Question

我在Keras中使用以下代码使用CNN对某些图像进行分类。我在第一个时期出现操作系统错误........................................... ................................................... ................................................... ........................

    from keras.preprocessing.image import ImageDataGenerator
    from keras.models import Sequential
    from keras.layers import Conv2D, MaxPooling2D
    from keras.layers import Activation, Dropout, Flatten, Dense
    from keras import backend as K
    import os, os.path
    import glob

    # dimensions of our images.
    img_width, img_height = 224,224
    train_data_dir ='D:/Sowmya/data/train/' #Note the forward slash
    validation_data_dir = 'D:/Sowmya/data/valid'
    epochs = 50
    batch_size = 2

    len(list(glob.iglob("D:/Sowmya/data/train/*/*.tif", recursive=True)))
    num_train=sum(1 for i in glob.iglob("D:/Sowmya/data/train/*/*.tif"))
    print ("Number fo training images =",num_train)

    len(list(glob.iglob("D:/Sowmya/data/valid/*/*.tif", recursive=True)))
    num_valid=sum(1 for i in glob.iglob("D:/Sowmya/data/valid/*/*.tif"))
    print ("Number fo validation images =",num_valid)

    input_shape = (img_width, img_height, 3)

    model = Sequential()
    model.add(Conv2D(32, (3, 3), input_shape=input_shape))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(Conv2D(32, (3, 3)))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(Conv2D(64, (3, 3)))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(Flatten())
    model.add(Dense(64))
    model.add(Activation('relu'))
    model.add(Dropout(0.5))
    model.add(Dense(1))
    model.add(Activation('sigmoid'))

    model.compile(loss='binary_crossentropy',
              optimizer='rmsprop',
              metrics=['accuracy'])

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

    train_generator = train_datagen.flow_from_directory(
    train_data_dir,
    target_size=(img_width, img_height),
    batch_size=batch_size,
    class_mode='binary')

    validation_generator = test_datagen.flow_from_directory(
    validation_data_dir,
    target_size=(img_width, img_height),
    batch_size=batch_size,
    class_mode='binary')

    model.fit_generator(
    train_generator,
    steps_per_epoch=num_train // batch_size,
    epochs=epochs,
    validation_data=validation_generator,
    validation_steps=num_valid // batch_size)

    model.save_weights('first_try.h5')

我遇到以下错误。

Epoch 1/50

---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
<ipython-input-15-da2e7998cf61> in <module>


c:\users\sowmy\appdata\local\programs\python\python36\lib\site-packages\keras_preprocessing\image.py in next(self)
   1968         # The transformation of images is not under thread lock
   1969         # so it can be done in parallel
-> 1970         return self._get_batches_of_transformed_samples(index_array)
   1971 
   1972 

c:\users\sowmy\appdata\local\programs\python\python36\lib\site-packages\keras_preprocessing\image.py in _get_batches_of_transformed_samples(self, index_array)
   1921                            color_mode=self.color_mode,
   1922                            target_size=self.target_size,
-> 1923                            interpolation=self.interpolation)
   1924             x = img_to_array(img, data_format=self.data_format)
   1925             # Pillow images should be closed after `load_img`,

c:\users\sowmy\appdata\local\programs\python\python36\lib\site-packages\keras_preprocessing\image.py in load_img(path, grayscale, color_mode, target_size, interpolation)
    496         raise ImportError('Could not import PIL.Image. '
    497                           'The use of `array_to_img` requires PIL.')
--> 498     img = pil_image.open(path)
    499     if color_mode == 'grayscale':
    500         if img.mode != 'L':

c:\users\sowmy\appdata\local\programs\python\python36\lib\site-packages\PIL\Image.py in open(fp, mode)
   2655         warnings.warn(message)
   2656     raise IOError("cannot identify image file %r"
-> 2657                   % (filename if filename else fp))
   2658 
   2659 #

OSError: cannot identify image file 'D:/Sowmya/data/train/RP\\Extract_tif969.TIF'

#

有人可以帮助您理解该错误吗？

Keras运行时错误“无法识别图像文件”

0 个答案: