---
license: cc0-1.0
task_categories:
- image-classification
- image-feature-extraction
language:
- en
size_categories:
- 1K<n<10K
pretty_name: Sudoku Image Recognition
---
# Dataset Card for Sudoku Image Recognition

Images of Sudoku puzzles for multilabel classification.

## Dataset Details

### Dataset Description

This dataset consists of 1400 labelled images of Sudoku puzzles. It is intended for training and evaluating a system that can automatically determine the state of each cell in the puzzle: whether it is solved or unsolved, and which digits it contains. The images are split into train (1000), val (200) and test (200).

## Uses

The dataset is intended for training models that can automatically determine the state of a Sudoku puzzle from an image. These can be used to streamline user experience in Sudoku apps and websites. Instead of manually entering the state of the puzzle, a user can process an image, then review and correct any mistakes made by the model. The digital Sudoku puzzle can then be shared, analyzed and completed in the app or website.

## Dataset Structure

The dataset consists of the following fields:

- `image` is an image of a Sudoku puzzle.
  
  The images are of varying sizes and the image formats include webp, jpg and png. Some images are screenshots and others are photos.

- `cells` is an array representing the puzzle cells.

  It has shape (9, 9, 10) = (rows, cols, flags) and all entries are 0 or 1. Flag 0 encodes whether the cell is solved (1) or unsolved (0). Flags 1-9 encode whether the digits 1-9 respectively are present (1) or absent (0). If the cell is solved, then there is exactly one digit present (the solution) and all other digits are absent. If the cell is unsolved, then any set of digits can be present (including no digits). If the cell is unsolved, then any present digits are candidates, not solutions.

- `keypoints` is an array of floats representing the puzzle keypoints (corners).

  It has shape (8,) but represents four (x, y) coordinate pairs. The values are absolute image coordinates and start in the top-left of the image, so (0.0, 0.0) is the top-left and (width, height) is the bottom-right. The keypoints are all ordered in the same way: top-left, bottom-left, bottom-right, top-right.
  
  Note that for photos, the keypoints may be outside the puzzle corners. This is because in some photos, the puzzle is distorted, so performing a crop or perspective transform based on the real corner locations would exclude some of the puzzle. Having the keypoints slightly outside the puzzle corners in this case overcomes that problem.