datasets

deepfake vs real 60k is a large-scale image classification dataset designed to distinguish between deepfake and real facial images. comprising 30,000 deepfake and 30,000 real images.

multilabel portrait 18k is a multi-label portrait classification dataset designed to analyze and categorize different styles of portrait images. it supports classification of four portrait types.

multilabel geoscenenet 16k is a geospatial image dataset. each image may belong to one or more geographic scene categories, making it suitable for multi-label learning tasks in remote sensing.

realistic face portrait 1024px is a high-resolution image dataset containing 6,712 realistic portrait images of male and female individuals. each image is standardized to 1024×1024 pixels.

bnw vs colored 10k is a curated dataset of 10,000 images designed for binary image classification tasks distinguishing between black & white (bnw) and colored images.

deepfake vs real 1440px max is a curated dataset of 28,000 portrait images designed for binary image classification tasks between deepfake and real portraits.