--multi-class not splitting images with multiple boxes correctly about cocosplit HOT 3 OPEN

        annotation_categories = funcy.lmap(lambda a: int(a['category_id']), annotations)

        #bottle neck 1
        #remove classes that has only one sample, because it can't be split into the training and testing sets
        annotation_categories =  funcy.lremove(lambda i: annotation_categories.count(i) <=1  , annotation_categories)

        filtered_annotations =  funcy.lremove(lambda i: i['category_id'] not in annotation_categories  , annotations)

        X_train, y_train, X_test, y_test = iterative_train_test_split(np.array([filtered_annotations]).T,np.array([ annotation_categories]).T, test_size = 1-args.split)

        img_train = filter_images(images, X_train.reshape(-1))
        img_test = filter_images(images, X_test.reshape(-1))
        
        image_test_ids = funcy.lmap(lambda i: int(i['id']), img_test)
        img_train = funcy.lremove(lambda a: int(a['id']) in image_test_ids, img_train)
        
        anns_train = filter_annotations(annotations, img_train)
        anns_test = filter_annotations(annotations, img_test)
        
        save_coco(args.train, info, licenses, img_train, anns_train, categories)
        save_coco(args.test, info, licenses,  img_test, anns_test, categories)

        print("Saved {} entries in {} and {} in {}".format(len(anns_train), args.train, len(anns_test), args.test))