def TestAccuracy(self, test_file_names):
num_files = len(test_file_names)
predict_result = self.__model__.predict(
CNNClassifier.func_generator(test_file_names)).argmax(axis=1)
predict_result = predict_result.reshape(num_files, -1)
predicted_fen_arr = np.array([
BoardHelper.LtoFEN(BoardHelper.LabelArrayToL(labels))
for labels in predict_result
])
test_fens = np.array([
DataHelper.GetCleanNameByPath(file_name)
for file_name in test_file_names
])
final_accuracy = (predicted_fen_arr == test_fens).astype(
np.float).mean()
return final_accuracy
def Predict(self, query_data):
grids = CNNClassifier.PreprocessImage(query_data)
y_pred = self.__model__.predict(grids).argmax(axis=1)
return BoardHelper.LabelArrayToL(y_pred)
def Predict(self, query_data):
grids = SVCClassifier.SVCPreprocess(query_data)
y_pred = self.__svc__.predict(grids)
return BoardHelper.LabelArrayToL(y_pred)