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")