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from data.pix2pix_dataset import Pix2pixDataset
from data.image_folder import make_dataset
class ADE20KDataset(Pix2pixDataset):
@staticmethod
def modify_commandline_options(parser, is_train):
parser = Pix2pixDataset.modify_commandline_options(parser, is_train)
parser.set_defaults(preprocess_mode='resize_and_crop')
if is_train:
parser.set_defaults(load_size=286)
else:
parser.set_defaults(load_size=256)
parser.set_defaults(crop_size=256)
parser.set_defaults(display_winsize=256)
parser.set_defaults(label_nc=150)
parser.set_defaults(contain_dontcare_label=True)
parser.set_defaults(cache_filelist_read=False)
parser.set_defaults(cache_filelist_write=False)
parser.set_defaults(no_instance=True)
return parser
def get_paths(self, opt):
root = opt.croot
phase = 'val' if opt.phase == 'test' else 'train'
all_images = make_dataset(root, recursive=True, read_cache=False, write_cache=False)
image_paths = []
label_paths = []
for p in all_images:
if '_%s_' % phase not in p:
continue
if p.endswith('.jpg'):
image_paths.append(p)
elif p.endswith('.png'):
label_paths.append(p)
instance_paths = [] # don't use instance map for ade20k
return label_paths, image_paths, instance_paths
# In ADE20k, 'unknown' label is of value 0.
# Change the 'unknown' label to the last label to match other datasets.
def postprocess(self, input_dict):
label = input_dict['label']
label = label - 1
label[label == -1] = self.opt.label_nc
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