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']:
