update

readme.md

@@ -8,7 +8,7 @@ python transfer_to_lut.py --model_path /wd/lut_reproduce/models/last_trained_net
 
 python train.py --model_path /wd/lut_reproduce/models/last_transfered_lut.pth --total_iter 2000
 
-python validate.py --val_datasets Set5,Set14,B100,Urban1[00,Manga109 --model_path /wd/lut_reproduce/models/last_trained_lut.pth
+python validate.py --val_datasets Set5,Set14,B100,Urban100,Manga109 --model_path /wd/lut_reproduce/models/last_trained_lut.pth
 
 python image_demo.py 
 ```

src/scripts/validate.py

@@ -49,18 +49,18 @@ class ValOptions():
 
         return args
 
-    def print_options(self, opt):
+    def __repr__(self):
+        config = self.parser.parse_args() 
         message = ''
         message += '----------------- Options ---------------\n'
-        for k, v in sorted(vars(opt).items()):
+        for k, v in sorted(vars(config).items()):
             comment = ''
             default = self.parser.get_default(k)
             if v != default:
                 comment = '\t[default: %s]' % str(default)
             message += '{:>25}: {:<30}{}\n'.format(str(k), str(v), comment)
         message += '----------------- End -------------------'
-        print(message)
-        print()
+        return message
 
 
 # TODO with unified save/load function any model file of net or lut can be tested with the same script.
@@ -69,7 +69,7 @@ if __name__ == "__main__":
     config_inst = ValOptions()
     config = config_inst.parse_args()
    
-    config.logger.info(config_inst.print_options(config))
+    config.logger.info(config_inst)
 
     model = LoadCheckpoint(config.model_path)
     model = model.cuda()