Computer Vision! Machine learning! A E S T H E T I C!
An Extremely Efficient Chess-board Detection for Non-trivial Photos
We present a set of algorithms that can be used to locate and crop the chess-board/chess-pieces from the picture, including every rectangular grid with any pattern. Our method is non-parametric, and thus does not require the prior knowledge from computer vision and machine learning, which is instead inferred from data. We illustrate the application of our method to a variety of examples, such as chess-board cropping and regular grid-pattern localization. In addition, we present two independent algorithms: PAMG (vertices detector) and FAPL (thermal lines) that can be widely used for other tasks in computer vision.
Files:
$ # basic
$ python3 detect <filename> # detect and crop chess-board from a photo
$ python3 fen <filename> # generate FEN from a cropped photo
$ # utils
$ python3 dataset # prepare a dataset (for detector)
$ python3 train # learn PAMG (neural network)Dependencies:
- Python 3
- Scipy 0.19.1
- OpenCV 3
- Tensorflow (with tflearn support)
- Networkx and Pyclipper
TODO:
- Board Detection: detect board and segment into 8x8 squares
"An Extremely Efficient Chess-board Detection for Non-trivial Photos" -- M. A. C.
- Piece Recognition: identify chess pieces from a cropped board
(currently using Jialin Ding method, but we are preparing something completely new)
Raw Process:
BONUS (old gif):
