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# --------------------------------------------------------
# InternImage
# Copyright (c) 2022 OpenGVLab
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
from mmseg.datasets.builder import DATASETS
from mmseg.datasets.custom import CustomDataset
@DATASETS.register_module()
class MapillaryDataset(CustomDataset):
"""Mapillary dataset.
"""
CLASSES = ('Bird', 'Ground Animal', 'Curb', 'Fence', 'Guard Rail', 'Barrier',
'Wall', 'Bike Lane', 'Crosswalk - Plain', 'Curb Cut', 'Parking', 'Pedestrian Area',
'Rail Track', 'Road', 'Service Lane', 'Sidewalk', 'Bridge', 'Building', 'Tunnel',
'Person', 'Bicyclist', 'Motorcyclist', 'Other Rider', 'Lane Marking - Crosswalk',
'Lane Marking - General', 'Mountain', 'Sand', 'Sky', 'Snow', 'Terrain', 'Vegetation',
'Water', 'Banner', 'Bench', 'Bike Rack', 'Billboard', 'Catch Basin', 'CCTV Camera',
'Fire Hydrant', 'Junction Box', 'Mailbox', 'Manhole', 'Phone Booth', 'Pothole',
'Street Light', 'Pole', 'Traffic Sign Frame', 'Utility Pole', 'Traffic Light',
'Traffic Sign (Back)', 'Traffic Sign (Front)', 'Trash Can', 'Bicycle', 'Boat',
'Bus', 'Car', 'Caravan', 'Motorcycle', 'On Rails', 'Other Vehicle', 'Trailer',
'Truck', 'Wheeled Slow', 'Car Mount', 'Ego Vehicle', 'Unlabeled')
PALETTE = [[165, 42, 42], [0, 192, 0], [196, 196, 196], [190, 153, 153],
[180, 165, 180], [90, 120, 150], [102, 102, 156], [128, 64, 255],
[140, 140, 200], [170, 170, 170], [250, 170, 160], [96, 96, 96],
[230, 150, 140], [128, 64, 128], [110, 110, 110], [244, 35, 232],
[150, 100, 100], [70, 70, 70], [150, 120, 90], [220, 20, 60],
[255, 0, 0], [255, 0, 100], [255, 0, 200], [200, 128, 128],
[255, 255, 255], [64, 170, 64], [230, 160, 50], [70, 130, 180],
[190, 255, 255], [152, 251, 152], [107, 142, 35], [0, 170, 30],
[255, 255, 128], [250, 0, 30], [100, 140, 180], [220, 220, 220],
[220, 128, 128], [222, 40, 40], [100, 170, 30], [40, 40, 40],
[33, 33, 33], [100, 128, 160], [142, 0, 0], [70, 100, 150],
[210, 170, 100], [153, 153, 153], [128, 128, 128], [0, 0, 80],
[250, 170, 30], [192, 192, 192], [220, 220, 0], [140, 140, 20],
[119, 11, 32], [150, 0, 255], [0, 60, 100], [0, 0, 142], [0, 0, 90],
[0, 0, 230], [0, 80, 100], [128, 64, 64], [0, 0, 110], [0, 0, 70],
[0, 0, 192], [32, 32, 32], [120, 10, 10], [0, 0, 0]]
def __init__(self, **kwargs):
super(MapillaryDataset, self).__init__(
img_suffix='.jpg',
seg_map_suffix='.png',
reduce_zero_label=False,
**kwargs)