Chesseract Dataset

A dataset containing the images and labels for the Chesseract data used in the CVPR NAS workshop Unseen-data challenge under the codename "Chester"
The Chesseract dataset is constructed from publicly accessible Chess games played by Grandmasters: Bobby Fischer, Garry Kasparov, Magnus Carlsen, Viswanathan Anand, Hikaru Nakamura, Anatoly Karpov, Fabiano Caruana, and Mikhail Tal.
We extracted the final 15% of board states where the nth board state refers to the position after N moves.
Chesseract uses 12 channels to encode the information rather than the traditional 2 or 3 for grayscale and RGB images respectively. Each channel represents a singular piece type and colour combination. In essence, this has allowed us to represent the pieces and their position on the board in a one-hot encoded format.
A rendering of one of the board states has been included in this archive to demonstrate how the machine perceives the dataset. A 2D traditional of the same board state is also included. Please note in the 3D rendering the white pieces have been rendered as gray to be more visible.
The data is in a channels-first format with a shape of (n, 12, 8, 8) where n is the number of samples in the corresponding set (49,998 for training, 10,001 for validation, and 10,001 for testing).
There are three classes in the dataset, with labels 23,333 examples of each distributed as evenly as possible between the three subsets.
The three classes and corresponding numerical labels are as follows:
White wins: 0,
Draw: 1,
Black ins: 2

该数据集包含用于 CVPR NAS 工作坊“未知数据挑战”中 Chesseract 项目之下的“Chester”代号所涉及的图像及其标签。Chesseract 数据集由公开可访问的棋手对弈棋局构建而成，这些棋手包括鲍比·费舍尔、加里·卡斯帕罗夫、马格努斯·卡尔森、维什瓦纳森·安达、河野太一、阿纳托利·卡尔波夫、法比安诺·卡鲁阿纳和米哈伊尔·塔尔。我们从对弈中提取了最后 15% 的棋盘状态，其中第 n 个棋盘状态指代经过 N 次走棋后的局面。Chesseract 采用 12 个通道来编码信息，而非传统的灰度图像的 2 个或 RGB 图像的 3 个通道。每个通道代表一种单一的棋子类型及其颜色组合。本质上，这使我们能够以独热编码格式表示棋子和它们在棋盘上的位置。本档案中包含了一个棋盘状态的渲染示例，以展示机器如何感知该数据集。同时还包括了同一棋盘状态的 2D 传统表示。请注意，在 3D 渲染中，为了提高可见性，白棋被渲染为灰色。数据以通道优先的格式存储，其形状为 (n, 12, 8, 8)，其中 n 代表对应集合中的样本数量（训练集 49,998 个，验证集和测试集各 10,001 个）。数据集中存在三个类别，每个类别包含 23,333 个示例，且尽可能均匀地分布在三个子集之间。三个类别及其对应的数值标签如下：白方获胜：0，平局：1，黑方失败：2。