandoresearch/fashion-mnist | The Fashion-MNIST dataset consists of images of fashion items such as shirts, pants, and bags. It is often used as a substitute for MNIST. |
ImageNet | Natural Images | 1.4 Million Images | Very Popular | http://image-net.org/ | The ImageNet dataset is a large dataset of natural images, labeled with 1000 categories. |
STL-10 | Natural Images | 5,000 Training Images and 8,000 Test Images | Popular | https://cs.stanford.edu/~acoates/stl10/ | The STL-10 dataset contains natural images with a low resolution and is often used as a benchmark for unsupervised learning methods. |
Caltech-101 | Object Images | 9,146 Images | Popular | http://www.vision.caltech.edu/Image_Datasets/Caltech101/ | The Caltech-101 dataset contains images of 101 object categories, such as faces, animals, and vehicles. |
Caltech-256 | Object Images | 30,607 Images | Popular | http://www.vision.caltech.edu/Image_Datasets/Caltech256/ | The Caltech-256 dataset is an extension of Caltech-101, containing 256 object categories with more images per category. |
Sun397 | Scene Images | 108,754 Images | Popular | http://groups.csail.mit.edu/vision/SUN/ | The Sun397 dataset contains scene images labeled with 397 scene categories, such as bedrooms, forests, and streets. |
Coco 2014 | Natural Images | 330,000 Images | Very Popular | http://cocodataset.org/#home | The Coco 2014 dataset is a large-scale dataset of natural images, labeled with 80 object categories and segmented masks. |