dataset_info:
features:
- name: image
dtype: image
- name: label
dtype: string
splits:
- name: train
num_bytes: 297694107.22
num_examples: 4770
- name: val
num_bytes: 35589990
num_examples: 583
download_size: 650206163
dataset_size: 333284097.22
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
Dataset for buildings / city_landscapes classification, it has 53 labels:
{ 'autumn_city_street', 'cafe', 'cafe_building', 'car_in_city', 'cars_on_road', 'church_building', 'city_center', 'city_skyscrapers', 'construction', 'crowd_of_people', 'fountain', 'garden', 'garden_building', 'gothic_building', 'highway', 'hotel', 'lake', 'mansion', 'market', 'modern_bridge', 'modern_building', 'modern_city_street', 'monastery', 'monument', 'museum', 'night_city_street', 'night_winter_street', 'old_bridge', 'old_city_street', 'palace', 'panel_building', 'parking', 'pedestrian_street', 'river_in_city', 'road', 'russian_church', 'shopping_mall', 'signboard', 'skating_ring', 'stadium', 'street_art', 'subway', 'summer_city_street', 'tall_building', 'theatre', 'theatre_building', 'touristic_castle', 'tower', 'train_station', 'trees', 'village_houses', 'winter_city', 'winter_city_street' }