问题
I'm training a semantic segmentation model using Keras with TensorFlow backend. I adopted ImageDataGenerator
to do the image augmentation, including rotation, flip and shift. By following the documentation, I created a dictionary maskgen_args
and used it as arguments to instantiate two ImageDataGenerator
instances.
maskgen_args = dict(
rotation_range=90,
validation_split=VALIDATION_SPLIT
)
image_datagen = ImageDataGenerator(**maskgen_args)
mask_datagen = ImageDataGenerator(**maskgen_args)
The training data generator is done as follows, by setting seed
to the same value, the mask will match the image.
training_data_generator = zip(
image_datagen.flow_from_directory(
data_dir,
target_size=(512, 512),
color_mode='rgb',
batch_size=BATCH_SIZE,
class_mode=None,
save_format='jpeg',
seed=GENERATE_SEED,
subset='training'
),
mask_datagen.flow_from_directory(
label_dir,
target_size=(512, 512),
color_mode='grayscale',
batch_size=BATCH_SIZE,
class_mode=None,
save_format='png',
seed=GENERATE_SEED,
subset='training'
)
)
So far, there is no problem occurred. But as I need to do some extra preprocessing (eg. normalization) only for the image but not for the mask, I created another imagegen_args
dictionary and used it as the arguments when instantiating the ImageDataGenerator
.
maskgen_args = dict(
rotation_range=90,
validation_split=VALIDATION_SPLIT
)
imagegen_args = dict(
samplewise_center=True,
samplewise_std_normalization=True,
channel_shift_range=10,
brightness_range=(0.7, 1.3),
**maskgen_args
)
image_datagen = ImageDataGenerator(**imagegen_args)
mask_datagen = ImageDataGenerator(**maskgen_args)
When I check the output of the training_data_generator
, problem occurred: seems the image and mask are generated separately: they surely have random rotation, but they are rotated in different angle, unlike before. Here is an example of a food image and the mask for the food.
I checked the id
of image_datagen
and mask_datagen
, both cases their id
are different. I wonder why the first case they can rotate the image and mask with the same random angle, but not in the second case? What should I do to make them behave like the first case when I indeed need to give extra arguments to image_datagen
?
回答1:
When you set
channel_shift_range=10,
brightness_range=(0.7, 1.3)
This modifies the RNG of this generator so that the Image RNG and the Mask RNG are not in sync anymore.
I propose you use a custom Sequence for this task until the KP new API is released. (see https://github.com/keras-team/governance/blob/master/rfcs/20190729-keras-preprocessing-redesign.md)
For an example of a custom Sequence, I propose an example here: https://dref360.github.io/deterministic-da/
来源:https://stackoverflow.com/questions/58846552/keras-imagedatagenerator-image-and-mask-augments-differently