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| from .base_options import BaseOptions | |
| class TestOptions(BaseOptions): | |
| def initialize(self): | |
| BaseOptions.initialize(self) | |
| self.parser.add_argument( | |
| '--ntest', type=int, default=float("inf"), help='# of test examples.') | |
| self.parser.add_argument( | |
| '--results_dir', type=str, default='./results/', help='saves results here.') | |
| self.parser.add_argument( | |
| '--aspect_ratio', type=float, default=1.0, help='aspect ratio of result images') | |
| self.parser.add_argument( | |
| '--phase', type=str, default='test', help='train, val, test, etc') | |
| self.parser.add_argument('--which_epoch', type=str, default='latest', | |
| help='which epoch to load? set to latest to use latest cached model') | |
| self.parser.add_argument( | |
| '--how_many', type=int, default=1000, help='how many test images to run') | |
| self.parser.add_argument('--serial_batches', action='store_false', | |
| help='if true, takes images in order to make batches, otherwise takes them randomly') | |
| self.parser.add_argument('--cluster_path', type=str, default='features_clustered_010.npy', | |
| help='the path for clustered results of encoded features') | |
| self.parser.add_argument('--use_encoded_image', action='store_true', | |
| help='if specified, encode the real image to get the feature map') | |
| self.parser.add_argument( | |
| "--export_onnx", type=str, help="export ONNX model to a given file") | |
| self.parser.add_argument("--engine", type=str, | |
| help="run serialized TRT engine") | |
| self.parser.add_argument( | |
| "--onnx", type=str, help="run ONNX model via TRT") | |
| self.isTrain = False | |