/poker-hand-recognition

Classification and recognition of poker hands via OpenCV and machine learning algorithms

Primary LanguagePythonMIT LicenseMIT

PokerHandRecognition

Description of project

Recognition of playing cards and classification of poker hands.

Libraries necessary to run scripts:

-python 2.7
-opencv 3.2
-numpy 1.12 or greater
-sckit-learn 0.18
-sckit-image 0.10
-h5py
-keras
-Theano or Tensorflow

All libraries can be installed via pip. Run command pip install <library_name>.

Run main.py -> Load models and recognize all cards from folder 'data/test_dataset/' and write result in /results/results.txt. If models aren't saved run train_nn.py first.

card_manipulation.py -> Script contains functions for image processing

crop_cards.py and preprocess_crop_cards.py -> Create dataset to run through neural network

train_nn.py -> Create models for NN and Random Forest and save to file