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我已經建立了一個模型其中兩個分支然後合併成一個單一的。對於模型的培訓,我想使用ImageGenerator來設計圖像數據,但不知道如何爲混合輸入類型工作。有人知道如何在keras中處理這個問題嗎? 任何幫助將不勝感激!使用keras ImageGenerator訓練多輸入模型
最佳, 尼克
MODEL 的第一branchen拍攝圖像作爲輸入:
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())
的第二分支取輔助數據作爲輸入:
aux_model = Sequential()
aux_model.add(Dense(3, input_dim=3))
那麼那些得到合併到最終的模型:
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'])
培訓/問題: 我試圖做這顯然失敗的情況如下:
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))
這將產生以下錯誤信息:
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)
不適用於我的錯誤:ValueError:模型需要2個輸入數組,但只接收一個數組。發現:具有形狀的陣列(0,299,299,3)' – Dmitry