我应该改变什么尺寸来解决这个问题?

时间:2019-11-04 19:04:28

标签: python tensorflow keras deep-learning

我建立了一个CNN模型,尺寸方面遇到了麻烦。

src = Input(shape=(196,41,3))

conv11 = Conv2D(32, kernel_size=4, activation='relu')(src)

pool11 = MaxPooling2D(pool_size=(2, 2))(conv11)

conv12 = Conv2D(16, kernel_size=4, activation='relu')(pool11)

drop = Dropout(0.3)

pool12 = MaxPooling2D(pool_size=(2, 2))(conv12)

flat1 = Flatten()(pool12)

# second input model
trgt = Input(shape=(196,41,3))
conv21 = Conv2D(32, kernel_size=4, activation='relu')(trgt)

pool21 = MaxPooling2D(pool_size=(2, 2))(conv21)

conv22 = Conv2D(16, kernel_size=4, activation='relu')(pool21)

pool22 = MaxPooling2D(pool_size=(2, 2))(conv22)

flat2 = Flatten()(pool22)
# merge input models
merge = keras.layers.concatenate([flat1, flat2])

# interpretation model
hidden1 = Dense(64, activation='relu')(merge)
output = Dense(196, activation='relu')(hidden1)

arch = Model(inputs=[src, trgt], outputs=output)

我明白了

检查目标时出错:预期density_35具有2维,但数组的形状为(70,41,196,3)

0 个答案:

没有答案