Question

我正在尝试在我的数据上训练CNN model，该数据是由gray-scale由numpy数组生成的OpenCV图像的集合，这些图像是75*70像素。我收到以下错误：

    ValueError: Error when checking input: expected conv2d_25_input to have 
    shape (64, 64, 1) but got array with shape (64, 64, 3)

这是我的代码：

# Importing the Keras libraries and packages
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

# Initialising the CNN
classifier = Sequential()

# Step 1 - Convolution
classifier.add(Convolution2D(32, 3, 3, input_shape = (64,64,1), activation = 'relu'))

# Step 2 - Pooling
classifier.add(MaxPooling2D(pool_size = (2, 2)))

# Adding a second convolutional layer
#classifier.add(Convolution2D(32, 3, 3, activation = 'relu'))
#classifier.add(MaxPooling2D(pool_size = (2, 2)))

# Step 3 - Flattening
classifier.add(Flatten())

# Step 4 - Full connection
classifier.add(Dense(output_dim = 128, activation = 'relu'))
classifier.add(Dense(output_dim = 750, activation = 'softmax'))

# Compiling the CNN
classifier.compile(optimizer = 'adam', loss = 'categorical_crossentropy', metrics = ['accuracy'])

# Part 2 - Fitting the CNN to the images

from keras.preprocessing.image import ImageDataGenerator


train_datagen = ImageDataGenerator(rescale = 1./255)


test_datagen = ImageDataGenerator(rescale = 1./255)

training_set = train_datagen.flow_from_directory('train',
                                                 target_size = (64, 64),
                                                 batch_size = 32,
                                                 class_mode = 'categorical')

test_set = test_datagen.flow_from_directory('test',
                                            target_size = (64, 64),
                                            batch_size = 32,
                                            class_mode = 'categorical')


classifier.fit_generator(training_set,
                         samples_per_epoch = 525,
                         nb_epoch = 25,
                         validation_data = test_set,
                         nb_val_samples = 225)

我的图片只有一个通道，但是仍然出现此输入形状错误，有人可以帮我吗？

编辑：我在keras documentation中找到了答案，ImageDataGenerator默认color_mode是rgb，所以我将其更改为grayscale，解决了{{1} } 代码看起来像这样；

input shape

但是，我遇到另一个错误： training_set = train_datagen.flow_from_directory('train', target_size = (64,64), color_mode = 'grayscale', batch_size = 32, class_mode = 'categorical') test_set = test_datagen.flow_from_directory('test', target_size = (64, 64), color_mode = 'grayscale', batch_size = 32, class_mode = 'categorical') 我不知道... !!

Answer 1

为什么不尝试使用.reshape（64,64,1）来确保图像在一个通道中

keras CNN无法识别一个频道的图像

1 个答案: