Keras CNN 分类器

Question

如果您愿意帮助我，我确实对 Keras 的 CNN 有疑问，我将非常感激。

免责声明：我是 CNN 和 Keras 的菜鸟，我现在只是在学习它们。

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我的数据：

2 类（狗和猫）

训练：每个类别 30 张图片

测试：每个类别 14 张图片

有效：每个类别 30 张图片

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我的代码：

data_path = Path("../data")

train_path = data_path / "train"
test_path = data_path / "test"
valid_path = data_path / "valid"

train_batch = ImageDataGenerator().flow_from_directory(directory=train_path,
                                                       target_size=(200, 200),
                                                       classes=animals,
                                                       batch_size=10)

valid_batch = ImageDataGenerator().flow_from_directory(directory=valid_path,
                                                       target_size=(200, 200),
                                                       classes=animals,
                                                       batch_size=10)

test_path = ImageDataGenerator().flow_from_directory(directory=test_path,
                                                     target_size=(200, 200),
                                                     classes=animals,
                                                     batch_size=4)

imgs, labels = next(train_batch)

model = Sequential(
    [Conv2D(32, (3, 3), activation="relu", input_shape=(200, 200, 3)), Flatten(),
     Dense(len(animals), activation='softmax')])

model.compile(Adam(lr=.0001), loss='categorical_crossentropy', metrics=['accuracy'])

model.fit_generator(train_path, steps_per_epoch=4, validation_data=valid_batch, validation_steps=3, epochs=5, verbose=2)

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这是我的错误信息：

我已将路径替换为“”

Traceback (most recent call last):
  File "", line 191, in <module>
    model.fit_generator(train_path, steps_per_epoch=4, validation_data=valid_batch, validation_steps=3, epochs=5, verbose=2)
  File "y", line 91, in wrapper
    return func(*args, **kwargs)
  File "", line 1732, in fit_generator
    initial_epoch=initial_epoch)
  File "", line 185, in fit_generator
    generator_output = next(output_generator)
  File "", line 742, in get
    six.reraise(*sys.exc_info())
  File "", line 693, in reraise
    raise value
  File "", line 711, in get
    inputs = future.get(timeout=30)
  File "", line 657, in get
    raise self._value
  File "", line 121, in worker
    result = (True, func(*args, **kwds))
  File "", line 650, in next_sample
    return six.next(_SHARED_SEQUENCES[uid])
TypeError: 'PosixPath' object is not an iterator

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谁能向我解释一下我做错了什么？另外，如果这是一个离题的问题，请告诉我在哪里可以问。

Answer 1

您遇到的问题是您没有通过生成器进行训练，而是通过了文件的路径（您使用的是 train_path 而不是 train_batch强>。

而在使用.fit_generator() 时，您需要为对象传递一个生成器：

model.fit_generator(train_batch, steps_per_epoch=4, validation_data=valid_batch, validation_steps=3, epochs=5, verbose=2)

Answer 2

这行不是必须的

imgs, labels = next(train_batch)

来自docs fit_generator 第一个参数是生成器对象，而不是您提供的字符串。像这样

model.fit_generator(train_path, steps_per_epoch=4, validation_data=valid_batch, validation_steps=3, epochs=5, verbose=2)