from datasets.vg import vg import numpy as np # Set up voc_<year>_<split> for year in ['2007', '2012']: for split in ['train', 'val', 'trainval', 'test']: name = 'voc_{}_{}'.format(year, split) __sets[name] = (lambda split=split, year=year: pascal_voc(split, year)) for year in ['2007', '2012']: for split in [ 'train_s', 'train_t', 'train_all', 'test_s', 'test_t', 'test_all' ]: name = 'cityscape_{}_{}'.format(year, split) __sets[name] = (lambda split=split, year=year: cityscape(split, year)) # Set up coco_2014_<split> for year in ['2014']: for split in ['train', 'val', 'minival', 'valminusminival', 'trainval']: name = 'coco_{}_{}'.format(year, split) __sets[name] = (lambda split=split, year=year: coco(split, year)) # Set up coco_2014_cap_<split> for year in ['2014']: for split in ['train', 'val', 'capval', 'valminuscapval', 'trainval']: name = 'coco_{}_{}'.format(year, split) __sets[name] = (lambda split=split, year=year: coco(split, year)) # Set up coco_2015_<split> for year in ['2015']:
from datasets.pascal_voc import pascal_voc from datasets.pascal_voc_water import pascal_voc_water from datasets.pascal_voc_cyclewater import pascal_voc_cyclewater from datasets.pascal_voc_cycleclipart import pascal_voc_cycleclipart from datasets.sim10k import sim10k from datasets.water import water from datasets.clipart import clipart from datasets.sim10k_cycle import sim10k_cycle from datasets.cityscape import cityscape from datasets.cityscape_car import cityscape_car from datasets.foggy_cityscape import foggy_cityscape import numpy as np for split in ['train', 'trainval', 'val', 'test']: name = 'cityscape_{}'.format(split) __sets[name] = (lambda split=split: cityscape(split)) for split in ['train', 'trainval', 'val', 'test']: name = 'cityscape_car_{}'.format(split) __sets[name] = (lambda split=split: cityscape_car(split)) for split in ['train', 'trainval', 'test']: name = 'foggy_cityscape_{}'.format(split) __sets[name] = (lambda split=split: foggy_cityscape(split)) for split in ['train', 'val']: name = 'sim10k_{}'.format(split) __sets[name] = (lambda split=split: sim10k(split)) for split in ['train', 'val']: name = 'sim10k_cycle_{}'.format(split) __sets[name] = (lambda split=split: sim10k_cycle(split)) for year in ['2007', '2012']: for split in ['train', 'val', 'trainval', 'test']: name = 'voc_{}_{}'.format(year, split)
# Set up pl_watercolor_<year>_<split> for year in ['2007']: devkit_path = '/userhome/Datasets/pl_watercolor' for split in ['train', 'test', 'trainval']: name = 'pl_watercolor_voc_{}_{}'.format(year, split) __sets[name] = (lambda year=year, split=split, devkit_path=devkit_path: pl_watercolor(split, year, devkit_path=devkit_path)) # Set up cityscape_<year>_<split> for year in ['2007']: devkit_path = '/userhome/Datasets/cityscape' # devkit_path = '/userhome/Datasets/Cityscape_FroggyCityscape/cityscape' for split in ['test', 'trainval']: name = 'cityscape_{}_{}'.format(year, split) __sets[name] = (lambda year=year, split=split, devkit_path=devkit_path: cityscape(split, year, devkit_path=devkit_path)) # Set up foggy_cityscape_<year>_<split> for year in ['2007']: devkit_path = '/userhome/Datasets/Cityscape_FroggyCityscape/foggy-cityscape' for split in ['test', 'trainval']: name = 'foggy_cityscape_{}_{}'.format(year, split) __sets[name] = (lambda year=year, split=split, devkit_path=devkit_path: foggy_cityscape(split, year, devkit_path=devkit_path)) # Set up city2foggy_<year>_<split> for year in ['2007']: devkit_path = '/userhome/Datasets/city2foggy' for split in ['test', 'trainval']: name = 'city2foggy_{}_{}'.format(year, split) __sets[name] = (lambda year=year, split=split, devkit_path=devkit_path: city2foggy(split, year, devkit_path=devkit_path)) # Set up foggy2city_<year>_<split>
from datasets.clipart import clipart from datasets.comic import comic from datasets.amds import amds from datasets.sim10k_cycle import sim10k_cycle from datasets.cityscape import cityscape from datasets.cityscape_car import cityscape_car from datasets.foggy_cityscape import foggy_cityscape from datasets.kitti import kitti import numpy as np import os for split in ['train', 'trainval','val','test','detection_train']: for data_percentage in ['', '_1_00', '_1_01', '_1_02', '_10_samples', '_10_samples_2', '_10_samples_3']: name = 'cityscapes{}_{}'.format(data_percentage, split) __sets[name] = (lambda split=split, data_percentage=data_percentage : cityscape("cityscapes_" + split, devkit_path="datasets/voc_cityscapes{}".format(data_percentage))) for split in ['train', 'trainval','val','test']: name = 'kitti_{}'.format(split) __sets[name] = (lambda split=split : kitti("kitti_" + split, devkit_path="datasets/voc_kitti")) for split in ['train', 'trainval','val','test']: name = 'cityscape_car_{}'.format(split) __sets[name] = (lambda split=split : cityscape_car(split)) for split in ['train', 'trainval','test']: for data_percentage in ['', '_1_00', '_1_01', '_1_02', '_10_samples', '_10_samples_2', '_10_samples_3']: name = 'foggy_cityscapes{}_{}'.format(data_percentage, split) __sets[name] = (lambda split=split, data_percentage=data_percentage : foggy_cityscape("foggy_" + split, devkit_path="datasets/voc_cityscapes2foggy{}".format(data_percentage))) for split in ['train', 'trainval','test']: for data_percentage in ['', '_1_00', '_1_01', '_1_02', '_10_samples', '_10_samples_2', '_10_samples_3']: name = 'kitti{}_{}'.format(data_percentage, split) __sets[name] = (lambda split=split, data_percentage=data_percentage : kitti("kitti_" + split, devkit_path="datasets/voc_kitti{}".format(data_percentage))) for split in ['train','val']: