我已经构建了一个模型,它包含两个分支,然后合并成单一的分支。为了训练这个模型,我想使用ImageGenerator来增强图像数据,但不知道如何将其应用于混合的输入类型。有没有人有任何关于在keras中处理这个问题的想法?
任何帮助都将不胜感激!
最好, Nick
模型 第一个分支以图像作为输入:
第二个分支将辅助数据作为输入:
然后这些模型会被合并到最终的模型中:
这会生成以下错误信息:
任何帮助都将不胜感激!
最好, Nick
模型 第一个分支以图像作为输入:
img_model = Sequential()
img_model.add(Convolution2D( 4, 9,9, border_mode='valid', input_shape=(1, 120, 160)))
img_model.add(Activation('relu'))
img_model.add(MaxPooling2D(pool_size=(2, 2)))
img_model.add(Dropout(0.5))
img_model.add(Flatten())
第二个分支将辅助数据作为输入:
aux_model = Sequential()
aux_model.add(Dense(3, input_dim=3))
然后这些模型会被合并到最终的模型中:
model = Sequential()
model.add(Merge([img_model, aux_model], mode='concat'))
model.add(Dropout(0.5))
model.add(Dense(5))
model.add(Activation('softmax'))
model.compile(loss='categorical_crossentropy', optimizer='adadelta', metrics=['accuracy'])
培训/问题: 我尝试做以下操作,但显然失败了:
datagen = ImageDataGenerator(
featurewise_center=False, # set input mean to 0 over the dataset
samplewise_center=False, # set each sample mean to 0
featurewise_std_normalization=False, # divide inputs by std of the dataset
samplewise_std_normalization=False, # divide each input by its std
zca_whitening=False, # apply ZCA whitening
rotation_range=10, #180, # randomly rotate images in the range (degrees, 0 to 180)
width_shift_range=0.1, # randomly shift images horizontally (fraction of total width)
height_shift_range=0.1, # randomly shift images vertically (fraction of total height)
horizontal_flip=False, # randomly flip images
vertical_flip=False) # randomly flip images
model.fit_generator( datagen.flow( [X,I], Y, batch_size=64),
samples_per_epoch=X.shape[0],
nb_epoch=20,
validation_data=([Xval, Ival], Yval))
这会生成以下错误信息:
Traceback (most recent call last):
File "importdata.py", line 139, in <module>
model.fit_generator( datagen.flow( [X,I], Y, batch_size=64),
File "/usr/local/lib/python3.5/dist-packages/keras/preprocessing/image.py", line 261, in flow
save_to_dir=save_to_dir, save_prefix=save_prefix, save_format=save_format)
File "/usr/local/lib/python3.5/dist-packages/keras/preprocessing/image.py", line 454, in __init__
'Found: X.shape = %s, y.shape = %s' % (np.asarray(X).shape, np.asarray(y).shape))
File "/usr/local/lib/python3.5/dist-packages/numpy/core/numeric.py", line 482, in asarray
return array(a, dtype, copy=False, order=order)
ValueError: could not broadcast input array from shape (42700,1,120,160) into shape (42700)
ValueError: 模型期望2个输入数组,但只收到一个数组。找到:形状为(0,299,299,3)的数组
。 - Dmitrytrain_generator
保存下来以备后用,比如说 .pickle 或其他什么格式? - Surya Palaniswamy