Releases: georg-wolflein/chesscog
Releases · georg-wolflein/chesscog
v1.0.2
- Determine how many misclassified positions are illegal according to the rules of chess. The results are obtained by running
python3 chesscog.report.analyze_misclassified_positions --results data://recognition --dataset test
andpython3 chesscog.report.analyze_misclassified_positions --results data://transfer_learning/recognition --dataset test
):- In the test set (342 samples total), 21 positions were misclassified, of which 1 was illegal according to the rules of chess.
- In the test set of the transfer learning dataset (27 samples total), 3 positions were misclassified, of which all 3 were illegal according to the rules of chess.
- Display a warning in the inference scripts (
chesscog.recognition.recognition
andchesscog.transfer_learning.recognition
) if the predicted position is illegal according to the rules of chess.
Note: FEN positions are validated using the chess library.
v1.0.1
v1.0.0
First stable version!
- Implement transfer learning algorithm to adapt the recognition system to an unseen chess set based on only two images of the starting position.
- Evaluate transfer learning approach.
- More scripts to evaluate the results for the report.
- Write a lot more documentation.
- Auto-generate documentation using Sphinx. Docs are available at https://georgw777.github.io/chesscog.
- More tests.
v0.2.7
- compute more evaluation statistics
- improve performance of chessboard corner detection
- implement new data augmentations (shear, scale, translate)
- implement transfer learning capabilities (achieve >99.9% per-square accuracy for both classifiers on unseen images, using only two training images of the starting chess position from both players' perspectives)
v0.2.6
- run Canny edge detection over edge gradients for border refinement
- end-to-end evaluation
v0.2.5
- more generous thresholds for corner detection
v0.2.4
- better RANSAC parameters
v0.2.3
- eliminate far-away lines in corner detection
v0.2.2
v0.2.1
- implement CI with chesscog-app
- automated deployment to the web