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)