Question

我正在尝试制作可以从图像预测动物的CNN。以下是我正在使用的工具和python版本。 IDE：Spyder 3.2.6与Anaconda Tensorflow：版本1.2.1 Keras 2.1.4。 python 3.5

from keras.models import Sequential
from keras.layers import Convolution2D
from keras.layers import MaxPooling2D
from keras.layers import Flatten
from keras.layers import Dense
from keras.layers import Conv2D

classifier = Sequential()
classifier.add(Convolution2D(32,3,3,input_shape=(64,64,3),activation = 'relu'))
classifier.add(MaxPooling2D(pool_size = (2, 2)))
classifier.add(Flatten())
classifier.add(Dense(output_dim = 128,activation='relu'))
classifier.add(Dense(output_dim = 1,activation='sigmoid'))
classifier.compile(optimizer='adam', loss = 'binary_crossentropy', matrix = ['accuracy'])

from keras.preprocessing.image import ImageDataGenerator

train_datagen = ImageDataGenerator(
        rescale=1./255,
        shear_range=0.2,
        zoom_range=0.2,
        horizontal_flip=True)

test_datagen = ImageDataGenerator(rescale=1./255)

training_set = train_datagen.flow_from_directory('dataset/training_set',
                                                    target_size=(64, 64),
                                                    batch_size=32,
                                                    class_mode='binary') 


test_set = test_datagen.flow_from_directory('dataset/test_set',
                                            target_size=(64, 64),
                                            batch_size=32,
                                            class_mode='binary')

classifier.fit_generator(training_set,
                         steps_per_epoch=(8000/32),
                         epochs=25,
                         validation_data=test_set,
                         validation_steps=(2000/32))

但是当我运行上面显示的fit_generator方法时，我得到以下错误

classifier.fit_generator(training_set,
                         steps_per_epoch=(8000/32),
                         epochs=25,
                         validation_data=test_set,
                         validation_steps=(2000/32))
Epoch 1/25
Traceback (most recent call last):

  File "<ipython-input-7-f76922930094>", line 5, in <module>
    validation_steps=(2000/32))

  File "C:\Users\fspathan\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper
    return func(*args, **kwargs)

  File "C:\Users\fspathan\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\keras\models.py", line 1276, in fit_generator
    initial_epoch=initial_epoch)

  File "C:\Users\fspathan\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper
    return func(*args, **kwargs)

  File "C:\Users\fspathan\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\keras\engine\training.py", line 2224, in fit_generator
    class_weight=class_weight)

  File "C:\Users\fspathan\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\keras\engine\training.py", line 1883, in train_on_batch
    outputs = self.train_function(ins)

  File "C:\Users\fspathan\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\keras\backend\tensorflow_backend.py", line 2478, in __call__
    **self.session_kwargs)

TypeError: run() got an unexpected keyword argument 'matrix'

我已经完成了enogh谷歌并应用了所有必要的修复程序，但仍然没有进展。如果有人知道解决方案，这将是一个很好的帮助

非常感谢

Answer 1

在第

行

classifier.compile(optimizer='adam', loss = 'binary_crossentropy', matrix = ['accuracy'])

您传递参数matrix = ['accuracy']。这不是compile函数接受的任何参数，并且如文档所述，传递给此函数的额外参数将转发到后端，在TensorFlow的情况下转发到内部的run方法tf.Session对象。但是，matrix也不是该函数的预期参数，因此在尝试传递时它会失败。

我怀疑你打算做的是要求Keras计算准确度指标，在这种情况下你需要传递metrics参数，而不是matrix：

classifier.compile(optimizer='adam', loss = 'binary_crossentropy', metrics = ['accuracy'])

调用fit_generator时出错：python Tensorflow

1 个答案: