Update phao_dataset.py

phao_dataset.py

@@ -1,306 +1,306 @@
-# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""MIT Scene Parsing Benchmark."""
-
-
-import os
-
-import pandas as pd
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{zhou2017scene,
-    title={Scene Parsing through ADE20K Dataset},
-    author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
-    booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
-    year={2017}
-}
-
-@article{zhou2016semantic,
-  title={Semantic understanding of scenes through the ade20k dataset},
-  author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
-  journal={arXiv preprint arXiv:1608.05442},
-  year={2016}
-}
-"""
-
-_DESCRIPTION = """\
-Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed.
-MIT Scene Parsing Benchmark (SceneParse150) provides a standard training and evaluation platform for the algorithms of scene parsing.
-The data for this benchmark comes from ADE20K Dataset which contains more than 20K scene-centric images exhaustively annotated with objects and object parts.
-Specifically, the benchmark is divided into 20K images for training, 2K images for validation, and another batch of held-out images for testing.
-There are totally 150 semantic categories included for evaluation, which include stuffs like sky, road, grass, and discrete objects like person, car, bed.
-Note that there are non-uniform distribution of objects occuring in the images, mimicking a more natural object occurrence in daily scene.
-"""
-
-_HOMEPAGE = "http://sceneparsing.csail.mit.edu/"
-
-_LICENSE = "BSD 3-Clause License"
-
-_URLS = {
-    "scene_parsing": {
-        "train/val": "https://phaodataset.s3.ap-southeast-2.amazonaws.com/LabelPhao.zip",
-        "test": "https://phaodataset.s3.ap-southeast-2.amazonaws.com/release_test.zip",
-    },
-    "instance_segmentation": {
-        "images": "https://phaodataset.s3.ap-southeast-2.amazonaws.com/images.zip",
-        "annotations": "https://phaodataset.s3.ap-southeast-2.amazonaws.com/annotations_instance.zip",
-        "test": "https://phaodataset.s3.ap-southeast-2.amazonaws.com/testing.zip",
-    },
-}
-
-_SCENE_CATEGORIES = """\
-airport_terminal art_gallery badlands ball_pit bathroom beach bedroom booth_indoor botanical_garden bridge bullring
-bus_interior butte canyon casino_outdoor castle church_outdoor closet coast conference_room construction_site corral
-corridor crosswalk day_care_center sand elevator_interior escalator_indoor forest_road gangplank gas_station
-golf_course gymnasium_indoor harbor hayfield heath hoodoo house hunting_lodge_outdoor ice_shelf joss_house kiosk_indoor
-kitchen landfill library_indoor lido_deck_outdoor living_room locker_room market_outdoor mountain_snowy office orchard
-arbor bookshelf mews nook preserve traffic_island palace palace_hall pantry patio phone_booth establishment
-poolroom_home quonset_hut_outdoor rice_paddy sandbox shopfront skyscraper stone_circle subway_interior platform
-supermarket swimming_pool_outdoor television_studio indoor_procenium train_railway coral_reef viaduct wave wind_farm
-bottle_storage abbey access_road air_base airfield airlock airplane_cabin airport entrance airport_ticket_counter
-alcove alley amphitheater amusement_arcade amusement_park anechoic_chamber apartment_building_outdoor apse_indoor
-apse_outdoor aquarium aquatic_theater aqueduct arcade arch archaelogical_excavation archive basketball football hockey
-performance rodeo soccer armory army_base arrival_gate_indoor arrival_gate_outdoor art_school art_studio artists_loft
-assembly_line athletic_field_indoor athletic_field_outdoor atrium_home atrium_public attic auditorium auto_factory
-auto_mechanics_indoor auto_mechanics_outdoor auto_racing_paddock auto_showroom backstage backstairs
-badminton_court_indoor badminton_court_outdoor baggage_claim shop exterior balcony_interior ballroom bamboo_forest
-bank_indoor bank_outdoor bank_vault banquet_hall baptistry_indoor baptistry_outdoor bar barbershop barn barndoor
-barnyard barrack baseball_field basement basilica basketball_court_indoor basketball_court_outdoor bathhouse
-batters_box batting_cage_indoor batting_cage_outdoor battlement bayou bazaar_indoor bazaar_outdoor beach_house
-beauty_salon bedchamber beer_garden beer_hall belfry bell_foundry berth berth_deck betting_shop bicycle_racks bindery
-biology_laboratory bistro_indoor bistro_outdoor bleachers_indoor bleachers_outdoor boardwalk boat_deck boathouse bog
-bomb_shelter_indoor bookbindery bookstore bow_window_indoor bow_window_outdoor bowling_alley box_seat boxing_ring
-breakroom brewery_indoor brewery_outdoor brickyard_indoor brickyard_outdoor building_complex building_facade bullpen
-burial_chamber bus_depot_indoor bus_depot_outdoor bus_shelter bus_station_indoor bus_station_outdoor butchers_shop
-cabana cabin_indoor cabin_outdoor cafeteria call_center campsite campus natural urban candy_store canteen
-car_dealership backseat frontseat caravansary cardroom cargo_container_interior airplane boat freestanding
-carport_indoor carport_outdoor carrousel casino_indoor catacomb cathedral_indoor cathedral_outdoor catwalk
