【发布时间】:2017-12-10 23:49:39
【问题描述】:
大家好,我是 Keras 的新人。我选择 keras 来实现这篇论文:http://mmlab.ie.cuhk.edu.hk/projects/TCDCN.html。我只需将输入大小更改为 48x48,然后对于输出,我只需要 68 个地标坐标。这是我的网络:
def mtfl40New(size):
model = Sequential()
model.add(Conv2D(16, (5, 5), padding='valid', input_shape=(3, size, size)))
model.add(Activation('tanh'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(48, (3, 3), padding='valid'))
model.add(Activation('tanh'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(64, (3, 3), padding='valid'))
model.add(Activation('tanh'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(64, (2, 2), padding='valid'))
model.add(Activation('tanh'))
model.add(Flatten())
model.summary()
#model.count_params()
model.add(Dense(100, kernel_initializer="normal", input_shape=(576,)))
model.add(Activation('tanh'))
model.add(Dense(136, kernel_initializer="normal"))
model.add(Activation('tanh'))
model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])
return model
【问题讨论】:
标签: python keras theano conv-neural-network