GoodWin/Deep-Multi-scale

1from .base_options import BaseOptions2 3 4class TestOptions(BaseOptions):5    def initialize(self, parser):6        parser = BaseOptions.initialize(self, parser)7        # parser.add_argument('--dataroot', type=str, default='/home/Data/AllDataImages/2018_FaceFH', help='path to images (should have subfolders trainA, trainB, valA, valB, etc)')8        parser.add_argument('--dataroot', type=str, default='', help='path to images (should have subfolders trainA, trainB, valA, valB, etc)')9        parser.add_argument('--phase', type=str, default='', help='train, val, test, etc')10        parser.add_argument('--aspect_ratio', type=float, default=1.0, help='aspect ratio of result images')11        parser.add_argument('--which_epoch', type=str, default='latest', help='which epoch to load? set to latest to use latest cached model')12        parser.set_defaults(model='test')13 14        parser.add_argument('--test_path', type=str, default='./TestData/TestWhole', help='test images path')15        parser.add_argument('--results_dir', type=str, default='./Results/TestWholeResults', help='saves results here.')16        parser.add_argument('--upscale_factor', type=int, default=4, help='upscale factor for the whole input image (not for face)')17 18        19        self.isTrain = False20        return parser21