-cavern_indoor cavern_outdoor cemetery chalet chaparral chapel checkout_counter cheese_factory chemical_plant
-chemistry_lab chicken_coop_indoor chicken_coop_outdoor chicken_farm_indoor chicken_farm_outdoor childs_room
-choir_loft_interior church_indoor circus_tent_indoor circus_tent_outdoor city classroom clean_room cliff booth room
-clock_tower_indoor cloister_indoor cloister_outdoor clothing_store coast_road cockpit coffee_shop computer_room
-conference_center conference_hall confessional control_room control_tower_indoor control_tower_outdoor
-convenience_store_indoor convenience_store_outdoor corn_field cottage cottage_garden courthouse courtroom courtyard
-covered_bridge_interior crawl_space creek crevasse library cybercafe dacha dairy_indoor dairy_outdoor dam dance_school
-darkroom delicatessen dentists_office department_store departure_lounge vegetation desert_road diner_indoor
-diner_outdoor dinette_home vehicle dining_car dining_hall dining_room dirt_track discotheque distillery ditch dock
-dolmen donjon doorway_indoor doorway_outdoor dorm_room downtown drainage_ditch dress_shop dressing_room drill_rig
-driveway driving_range_indoor driving_range_outdoor drugstore dry_dock dugout earth_fissure editing_room
-electrical_substation elevated_catwalk door freight_elevator elevator_lobby elevator_shaft embankment embassy
-engine_room entrance_hall escalator_outdoor escarpment estuary excavation exhibition_hall fabric_store factory_indoor
-factory_outdoor fairway farm fastfood_restaurant fence cargo_deck ferryboat_indoor passenger_deck cultivated wild
-field_road fire_escape fire_station firing_range_indoor firing_range_outdoor fish_farm fishmarket fishpond
-fitting_room_interior fjord flea_market_indoor flea_market_outdoor floating_dry_dock flood florist_shop_indoor
-florist_shop_outdoor fly_bridge food_court football_field broadleaf needleleaf forest_fire forest_path formal_garden
-fort fortress foundry_indoor foundry_outdoor fountain freeway funeral_chapel funeral_home furnace_room galley game_room
-garage_indoor garage_outdoor garbage_dump gasworks gate gatehouse gazebo_interior general_store_indoor
-general_store_outdoor geodesic_dome_indoor geodesic_dome_outdoor ghost_town gift_shop glacier glade gorge granary
-great_hall greengrocery greenhouse_indoor greenhouse_outdoor grotto guardhouse gulch gun_deck_indoor gun_deck_outdoor
-gun_store hacienda hallway handball_court hangar_indoor hangar_outdoor hardware_store hat_shop hatchery hayloft hearth
-hedge_maze hedgerow heliport herb_garden highway hill home_office home_theater hospital hospital_room hot_spring
-hot_tub_indoor hot_tub_outdoor hotel_outdoor hotel_breakfast_area hotel_room hunting_lodge_indoor hut ice_cream_parlor
-ice_floe ice_skating_rink_indoor ice_skating_rink_outdoor iceberg igloo imaret incinerator_indoor incinerator_outdoor
-industrial_area industrial_park inn_indoor inn_outdoor irrigation_ditch islet jacuzzi_indoor jacuzzi_outdoor
-jail_indoor jail_outdoor jail_cell japanese_garden jetty jewelry_shop junk_pile junkyard jury_box kasbah kennel_indoor
-kennel_outdoor kindergarden_classroom kiosk_outdoor kitchenette lab_classroom labyrinth_indoor labyrinth_outdoor lagoon
-artificial landing landing_deck laundromat lava_flow lavatory lawn lean-to lecture_room legislative_chamber levee
-library_outdoor lido_deck_indoor lift_bridge lighthouse limousine_interior liquor_store_indoor liquor_store_outdoor
-loading_dock lobby lock_chamber loft lookout_station_indoor lookout_station_outdoor lumberyard_indoor
-lumberyard_outdoor machine_shop manhole mansion manufactured_home market_indoor marsh martial_arts_gym mastaba
-maternity_ward mausoleum medina menhir mesa mess_hall mezzanine military_hospital military_hut military_tent mine
-mineshaft mini_golf_course_indoor mini_golf_course_outdoor mission dry water mobile_home monastery_indoor
-monastery_outdoor moon_bounce moor morgue mosque_indoor mosque_outdoor motel mountain mountain_path mountain_road
-movie_theater_indoor movie_theater_outdoor mudflat museum_indoor museum_outdoor music_store music_studio misc
-natural_history_museum naval_base newsroom newsstand_indoor newsstand_outdoor nightclub nuclear_power_plant_indoor
-nuclear_power_plant_outdoor nunnery nursery nursing_home oasis oast_house observatory_indoor observatory_outdoor
-observatory_post ocean office_building office_cubicles oil_refinery_indoor oil_refinery_outdoor oilrig operating_room
-optician organ_loft_interior orlop_deck ossuary outcropping outhouse_indoor outhouse_outdoor overpass oyster_bar
-oyster_farm acropolis aircraft_carrier_object amphitheater_indoor archipelago questionable assembly_hall assembly_plant
-awning_deck back_porch backdrop backroom backstage_outdoor backstairs_indoor backwoods ballet balustrade barbeque
-basin_outdoor bath_indoor bath_outdoor bathhouse_outdoor battlefield bay booth_outdoor bottomland breakfast_table
-bric-a-brac brooklet bubble_chamber buffet bulkhead bunk_bed bypass byroad cabin_cruiser cargo_helicopter cellar
