The Chess Recognition Dataset 2K (ChessReD2K) comprises a diverse collection of images of chess formations captured using smartphone cameras; a sensor choice made to ensure real-world applicability. The dataset is accompanied by detailed annotations providing information about the chess pieces formation in the images, bounding-boxes, and chessboard corner annotations. The number of annotations for each image depends on the number of chess pieces depicted in it. There are 12 category ids in total (i.e., 6 piece types per colour) and the chessboard coordinates are in the form of algebraic notation strings (e.g., "a8"). The corners are annotated based on their location on the chessboard (e.g., "bottom-left") with respect to the white player's view. This discrimination between these different types of corners provides information about the orientation of the chessboard that can be leveraged to determine the image's perspective and viewing angle.

Dataset specifications

The dataset consists of 20 chess games (selected from the ChessReD dataset), each with an arbitrary number of moves and therefore images, amounting to a total of 2,078 images. A 70/15/15 split stratified over the smartphone cameras was followed, which led to a total of 14 training games (1,442 images), 3 validation games (330 images), and 3 test games (306 images) being annotated. The split was also stratified over the three distinct smartphone cameras (Apple iPhone 12, Huawei P40 pro, Samsung Galaxy S8) that were used to capture the images.