def create_cls(img_path,ae_path,out_path): img_frame=images.read_image_frame(img_path) n_cats=data.get_n_cats(img_frame) print(n_cats) cls=comp.create_extractor(n_cats,ae_path) #cls=nn.built_nn_cls(n_cats) cls=deep.learning_iter(img_frame,cls,n_epochs=1000) utils.save_object(cls.get_model(),out_path) return cls
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