-chair_lift cocktail_lounge corner country_house country_road customhouse dance_floor deck-house_boat_deck_house
-deck-house_deck_house dining_area diving_board embrasure entranceway_indoor entranceway_outdoor entryway_outdoor
-estaminet farm_building farmhouse feed_bunk field_house field_tent_indoor field_tent_outdoor fire_trench fireplace
-flashflood flatlet floating_dock flood_plain flowerbed flume_indoor flying_buttress foothill forecourt foreshore
-front_porch garden gas_well glen grape_arbor grove guardroom guesthouse gymnasium_outdoor head_shop hen_yard hillock
-housing_estate housing_project howdah inlet insane_asylum outside juke_joint jungle kraal laboratorywet landing_strip
-layby lean-to_tent loge loggia_outdoor lower_deck luggage_van mansard meadow meat_house megalith mens_store_outdoor
-mental_institution_indoor mental_institution_outdoor military_headquarters millpond millrace natural_spring
-nursing_home_outdoor observation_station open-hearth_furnace operating_table outbuilding palestra parkway patio_indoor
-pavement pawnshop_outdoor pinetum piste_road pizzeria_outdoor powder_room pumping_station reception_room rest_stop
-retaining_wall rift_valley road rock_garden rotisserie safari_park salon saloon sanatorium science_laboratory scrubland
-scullery seaside semidesert shelter shelter_deck shelter_tent shore shrubbery sidewalk snack_bar snowbank stage_set
-stall stateroom store streetcar_track student_center study_hall sugar_refinery sunroom supply_chamber t-bar_lift
-tannery teahouse threshing_floor ticket_window_indoor tidal_basin tidal_river tiltyard tollgate tomb tract_housing
-trellis truck_stop upper_balcony vestibule vinery walkway war_room washroom water_fountain water_gate waterscape
-waterway wetland widows_walk_indoor windstorm packaging_plant pagoda paper_mill park parking_garage_indoor
-parking_garage_outdoor parking_lot parlor particle_accelerator party_tent_indoor party_tent_outdoor pasture pavilion
-pawnshop pedestrian_overpass_indoor penalty_box pet_shop pharmacy physics_laboratory piano_store picnic_area pier
-pig_farm pilothouse_indoor pilothouse_outdoor pitchers_mound pizzeria planetarium_indoor planetarium_outdoor
-plantation_house playground playroom plaza podium_indoor podium_outdoor police_station pond pontoon_bridge poop_deck
-porch portico portrait_studio postern power_plant_outdoor print_shop priory promenade promenade_deck pub_indoor
-pub_outdoor pulpit putting_green quadrangle quicksand quonset_hut_indoor racecourse raceway raft railroad_track
-railway_yard rainforest ramp ranch ranch_house reading_room reception recreation_room rectory recycling_plant_indoor
-refectory repair_shop residential_neighborhood resort rest_area restaurant restaurant_kitchen restaurant_patio
-restroom_indoor restroom_outdoor revolving_door riding_arena river road_cut rock_arch roller_skating_rink_indoor
-roller_skating_rink_outdoor rolling_mill roof roof_garden root_cellar rope_bridge roundabout roundhouse rubble ruin
-runway sacristy salt_plain sand_trap sandbar sauna savanna sawmill schoolhouse schoolyard science_museum scriptorium
-sea_cliff seawall security_check_point server_room sewer sewing_room shed shipping_room shipyard_outdoor shoe_shop
-shopping_mall_indoor shopping_mall_outdoor shower shower_room shrine signal_box sinkhole ski_jump ski_lodge ski_resort
-ski_slope sky skywalk_indoor skywalk_outdoor slum snowfield massage_room mineral_bath spillway sporting_goods_store
-squash_court stable baseball stadium_outdoor stage_indoor stage_outdoor staircase starting_gate steam_plant_outdoor
-steel_mill_indoor storage_room storm_cellar street strip_mall strip_mine student_residence submarine_interior sun_deck
-sushi_bar swamp swimming_hole swimming_pool_indoor synagogue_indoor synagogue_outdoor taxistand taxiway tea_garden
-tearoom teashop television_room east_asia mesoamerican south_asia western tennis_court_indoor tennis_court_outdoor
-tent_outdoor terrace_farm indoor_round indoor_seats theater_outdoor thriftshop throne_room ticket_booth
-tobacco_shop_indoor toll_plaza tollbooth topiary_garden tower town_house toyshop track_outdoor trading_floor
-trailer_park train_interior train_station_outdoor station tree_farm tree_house trench trestle_bridge tundra rail_indoor
-rail_outdoor road_indoor road_outdoor turkish_bath ocean_deep ocean_shallow utility_room valley van_interior
-vegetable_garden velodrome_indoor velodrome_outdoor ventilation_shaft veranda vestry veterinarians_office videostore
-village vineyard volcano volleyball_court_indoor volleyball_court_outdoor voting_booth waiting_room walk_in_freezer
-warehouse_indoor warehouse_outdoor washhouse_indoor washhouse_outdoor watchtower water_mill water_park water_tower
-water_treatment_plant_indoor water_treatment_plant_outdoor block cascade cataract fan plunge watering_hole weighbridge
-wet_bar wharf wheat_field whispering_gallery widows_walk_interior windmill window_seat barrel_storage winery
-witness_stand woodland workroom workshop wrestling_ring_indoor wrestling_ring_outdoor yard youth_hostel zen_garden
-ziggurat zoo forklift hollow hutment pueblo vat perfume_shop steel_mill_outdoor orchestra_pit bridle_path lyceum
