TypeError：listdir：path应该是string、bytes、os.pathlike或None，而不是DirectoryIterator

Question

我是机器学习的初学者，目前正在尝试将VGG网络应用于我的神经网络

from tensorflow.keras.preprocessing.image import ImageDataGenerator
#Training Set
train_set = train_datagen.flow_from_directory('train')

#Training Set
valid_set = train_datagen.flow_from_directory('test')


train_size, validation_size, test_size = 200, 100, 100
img_width, img_height = 224, 224  # Default input size for VGG16

# Extract features
import os, shutil


datagen = ImageDataGenerator(rescale=1./255)
batch_size = 32

def extract_features(directory, sample_count):
    features = np.zeros(shape=(sample_count, 7, 7, 512))  # Must be equal to the output of the convolutional base
    labels = np.zeros(shape=(sample_count))
    # Preprocess data
    generator = datagen.flow_from_directory(directory,
                                            target_size=(img_width,img_height),
                                            batch_size = batch_size,
                                            class_mode='categorical')
    # Pass data through convolutional base
    i = 0
    for inputs_batch, labels_batch in generator:
        features_batch = conv_base.predict(inputs_batch)
        features[i * batch_size: (i + 1) * batch_size] = features_batch
        labels[i * batch_size: (i + 1) * batch_size] = labels_batch
        i += 1
        if i * batch_size >= sample_count:
            break
    return features, labels

train_features, train_labels = extract_features(train_set, train_size)  # Agree with our small dataset size
validation_features, validation_labels = extract_features(validation_dir, validation_size)
test_features, test_labels = extract_features(test_dir, test_size)

这是发生的错误

发现714幅图像，分属10类。发现100个图像，属于

到10个班。-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

在extract_features（目录，sample_count)24 target_size=(img_width,img_height)，25 batch_size=batch_size，-->26 class_mode='categorical')27#通过卷积基28 i=0

~\anaconda3\envs\tensorflow_cpu\lib\site-packages\keras_preprocessing\image\image_data_generator.py in flow_from_directory（self,directory,target_size,color_mode,classes,class_mode,batch_size,shuffle,seed,save_to_dir,save_prefix,save_format,follow_links,subset,interpolation）538

~\anaconda3\envs\tensorflow_cpu\lib\site-packages\keras_preprocessing\image\directory_iterator.py init（self,directory,image_data_generator,target_size,color_mode,classes,class_mode,batch_size,shuffle,seed,data_format,save_to_dir,save_prefix,save_format,follow_links,suffle,seed,

TypeError：listdir：path应该是string、bytes、os.pathlike或None，而不是DirectoryIterator

Answer 1

您正在将一个数据生成器传递给另一个数据生成器，如下所示：

generator = datagen.flow_from_directory(directory,
                                        target_size=(img_width,img_height),
                                        batch_size = batch_size,
                                        class_mode='categorical')

第一个参数directory应该是一个目录，而不是一个数据生成器，它应该类似于:'path/to/my/train_set/'。我想，在你的情况下，这只是“火车”，因为你把它们放在同一个文件夹里，就像你的笔记本一样。