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| from .base_options import BaseOptions |
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|
| 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=50, help="how many test images to run") |
| 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.parser.add_argument( |
| "--start_epoch", |
| type=int, |
| default=-1, |
| help="write the start_epoch of iter.txt into this parameter", |
| ) |
|
|
| self.parser.add_argument("--test_dataset", type=str, default="Real_RGB_old.bigfile") |
| self.parser.add_argument( |
| "--no_degradation", |
| action="store_true", |
| help="when train the mapping, enable this parameter --> no degradation will be added into clean image", |
| ) |
| self.parser.add_argument( |
| "--no_load_VAE", |
| action="store_true", |
| help="when train the mapping, enable this parameter --> random initialize the encoder an decoder", |
| ) |
| self.parser.add_argument( |
| "--use_v2_degradation", |
| action="store_true", |
| help="enable this parameter --> 4 kinds of degradations will be used to synthesize corruption", |
| ) |
| self.parser.add_argument("--use_vae_which_epoch", type=str, default="latest") |
| self.isTrain = False |
|
|
| self.parser.add_argument("--generate_pair", action="store_true") |
|
|
| self.parser.add_argument("--multi_scale_test", type=float, default=0.5) |
| self.parser.add_argument("--multi_scale_threshold", type=float, default=0.5) |
| self.parser.add_argument( |
| "--mask_need_scale", |
| action="store_true", |
| help="enable this param meas that the pixel range of mask is 0-255", |
| ) |
| self.parser.add_argument("--scale_num", type=int, default=1) |
|
|
| self.parser.add_argument( |
| "--save_feature_url", type=str, default="", help="While extracting the features, where to put" |
| ) |
|
|
| self.parser.add_argument( |
| "--test_input", type=str, default="", help="A directory or a root of bigfile" |
| ) |
| self.parser.add_argument("--test_mask", type=str, default="", help="A directory or a root of bigfile") |
| self.parser.add_argument("--test_gt", type=str, default="", help="A directory or a root of bigfile") |
|
|
| self.parser.add_argument( |
| "--scale_input", action="store_true", help="While testing, choose to scale the input firstly" |
| ) |
|
|
| self.parser.add_argument( |
| "--save_feature_name", type=str, default="features.json", help="The name of saved features" |
| ) |
| self.parser.add_argument( |
| "--test_rgb_old_wo_scratch", action="store_true", help="Same setting with origin test" |
| ) |
|
|
| self.parser.add_argument("--test_mode", type=str, default="Crop", help="Scale|Full|Crop") |
| self.parser.add_argument("--Quality_restore", action="store_true", help="For RGB images") |
| self.parser.add_argument( |
| "--Scratch_and_Quality_restore", action="store_true", help="For scratched images" |
| ) |
| self.parser.add_argument("--HR", action='store_true',help='Large input size with scratches') |
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