-one-way_street parade_ground pump_room recycling_plant_outdoor chuck_wagon
-"""
-_SCENE_CATEGORIES = _SCENE_CATEGORIES.strip().split()
-
-
-class SceneParse150(datasets.GeneratorBasedBuilder):
-    """MIT Scene Parsing Benchmark dataset."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="scene_parsing", version=VERSION, description="The scene parsing variant."),
-        datasets.BuilderConfig(
-            name="instance_segmentation", version=VERSION, description="The instance segmentation variant."
-        ),
-    ]
-
-    DEFAULT_CONFIG_NAME = "scene_parsing"
-
-    def _info(self):
-        if self.config.name == "scene_parsing":
-            features = datasets.Features(
-                {
-                    "image": datasets.Image(),
-                    "annotation": datasets.Image(),
-                    "scene_category": datasets.ClassLabel(names=_SCENE_CATEGORIES),
-                }
-            )
-        else:
-            features = datasets.Features(
-                {
-                    "image": datasets.Image(),
-                    "annotation": datasets.Image(),
-                }
-            )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        urls = _URLS[self.config.name]
-
-        if self.config.name == "scene_parsing":
-            data_dirs = dl_manager.download_and_extract(urls)
-            train_data = val_data = os.path.join(data_dirs["train/val"], "ADEChallengeData2016")
-            test_data = os.path.join(data_dirs["test"], "release_test")
-        else:
-            data_dirs = dl_manager.download(urls)
-            train_data = dl_manager.iter_archive(data_dirs["images"]), dl_manager.iter_archive(
-                data_dirs["annotations"]
-            )
-            val_data = dl_manager.iter_archive(data_dirs["images"]), dl_manager.iter_archive(data_dirs["annotations"])
-            test_data = dl_manager.iter_archive(data_dirs["test"])
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "data": train_data,
-                    "split": "training",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"data": test_data, "split": "testing"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "data": val_data,
-                    "split": "validation",
-                },
-            ),
-        ]
-
-    def _generate_examples(self, data, split):
-        if self.config.name == "scene_parsing":
-            if split == "testing":
-                image_dir = os.path.join(data, split)
-                for idx, image_file in enumerate(os.listdir(image_dir)):
-                    yield idx, {
-                        "image": os.path.join(image_dir, image_file),
-                        "annotation": None,
-                        "scene_category": None,
-                    }
-            else:
-                image_id2cat = pd.read_csv(
-                    os.path.join(data, "sceneCategories.txt"), sep=" ", names=["image_id", "scene_category"]
-                )
-                image_id2cat = image_id2cat.set_index("image_id")
-                images_dir = os.path.join(data, "images", split)
-                annotations_dir = os.path.join(data, "annotations", split)
-                for idx, image_file in enumerate(os.listdir(images_dir)):
-                    image_id = image_file.split(".")[0]
-                    yield idx, {
-                        "image": os.path.join(images_dir, image_file),
-                        "annotation": os.path.join(annotations_dir, image_id + ".png"),
-                        "scene_category": image_id2cat.loc[image_id, "scene_category"],
-                    }
-        else:
-            if split == "testing":
-                for idx, (path, file) in enumerate(data):
-                    if path.endswith(".jpg"):
-                        yield idx, {
-                            "image": {"path": path, "bytes": file.read()},
-                            "annotation": None,
-                        }
-            else:
-                images, annotations = data
-                image_id2annot = {}
-                # loads the annotations for the split into RAM (less than 100 MB) to support streaming
-                for path_annot, file_annot in annotations:
-                    if split in path_annot and path_annot.endswith(".png"):
-                        image_id = os.path.basename(path_annot).split(".")[0]
-                        image_id2annot[image_id] = (path_annot, file_annot.read())
-                for idx, (path_img, file_img) in enumerate(images):
-                    if split in path_img and path_img.endswith(".jpg"):
-                        image_id = os.path.basename(path_img).split(".")[0]
-                        path_annot, bytes_annot = image_id2annot[image_id]
-                        yield idx, {
-                            "image": {"path": path_img, "bytes": file_img.read()},
-                            "annotation": {"path": path_annot, "bytes": bytes_annot},
+# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""MIT Scene Parsing Benchmark."""
