model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
#
model.add(Convolution2D(64, 5, 5))
model.add(Activation('relu'))
#
#model.add(MaxPooling2D(pool_size=(2,2)))
#
#model.add(Convolution2D(128, 4, 4))
#model.add(Activation('relu'))
#
#model.add(MaxPooling2D(pool_size=(2, 2)))
#model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(512))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(outsize, init='normal'))
lr = 0.000001
optimizer = Adadelta()
model.compile(loss='mean_squared_error', optimizer=optimizer)
# model.set_weights(getWeights("../OCRfeatures/200_5_3/bestModel.pickle"))
helperFuncs.saveModel(model, folder + "wholeModel")
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(512))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(outsize, init='normal'))
model.compile(loss='mean_squared_error', optimizer='rmsprop')
# model.set_weights(getWeights("../OCRfeatures/200_5_3/bestModel.pickle"))
#with open(folder+"bestModel.pickle", 'wb') as f:
# cp = cPickle.Pickler(f)
# cp.dump(model)
#with open(folder+"wholeModel.pickle", 'wb') as f:
# cp = cPickle.Pickler(f)
# cp.dump(model)
helperFuncs.saveModel(model,folder+"wholeModel")