【发布时间】:2019-03-21 13:28:43
【问题描述】:
我正在做图像分类,我正在尝试提高我的准确性,我正在尝试生成图像,但是我遇到了一些文件路径错误,请帮助我怎么做。
这里是我的代码:
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(
'C:\\Users\\NanduCn\\jupter1\\train-scene classification',
target_size=(64, 64),
batch_size=32,
class_mode='categorical')
validation_generator = test_datagen.flow_from_directory(
'C:\\Users\\NanduCn\\jupter1\\train-scene classification',
target_size=(64, 64),
batch_size=32,
class_mode='categorical')
model.fit_generator(
train_generator,
steps_per_epoch=2000,
epochs=50,
validation_data=validation_generator,
validation_steps=800)
我有 6 类图像,但我有 1 类图像生成,这里我的文件像这样 train-scene classification is folder in train is images file and train.csv, and test.csv 。
Found 24335 images belonging to 1 classes.
Found 24335 images belonging to 1 classes.
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-57-faf37afc0119> in <module>()
24 epochs=50,
25 validation_data=0.25,
---> 26 validation_steps=800)
~\Anaconda3\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs)
89 warnings.warn('Update your `' + object_name + '` call to the ' +
90 'Keras 2 API: ' + signature, stacklevel=2)
---> 91 return func(*args, **kwargs)
92 wrapper._original_function = func
93 return wrapper
~\Anaconda3\lib\site-packages\keras\engine\training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
1416 use_multiprocessing=use_multiprocessing,
1417 shuffle=shuffle,
-> 1418 initial_epoch=initial_epoch)
1419
1420 @interfaces.legacy_generator_methods_support
~\Anaconda3\lib\site-packages\keras\engine\training_generator.py in fit_generator(model, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
131 else:
132 # Prepare data for validation
--> 133 if len(validation_data) == 2:
134 val_x, val_y = validation_data
135 val_sample_weight = None
TypeError: object of type 'float' has no len()
【问题讨论】:
-
或许
validation_data=[0.25]? -
对数据的验证
-
taras表示validation_data应该是一个列表,而不是单个值。您更新了代码,但没有更新错误输出。 -
嗨 meowgoesthedog 我有 6 类图像,但它显示 1 类,你能帮我如何生成图像吗?
标签: python image-processing keras deep-learning