+
+
+import os
+
+import pandas as pd
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{zhou2017scene,
+    title={Scene Parsing through ADE20K Dataset},
+    author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
+    booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
+    year={2017}
+}
+
+@article{zhou2016semantic,
+  title={Semantic understanding of scenes through the ade20k dataset},
+  author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
+  journal={arXiv preprint arXiv:1608.05442},
+  year={2016}
+}
+"""
+
+_DESCRIPTION = """\
+Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed.
+MIT Scene Parsing Benchmark (SceneParse150) provides a standard training and evaluation platform for the algorithms of scene parsing.
+The data for this benchmark comes from ADE20K Dataset which contains more than 20K scene-centric images exhaustively annotated with objects and object parts.
+Specifically, the benchmark is divided into 20K images for training, 2K images for validation, and another batch of held-out images for testing.
+There are totally 150 semantic categories included for evaluation, which include stuffs like sky, road, grass, and discrete objects like person, car, bed.
+Note that there are non-uniform distribution of objects occuring in the images, mimicking a more natural object occurrence in daily scene.
+"""
+
+_HOMEPAGE = "http://sceneparsing.csail.mit.edu/"
+
+_LICENSE = "BSD 3-Clause License"
+
+_URLS = {
+    "scene_parsing": {
+        "train/val": "https://phaotestjson.s3.ap-southeast-2.amazonaws.com/LabelPhao.zip",
+        "test": "https://phaotestjson.s3.ap-southeast-2.amazonaws.com/release_test.zip",
+    },
+    "instance_segmentation": {
+        "images": "https://phaotestjson.s3.ap-southeast-2.amazonaws.com/images.zip",
+        "annotations": "https://phaotestjson.s3.ap-southeast-2.amazonaws.com/annotations_instance.zip",
+        "test": "https://phaotestjson.s3.ap-southeast-2.amazonaws.com/testing.zip",
+    },
+}
+
+_SCENE_CATEGORIES = """\
+airport_terminal art_gallery badlands ball_pit bathroom beach bedroom booth_indoor botanical_garden bridge bullring
+bus_interior butte canyon casino_outdoor castle church_outdoor closet coast conference_room construction_site corral
+corridor crosswalk day_care_center sand elevator_interior escalator_indoor forest_road gangplank gas_station
+golf_course gymnasium_indoor harbor hayfield heath hoodoo house hunting_lodge_outdoor ice_shelf joss_house kiosk_indoor
+kitchen landfill library_indoor lido_deck_outdoor living_room locker_room market_outdoor mountain_snowy office orchard
+arbor bookshelf mews nook preserve traffic_island palace palace_hall pantry patio phone_booth establishment
+poolroom_home quonset_hut_outdoor rice_paddy sandbox shopfront skyscraper stone_circle subway_interior platform
+supermarket swimming_pool_outdoor television_studio indoor_procenium train_railway coral_reef viaduct wave wind_farm
+bottle_storage abbey access_road air_base airfield airlock airplane_cabin airport entrance airport_ticket_counter
+alcove alley amphitheater amusement_arcade amusement_park anechoic_chamber apartment_building_outdoor apse_indoor
+apse_outdoor aquarium aquatic_theater aqueduct arcade arch archaelogical_excavation archive basketball football hockey
+performance rodeo soccer armory army_base arrival_gate_indoor arrival_gate_outdoor art_school art_studio artists_loft
+assembly_line athletic_field_indoor athletic_field_outdoor atrium_home atrium_public attic auditorium auto_factory
+auto_mechanics_indoor auto_mechanics_outdoor auto_racing_paddock auto_showroom backstage backstairs
+badminton_court_indoor badminton_court_outdoor baggage_claim shop exterior balcony_interior ballroom bamboo_forest
+bank_indoor bank_outdoor bank_vault banquet_hall baptistry_indoor baptistry_outdoor bar barbershop barn barndoor
+barnyard barrack baseball_field basement basilica basketball_court_indoor basketball_court_outdoor bathhouse
+batters_box batting_cage_indoor batting_cage_outdoor battlement bayou bazaar_indoor bazaar_outdoor beach_house
+beauty_salon bedchamber beer_garden beer_hall belfry bell_foundry berth berth_deck betting_shop bicycle_racks bindery
+biology_laboratory bistro_indoor bistro_outdoor bleachers_indoor bleachers_outdoor boardwalk boat_deck boathouse bog
+bomb_shelter_indoor bookbindery bookstore bow_window_indoor bow_window_outdoor bowling_alley box_seat boxing_ring
+breakroom brewery_indoor brewery_outdoor brickyard_indoor brickyard_outdoor building_complex building_facade bullpen
+burial_chamber bus_depot_indoor bus_depot_outdoor bus_shelter bus_station_indoor bus_station_outdoor butchers_shop
+cabana cabin_indoor cabin_outdoor cafeteria call_center campsite campus natural urban candy_store canteen
+car_dealership backseat frontseat caravansary cardroom cargo_container_interior airplane boat freestanding
+carport_indoor carport_outdoor carrousel casino_indoor catacomb cathedral_indoor cathedral_outdoor catwalk
