|
@@ -220,6 +220,9 @@ def main():
|
|
|
help="list of specific param for each metric choice (See README.md for further information in 3D mode)",
|
|
|
default='100, 200 :: 50, 25',
|
|
|
required=True)
|
|
|
+ parser.add_argument('--size', type=str,
|
|
|
+ help="Size of input images",
|
|
|
+ default="100, 100")
|
|
|
parser.add_argument('--scenes', type=str, help='List of scenes to use for training data')
|
|
|
parser.add_argument('--nb_zones', type=int, help='Number of zones to use for training data set', choices=list(range(1, 17)))
|
|
|
parser.add_argument('--renderer', type=str, help='Renderer choice in order to limit scenes used', choices=cfg.renderer_choices, default='all')
|
|
@@ -231,6 +234,7 @@ def main():
|
|
|
p_features = list(map(str.strip, args.features.split(',')))
|
|
|
p_params = list(map(str.strip, args.params.split('::')))
|
|
|
p_scenes = args.scenes.split(',')
|
|
|
+ p_size = args.size # not necessary to split here
|
|
|
p_nb_zones = args.nb_zones
|
|
|
p_renderer = args.renderer
|
|
|
p_random = args.random
|
|
@@ -243,7 +247,7 @@ def main():
|
|
|
if feature not in features_choices:
|
|
|
raise ValueError("Unknown metric, please select a correct metric : ", features_choices)
|
|
|
|
|
|
- transformations.append(Transformation(feature, p_params[id]))
|
|
|
+ transformations.append(Transformation(feature, p_params[id], p_size))
|
|
|
|
|
|
if transformations[0].getName() == 'static':
|
|
|
raise ValueError("The first transformation in list cannot be static")
|