def base_model_weights_file(self):
if self.use_base_model_weights:
if self.use_ext_base_model_weights:
return assign_raise(self.cp[self.SECTION].get("base_model_weights_file"))
else:
return "imagenet"
else:
return None
def loss_function(self):
return assign_raise(self.cp[self.SECTION].get("loss_function"))
def output_weights_name(self):
return assign_raise(self.cp[self.SECTION].get("output_weights_name"))
def image_dir(self):
return assign_raise(self.cp["IMAGE"].get("image_source_dir"))
def class_names(self):
return assign_raise(self.cp["DATASET"].get("class_names").split(","))
def grad_cam_outputdir(self):
return assign_raise(self.cp["TEST"].get("grad_cam_outputdir"))
def data_entry(self):
return assign_raise(self.cp["DATASET"].get("data_entry_file"))
def normalize_by_mean_var(self):
return assign_raise(
self.cp[self.SECTION].getboolean("normalize_by_mean_var"))
def config_dilation(self):
return assign_raise(self.cp["DATASET"].getfloat("dataset_dilation"))
def class_mode(self):
return assign_raise(self.cp["DATASET"].get("class_mode"))
def output_dir(self):
return assign_raise(self.cp["DEFAULT"].get("output_dir"))