+cavern_indoor cavern_outdoor cemetery chalet chaparral chapel checkout_counter cheese_factory chemical_plant
+chemistry_lab chicken_coop_indoor chicken_coop_outdoor chicken_farm_indoor chicken_farm_outdoor childs_room
+choir_loft_interior church_indoor circus_tent_indoor circus_tent_outdoor city classroom clean_room cliff booth room
+clock_tower_indoor cloister_indoor cloister_outdoor clothing_store coast_road cockpit coffee_shop computer_room
+conference_center conference_hall confessional control_room control_tower_indoor control_tower_outdoor
+convenience_store_indoor convenience_store_outdoor corn_field cottage cottage_garden courthouse courtroom courtyard
+covered_bridge_interior crawl_space creek crevasse library cybercafe dacha dairy_indoor dairy_outdoor dam dance_school
+darkroom delicatessen dentists_office department_store departure_lounge vegetation desert_road diner_indoor
+diner_outdoor dinette_home vehicle dining_car dining_hall dining_room dirt_track discotheque distillery ditch dock
+dolmen donjon doorway_indoor doorway_outdoor dorm_room downtown drainage_ditch dress_shop dressing_room drill_rig
+driveway driving_range_indoor driving_range_outdoor drugstore dry_dock dugout earth_fissure editing_room
+electrical_substation elevated_catwalk door freight_elevator elevator_lobby elevator_shaft embankment embassy
+engine_room entrance_hall escalator_outdoor escarpment estuary excavation exhibition_hall fabric_store factory_indoor
+factory_outdoor fairway farm fastfood_restaurant fence cargo_deck ferryboat_indoor passenger_deck cultivated wild
+field_road fire_escape fire_station firing_range_indoor firing_range_outdoor fish_farm fishmarket fishpond
+fitting_room_interior fjord flea_market_indoor flea_market_outdoor floating_dry_dock flood florist_shop_indoor
+florist_shop_outdoor fly_bridge food_court football_field broadleaf needleleaf forest_fire forest_path formal_garden
+fort fortress foundry_indoor foundry_outdoor fountain freeway funeral_chapel funeral_home furnace_room galley game_room
+garage_indoor garage_outdoor garbage_dump gasworks gate gatehouse gazebo_interior general_store_indoor
+general_store_outdoor geodesic_dome_indoor geodesic_dome_outdoor ghost_town gift_shop glacier glade gorge granary
+great_hall greengrocery greenhouse_indoor greenhouse_outdoor grotto guardhouse gulch gun_deck_indoor gun_deck_outdoor
+gun_store hacienda hallway handball_court hangar_indoor hangar_outdoor hardware_store hat_shop hatchery hayloft hearth
+hedge_maze hedgerow heliport herb_garden highway hill home_office home_theater hospital hospital_room hot_spring
+hot_tub_indoor hot_tub_outdoor hotel_outdoor hotel_breakfast_area hotel_room hunting_lodge_indoor hut ice_cream_parlor
+ice_floe ice_skating_rink_indoor ice_skating_rink_outdoor iceberg igloo imaret incinerator_indoor incinerator_outdoor
+industrial_area industrial_park inn_indoor inn_outdoor irrigation_ditch islet jacuzzi_indoor jacuzzi_outdoor
+jail_indoor jail_outdoor jail_cell japanese_garden jetty jewelry_shop junk_pile junkyard jury_box kasbah kennel_indoor
+kennel_outdoor kindergarden_classroom kiosk_outdoor kitchenette lab_classroom labyrinth_indoor labyrinth_outdoor lagoon
+artificial landing landing_deck laundromat lava_flow lavatory lawn lean-to lecture_room legislative_chamber levee
+library_outdoor lido_deck_indoor lift_bridge lighthouse limousine_interior liquor_store_indoor liquor_store_outdoor
+loading_dock lobby lock_chamber loft lookout_station_indoor lookout_station_outdoor lumberyard_indoor
+lumberyard_outdoor machine_shop manhole mansion manufactured_home market_indoor marsh martial_arts_gym mastaba
+maternity_ward mausoleum medina menhir mesa mess_hall mezzanine military_hospital military_hut military_tent mine
+mineshaft mini_golf_course_indoor mini_golf_course_outdoor mission dry water mobile_home monastery_indoor
+monastery_outdoor moon_bounce moor morgue mosque_indoor mosque_outdoor motel mountain mountain_path mountain_road
+movie_theater_indoor movie_theater_outdoor mudflat museum_indoor museum_outdoor music_store music_studio misc
+natural_history_museum naval_base newsroom newsstand_indoor newsstand_outdoor nightclub nuclear_power_plant_indoor
+nuclear_power_plant_outdoor nunnery nursery nursing_home oasis oast_house observatory_indoor observatory_outdoor
+observatory_post ocean office_building office_cubicles oil_refinery_indoor oil_refinery_outdoor oilrig operating_room
+optician organ_loft_interior orlop_deck ossuary outcropping outhouse_indoor outhouse_outdoor overpass oyster_bar
+oyster_farm acropolis aircraft_carrier_object amphitheater_indoor archipelago questionable assembly_hall assembly_plant
+awning_deck back_porch backdrop backroom backstage_outdoor backstairs_indoor backwoods ballet balustrade barbeque
+basin_outdoor bath_indoor bath_outdoor bathhouse_outdoor battlefield bay booth_outdoor bottomland breakfast_table
+bric-a-brac brooklet bubble_chamber buffet bulkhead bunk_bed bypass byroad cabin_cruiser cargo_helicopter cellar
+chair_lift cocktail_lounge corner country_house country_road customhouse dance_floor deck-house_boat_deck_house
