CIFARTile Dataset

<p dir="ltr">The CIFARTile dataset is constructed using batches of image from the popular CIFAR-10 dataset (available at https://www.cs.toronto.edu/~kriz/cifar.html)</p><p dir="ltr">Each CIFARTile image is a joining of four CIFAR-10 Images in a grid pattern. The solution to this dataset is for a model to identify the number of classes from the original CIFAR-10 that appear in the CIFARTile image. The original CIFAR-10 has 10 classes: Airplane, Automobile, Bird, Cat, Deer, Dog, Frog, Horse, Ship, and Truck. A example CIFARTile image might include two images of horses, a car, and a bird.</p><p dir="ltr">The data is in a channels-first format with a shape of (n, 3, 64, 64) where n is the number of samples in the corresponding set (45,000 for training, 15,000 for validation, and 10,000 for testing).</p><p dir="ltr">There are four classes in the dataset, with 17,500 examples of each distributed as evenly as possible between the three subsets.</p><p dir="ltr">Each images label represents the number of CIFAR-10 classes that appear minus one, for zero-indexing. This means the above example of two horse images, one car, and one bird would have a final label of 2, as there are three different classes.</p><p dir="ltr">0: All sub-images belong to the same CIFAR-10 class.<br>1: There are two CIFAR-10 classes among the sub-images.<br>2: There are three CIFAR-10 classes among the sub-images<br>3: All usb-images belong to different CIFAR-10 classes.</p>