Add files via upload

predict_GoPro_test_results.py

@@ -18,7 +18,7 @@ def get_args():
 if __name__ == '__main__':
     args = get_args()
     with open('config/config_Stripformer_gopro.yaml') as cfg:
-        config = yaml.load(cfg)
+        config = yaml.safe_load(cfg)
     blur_path = './datasets/GoPro/test/blur/'
     out_path = './out/Stripformer_GoPro_results'
     if not os.path.isdir(out_path):

predict_HIDE_results.py

@@ -18,7 +18,7 @@ def get_args():
 if __name__ == '__main__':
     args = get_args()
     with open('config/config_Stripformer_gopro.yaml') as cfg:
-        config = yaml.load(cfg)
+        config = yaml.safe_load(cfg)
     blur_path = './datasets/HIDE/blur/'
     out_path = './out/Stripformer_HIDE_results'
     if not os.path.isdir(out_path):

predict_RealBlur_J_test_results.py

@@ -19,7 +19,7 @@ def get_args():
 if __name__ == '__main__':
     args = get_args()
     with open('config/config_Stripformer_gopro.yaml') as cfg:
-        config = yaml.load(cfg)
+        config = yaml.safe_load(cfg)
     blur_path = './datasets/Realblur_J/test/blur/'
     out_path = './out/Stripformer_realblur_J_results'
     if not os.path.isdir(out_path):

predict_RealBlur_R_test_results.py

@@ -19,7 +19,7 @@ def get_args():
 if __name__ == '__main__':
     args = get_args()
     with open('config/config_Stripformer_gopro.yaml') as cfg:
-        config = yaml.load(cfg)
+        config = yaml.safe_load(cfg)
     blur_path = './datasets/Realblur_R/test/blur/'
     out_path = './out/Stripformer_realblur_R_results'
     model = get_generator(config['model'])

train_Stripformer_gopro.py

@@ -148,7 +148,7 @@ class Trainer:
 
 if __name__ == '__main__':
     with open('config/config_Stripformer_gopro.yaml', 'r') as f:
-        config = yaml.load(f)
+        config = yaml.safe_load(f)
     # setup
     torch.backends.cudnn.enabled = True
     torch.backends.cudnn.benchmark = True

train_Stripformer_pretrained.py

@@ -142,7 +142,7 @@ class Trainer:
 
 if __name__ == '__main__':
     with open('config/config_Stripformer_pretrained.yaml', 'r') as f:
-        config = yaml.load(f)
+        config = yaml.safe_load(f)
     # setup
     torch.backends.cudnn.enabled = True
     torch.backends.cudnn.benchmark = True