+deck-house_deck_house dining_area diving_board embrasure entranceway_indoor entranceway_outdoor entryway_outdoor
+estaminet farm_building farmhouse feed_bunk field_house field_tent_indoor field_tent_outdoor fire_trench fireplace
+flashflood flatlet floating_dock flood_plain flowerbed flume_indoor flying_buttress foothill forecourt foreshore
+front_porch garden gas_well glen grape_arbor grove guardroom guesthouse gymnasium_outdoor head_shop hen_yard hillock
+housing_estate housing_project howdah inlet insane_asylum outside juke_joint jungle kraal laboratorywet landing_strip
+layby lean-to_tent loge loggia_outdoor lower_deck luggage_van mansard meadow meat_house megalith mens_store_outdoor
+mental_institution_indoor mental_institution_outdoor military_headquarters millpond millrace natural_spring
+nursing_home_outdoor observation_station open-hearth_furnace operating_table outbuilding palestra parkway patio_indoor
+pavement pawnshop_outdoor pinetum piste_road pizzeria_outdoor powder_room pumping_station reception_room rest_stop
+retaining_wall rift_valley road rock_garden rotisserie safari_park salon saloon sanatorium science_laboratory scrubland
+scullery seaside semidesert shelter shelter_deck shelter_tent shore shrubbery sidewalk snack_bar snowbank stage_set
+stall stateroom store streetcar_track student_center study_hall sugar_refinery sunroom supply_chamber t-bar_lift
+tannery teahouse threshing_floor ticket_window_indoor tidal_basin tidal_river tiltyard tollgate tomb tract_housing
+trellis truck_stop upper_balcony vestibule vinery walkway war_room washroom water_fountain water_gate waterscape
+waterway wetland widows_walk_indoor windstorm packaging_plant pagoda paper_mill park parking_garage_indoor
+parking_garage_outdoor parking_lot parlor particle_accelerator party_tent_indoor party_tent_outdoor pasture pavilion
+pawnshop pedestrian_overpass_indoor penalty_box pet_shop pharmacy physics_laboratory piano_store picnic_area pier
+pig_farm pilothouse_indoor pilothouse_outdoor pitchers_mound pizzeria planetarium_indoor planetarium_outdoor
+plantation_house playground playroom plaza podium_indoor podium_outdoor police_station pond pontoon_bridge poop_deck
+porch portico portrait_studio postern power_plant_outdoor print_shop priory promenade promenade_deck pub_indoor
+pub_outdoor pulpit putting_green quadrangle quicksand quonset_hut_indoor racecourse raceway raft railroad_track
+railway_yard rainforest ramp ranch ranch_house reading_room reception recreation_room rectory recycling_plant_indoor
+refectory repair_shop residential_neighborhood resort rest_area restaurant restaurant_kitchen restaurant_patio
+restroom_indoor restroom_outdoor revolving_door riding_arena river road_cut rock_arch roller_skating_rink_indoor
+roller_skating_rink_outdoor rolling_mill roof roof_garden root_cellar rope_bridge roundabout roundhouse rubble ruin
+runway sacristy salt_plain sand_trap sandbar sauna savanna sawmill schoolhouse schoolyard science_museum scriptorium
+sea_cliff seawall security_check_point server_room sewer sewing_room shed shipping_room shipyard_outdoor shoe_shop
+shopping_mall_indoor shopping_mall_outdoor shower shower_room shrine signal_box sinkhole ski_jump ski_lodge ski_resort
+ski_slope sky skywalk_indoor skywalk_outdoor slum snowfield massage_room mineral_bath spillway sporting_goods_store
+squash_court stable baseball stadium_outdoor stage_indoor stage_outdoor staircase starting_gate steam_plant_outdoor
+steel_mill_indoor storage_room storm_cellar street strip_mall strip_mine student_residence submarine_interior sun_deck
+sushi_bar swamp swimming_hole swimming_pool_indoor synagogue_indoor synagogue_outdoor taxistand taxiway tea_garden
+tearoom teashop television_room east_asia mesoamerican south_asia western tennis_court_indoor tennis_court_outdoor
+tent_outdoor terrace_farm indoor_round indoor_seats theater_outdoor thriftshop throne_room ticket_booth
+tobacco_shop_indoor toll_plaza tollbooth topiary_garden tower town_house toyshop track_outdoor trading_floor
+trailer_park train_interior train_station_outdoor station tree_farm tree_house trench trestle_bridge tundra rail_indoor
+rail_outdoor road_indoor road_outdoor turkish_bath ocean_deep ocean_shallow utility_room valley van_interior
+vegetable_garden velodrome_indoor velodrome_outdoor ventilation_shaft veranda vestry veterinarians_office videostore
+village vineyard volcano volleyball_court_indoor volleyball_court_outdoor voting_booth waiting_room walk_in_freezer
+warehouse_indoor warehouse_outdoor washhouse_indoor washhouse_outdoor watchtower water_mill water_park water_tower
+water_treatment_plant_indoor water_treatment_plant_outdoor block cascade cataract fan plunge watering_hole weighbridge
+wet_bar wharf wheat_field whispering_gallery widows_walk_interior windmill window_seat barrel_storage winery
+witness_stand woodland workroom workshop wrestling_ring_indoor wrestling_ring_outdoor yard youth_hostel zen_garden
