data/ade20k_dataset.py

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