Machine learning for card value identification (2, 3, 4,..., K, A, Joker).
Successfully tested on medium/large browser sizes with low/high resolution settings.
Recalibrations are no longer needed with the new system and 100% accuracy for card value identification \o/
The system is robust to changes in browser window zoom and/or Window scaling settings, but not yet fully implemented.
Tests made on an i7 4790 and GTX 980Ti
Pitfalls:
card suit (Spade, Heard, Clubs, Diamond) identification may not be 100% accurate (yet)
the new archive size is much larger than before. A downloader will be added to retrieve the required dependency automagically.
potential hardware compability issues for people not having CUDA GPUs (to be checked)
the fallback to CPU-only computations instead of using the GPU is very likely induce a loss in evaluation speed which needs to be tested
Machine learning for card value identification (2, 3, 4,..., K, A, Joker). Successfully tested on medium/large browser sizes with low/high resolution settings. Recalibrations are no longer needed with the new system and 100% accuracy for card value identification \o/ The system is robust to changes in browser window zoom and/or Window scaling settings, but not yet fully implemented. Tests made on an i7 4790 and GTX 980Ti
Pitfalls:
Card suit identification: work in progress.