+ziggurat zoo forklift hollow hutment pueblo vat perfume_shop steel_mill_outdoor orchestra_pit bridle_path lyceum
+one-way_street parade_ground pump_room recycling_plant_outdoor chuck_wagon
+"""
+_SCENE_CATEGORIES = _SCENE_CATEGORIES.strip().split()
+
+
+class SceneParse150(datasets.GeneratorBasedBuilder):
+    """MIT Scene Parsing Benchmark dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="scene_parsing", version=VERSION, description="The scene parsing variant."),
+        datasets.BuilderConfig(
+            name="instance_segmentation", version=VERSION, description="The instance segmentation variant."
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "scene_parsing"
+
+    def _info(self):
+        if self.config.name == "scene_parsing":
+            features = datasets.Features(
+                {
+                    "image": datasets.Image(),
+                    "annotation": datasets.Image(),
+                    "scene_category": datasets.ClassLabel(names=_SCENE_CATEGORIES),
+                }
+            )
+        else:
+            features = datasets.Features(
+                {
+                    "image": datasets.Image(),
+                    "annotation": datasets.Image(),
+                }
+            )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = _URLS[self.config.name]
+
+        if self.config.name == "scene_parsing":
+            data_dirs = dl_manager.download_and_extract(urls)
+            train_data = val_data = os.path.join(data_dirs["train/val"], "ADEChallengeData2016")
+            test_data = os.path.join(data_dirs["test"], "release_test")
+        else:
+            data_dirs = dl_manager.download(urls)
+            train_data = dl_manager.iter_archive(data_dirs["images"]), dl_manager.iter_archive(
+                data_dirs["annotations"]
+            )
+            val_data = dl_manager.iter_archive(data_dirs["images"]), dl_manager.iter_archive(data_dirs["annotations"])
+            test_data = dl_manager.iter_archive(data_dirs["test"])
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data": train_data,
+                    "split": "training",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"data": test_data, "split": "testing"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "data": val_data,
+                    "split": "validation",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data, split):
+        if self.config.name == "scene_parsing":
+            if split == "testing":
+                image_dir = os.path.join(data, split)
+                for idx, image_file in enumerate(os.listdir(image_dir)):
+                    yield idx, {
+                        "image": os.path.join(image_dir, image_file),
+                        "annotation": None,
+                        "scene_category": None,
+                    }
+            else:
+                image_id2cat = pd.read_csv(
+                    os.path.join(data, "sceneCategories.txt"), sep=" ", names=["image_id", "scene_category"]
+                )
+                image_id2cat = image_id2cat.set_index("image_id")
+                images_dir = os.path.join(data, "images", split)
+                annotations_dir = os.path.join(data, "annotations", split)
+                for idx, image_file in enumerate(os.listdir(images_dir)):
+                    image_id = image_file.split(".")[0]
+                    yield idx, {
+                        "image": os.path.join(images_dir, image_file),
+                        "annotation": os.path.join(annotations_dir, image_id + ".json"),
+                        "scene_category": image_id2cat.loc[image_id, "scene_category"],
+                    }
+        else:
+            if split == "testing":
+                for idx, (path, file) in enumerate(data):
+                    if path.endswith(".jpg"):
+                        yield idx, {
+                            "image": {"path": path, "bytes": file.read()},
+                            "annotation": None,
+                        }
+            else:
+                images, annotations = data
+                image_id2annot = {}
+                # loads the annotations for the split into RAM (less than 100 MB) to support streaming
+                for path_annot, file_annot in annotations:
+                    if split in path_annot and path_annot.endswith(".json"):
+                        image_id = os.path.basename(path_annot).split(".")[0]
+                        image_id2annot[image_id] = (path_annot, file_annot.read())
+                for idx, (path_img, file_img) in enumerate(images):
+                    if split in path_img and path_img.endswith(".jpg"):
+                        image_id = os.path.basename(path_img).split(".")[0]
+                        path_annot, bytes_annot = image_id2annot[image_id]
+                        yield idx, {
+                            "image": {"path": path_img, "bytes": file_img.read()},
+                            "annotation": {"path": path_annot, "bytes": bytes_annot},
                         }