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Keras split train test set when using ImageDataGenerator

时间:2019-12-19 23:07:30      阅读:115      评论:0      收藏:0      [点我收藏+]

Keras split train test set when using ImageDataGenerator

I have a single directory which contains sub-folders (according to labels) of images. I want to split this data into train and test set while using ImageDataGenerator in Keras. Although model.fit() in keras has argument validation_split for specifying the split, I could not find the same for model.fit_generator(). How to do it ?

train_datagen = ImageDataGenerator(rescale=1./255,

shear_range=0.2,

zoom_range=0.2,

horizontal_flip=True)

?

train_generator = train_datagen.flow_from_directory(

train_data_dir,

target_size=(img_width, img_height),

batch_size=32,

class_mode=‘binary‘)

?

model.fit_generator(

train_generator,

samples_per_epoch=nb_train_samples,

nb_epoch=nb_epoch,

validation_data=??,

nb_val_samples=nb_validation_samples)

I don‘t have separate directory for validation data, need to split it from the training data

-----

Keras has now added Train / validation split from a single directory using ImageDataGenerator:

train_datagen = ImageDataGenerator(rescale=1./255,

    shear_range=0.2,

    zoom_range=0.2,

    horizontal_flip=True,


					validation_split=0.2) # set validation split
					

?

train_generator = train_datagen.flow_from_directory(

    train_data_dir,

    target_size=(img_height, img_width),

    batch_size=batch_size,

    class_mode=‘binary‘,


					subset=‘training‘) # set as training data
					

?

validation_generator = train_datagen.flow_from_directory(

    train_data_dir, # same directory as training data
						

    target_size=(img_height, img_width),

    batch_size=batch_size,

    class_mode=‘binary‘,


					subset=‘validation‘) # set as validation data
					

?

model.fit_generator(

    train_generator,

    steps_per_epoch = train_generator.samples // batch_size,

    validation_data = validation_generator, 

    validation_steps = validation_generator.samples // batch_size,

    epochs = nb_epochs)
					

https://keras.io/preprocessing/image/

?

keras.preprocessing.image.ImageDataGenerator(featurewise_center=False, samplewise_center=False, featurewise_std_normalization=False, samplewise_std_normalization=False, zca_whitening=False, zca_epsilon=1e-06, rotation_range=0, width_shift_range=0.0, height_shift_range=0.0, brightness_range=None, shear_range=0.0, zoom_range=0.0, channel_shift_range=0.0, fill_mode=‘nearest‘, cval=0.0, horizontal_flip=False, vertical_flip=False, rescale=None, preprocessing_function=None, data_format=‘channels_last‘, validation_split=0.0, interpolation_order=1, dtype=‘float32‘)

?

?

Does the validation_generator also augment data? After reading the comments from?github.com/keras-team/keras/issues/5862?it seems like it does.?–?bitnahian?May 9 at 13:54

Keras split train test set when using ImageDataGenerator

原文:https://www.cnblogs.com/xiexiaokui/p/12070356.html

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