For my thesis, I developed some tensor-based algorithms for image classification. I have been using the MNIST dataset as benchmark for quite some time now but I want to test my algorithms on other datasets. Because I need images that are already preprocessed (centered, rotated, ...) there aren't much datasets I can use. For example, the COIL datasets contains images of objects that are rotated which isn't good. I have found one other dataset with faces that I can use but are there any other already preprocessed dataset I can use?
The CIFAR-10 dataset consists of 60000 32x32 color images in 10 classes, with 6000 images per class. So, that is a decent pre-processing I feel.
You can train on ImageNet which consists of hundreds and thousands of images belonging to thousands of classes, though not exactly pre-processed in terms of uniform image size. Microsoft Common Objects in Context (COCO) and CIFAR-100 Dataset are some other datasets you can try.