|
|
@@ -45,7 +45,8 @@ def main():
|
|
|
|
|
|
args = parser.parse_args()
|
|
|
|
|
|
- p_interval = list(map(int, args.interval.split(',')))
|
|
|
+ # keep p_interval as it is
|
|
|
+ p_interval = args.interval
|
|
|
p_model_file = args.model
|
|
|
p_mode = args.mode
|
|
|
p_metric = args.metric
|
|
|
@@ -123,11 +124,9 @@ def main():
|
|
|
tmp_file_path = tmp_filename.replace('__model__', p_model_file.split('/')[-1].replace('.joblib', '_'))
|
|
|
block.save(tmp_file_path)
|
|
|
|
|
|
- python_cmd = "python predict_noisy_image_svd.py --image " + tmp_file_path + \
|
|
|
- " --interval '" + p_interval + \
|
|
|
- "' --model " + p_model_file + \
|
|
|
- " --mode " + p_mode + \
|
|
|
- " --metric " + p_metric
|
|
|
+ python_cmd = """python predict_noisy_image_svd.py --image {0} --interval '{1}' --model {2} --mode {3} --metric {4}""".format(tmp_file_path, p_interval, p_model_file, p_mode, p_metric)
|
|
|
+
|
|
|
+ print(python_cmd)
|
|
|
|
|
|
# specify use of custom file for min max normalization
|
|
|
if p_custom:
|
