def get_function_signature(function, method=True):
wrapped = getattr(function, '_original_function', None)
if wrapped is None:
signature = generic_utils.getargspec(function)
else:
signature = generic_utils.getargspec(wrapped)
defaults = signature.defaults
if method:
args = signature.args[1:]
else:
args = signature.args
if defaults:
kwargs = zip(args[-len(defaults):], defaults)
args = args[:-len(defaults)]
else:
kwargs = []
st = '%s.%s(' % (clean_module_name(function.__module__), function.__name__)
for a in args:
st += str(a) + ', '
for a, v in kwargs:
if isinstance(v, str):
v = '\'' + v + '\''
st += str(a) + '=' + str(v) + ', '
if kwargs or args:
signature = st[:-2] + ')'
else:
signature = st + ')'
return post_process_signature(signature)
def __init__(self,
x,
y,
image_data_generator,
batch_size=32,
shuffle=False,
sample_weight=None,
seed=None,
data_format=None,
save_to_dir=None,
save_prefix='',
save_format='png',
subset=None,
dtype=None):
if data_format is None:
data_format = backend.image_data_format()
kwargs = {}
if 'dtype' in generic_utils.getargspec(
image.NumpyArrayIterator.__init__).args:
if dtype is None:
dtype = backend.floatx()
kwargs['dtype'] = dtype
super(NumpyArrayIterator, self).__init__(x,
y,
image_data_generator,
batch_size=batch_size,
shuffle=shuffle,
sample_weight=sample_weight,
seed=seed,
data_format=data_format,
save_to_dir=save_to_dir,
save_prefix=save_prefix,
save_format=save_format,
subset=subset,
**kwargs)
def img_to_array(img, data_format=None, dtype=None):
if data_format is None:
data_format = backend.image_data_format()
if 'dtype' in generic_utils.getargspec(image.img_to_array).args:
if dtype is None:
dtype = backend.floatx()
return image.img_to_array(img, data_format=data_format, dtype=dtype)
return image.img_to_array(img, data_format=data_format)
def __init__(
self,
contrast_stretching=False, # additional
histogram_equalization=False, # additional
adaptive_equalization=False, # additional
featurewise_center=False,
samplewise_center=False,
featurewise_std_normalization=False,
samplewise_std_normalization=False,
zca_whitening=False,
zca_epsilon=1e-6,
rotation_range=0,
width_shift_range=0.,
height_shift_range=0.,
brightness_range=None,
shear_range=0.,
zoom_range=0.,
channel_shift_range=0.,
fill_mode='nearest',
cval=0.,
horizontal_flip=False,
vertical_flip=False,
rescale=None,
preprocessing_function=None,
data_format=None,
validation_split=0.0,
dtype=None):
if data_format is None:
data_format = backend.image_data_format()
kwargs = {}
if 'dtype' in generic_utils.getargspec(
image.ImageDataGenerator.__init__).args:
if dtype is None:
dtype = backend.floatx()
kwargs['dtype'] = dtype
super(ImageDataGenerator, self).__init__(
featurewise_center=featurewise_center,
samplewise_center=samplewise_center,
featurewise_std_normalization=featurewise_std_normalization,
samplewise_std_normalization=samplewise_std_normalization,
zca_whitening=zca_whitening,
zca_epsilon=zca_epsilon,
rotation_range=rotation_range,
width_shift_range=width_shift_range,
height_shift_range=height_shift_range,
brightness_range=brightness_range,
shear_range=shear_range,
zoom_range=zoom_range,
channel_shift_range=channel_shift_range,
fill_mode=fill_mode,
cval=cval,
horizontal_flip=horizontal_flip,
vertical_flip=vertical_flip,
rescale=rescale,
preprocessing_function=preprocessing_function,
data_format=data_format,
validation_split=validation_split,
**kwargs)
def array_to_img(x, data_format=None, scale=True, dtype=None):
if data_format is None:
data_format = backend.image_data_format()
if 'dtype' in generic_utils.getargspec(image.array_to_img).args:
if dtype is None:
dtype = backend.floatx()
return image.array_to_img(x,
data_format=data_format,
scale=scale,
dtype=dtype)
return image.array_to_img(x, data_format=data_format, scale=scale)
def __init__(self,
directory,
image_data_generator,
target_size=(256, 256),
color_mode='rgb',
classes=None,
class_mode='categorical',
batch_size=32,
shuffle=True,
seed=None,
data_format=None,
save_to_dir=None,
save_prefix='',
save_format='png',
follow_links=False,
subset=None,
interpolation='nearest',
dtype=None):
if data_format is None:
data_format = backend.image_data_format()
kwargs = {}
if 'dtype' in generic_utils.getargspec(
image.ImageDataGenerator.__init__).args:
if dtype is None:
dtype = backend.floatx()
kwargs['dtype'] = dtype
super(DirectoryIterator, self).__init__(directory,
image_data_generator,
target_size=target_size,
color_mode=color_mode,
classes=classes,
class_mode=class_mode,
batch_size=batch_size,
shuffle=shuffle,
seed=seed,
data_format=data_format,
save_to_dir=save_to_dir,
save_prefix=save_prefix,
save_format=save_format,
follow_links=follow_links,
subset=subset,
interpolation=interpolation,
**kwargs)