def compile(self, image_shape=(3060, 4060)):
self.logger.info('Compiling saliency network convolution function...')
ratio = config.filtersize[0] / config.data_imsize[0]
targetsize = np.round(np.array(image_shape) * ratio).astype(int)
saliency_conv_model = models.get_saliency_network(train=False, shape=targetsize)
self.convolution_function = keras_helpers.get_convolution_function(
self.saliency_network, saliency_conv_model)
def __init__(self, logger='default'):
if logger == 'default':
self.logger = util.get_default_logger()
else:
self.logger = logger
self.saliency_network = models.get_saliency_network(
train=True, compile=False)
