from keras.models import Sequential
from keras.layers import Dense, Dropout

model = Sequential()
model.add(Dense(1000, input_dim=image_height*image_width*3, activation='relu'))
model.add(Dropout(0.3))
model.add(Dense(100, activation='softmax'))
print(model.summary())

EPOCHS = 40
model.compile(loss='categorical_crossentropy', optimizer='adam',
              metrics=['accuracy'])
history = model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=EPOCHS, batch_size=256, verbose=0)
