def create_cls(in_path,ae_path,out_path):
imgs=data.read_image_frame(in_path)
X=imgs['Images'].tolist()
y=imgs['Category'].tolist()
n_cats=max(y)+1
cls=comp.create_extractor(n_cats,ae_path)
deep.learning_iter_super(cls,X,y,n_epochs=1000)
utils.save_object(cls.get_model(),out_path)
return cls
def create_sda(in_path,out_path,cls_config_path):
imgs=data.read_image_frame(in_path)
X=imgs['Images'].tolist()
y=imgs['Category'].tolist()
n_cats=max(y)+1
hyper_params=tools.read_hyper_params(cls_config_path)
hyper_params['n_out']=n_cats
cls=sda.built_sda_cls(hyper_params)
deep.learning_iter_super(cls,X,y,n_epochs=1000)
utils.save_object(cls.model,out_path)
return cls
