Update GDPOSR/inferences/test.py

GDPOSR/inferences/test.py

@@ -34,10 +34,10 @@ def get_validation_prompt(args, image, model, device='cuda'):
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
-    parser.add_argument('--input_image', type=str, default="", help='path to the input image')
+    parser.add_argument('--input_path', type=str, default="", help='path to the input image')
     parser.add_argument('--model_name', type=str, default='realsr', help='name of the pretrained model to be used')
     parser.add_argument('--pretrained_path', type=str, default='', help='path to a model state dict to be used')
-    parser.add_argument('--output_dir', type=str, default='', help='the directory to save the output')
+    parser.add_argument('--output_path', type=str, default='', help='the directory to save the output')
     parser.add_argument('--seed', type=int, default=42, help='Random seed to be used')
     parser.add_argument("--process_size", type=int, default=512)
     parser.add_argument("--upscale", type=int, default=4)
@@ -54,10 +54,10 @@ if __name__ == "__main__":
     model = GDPOSRTest(args)
     model.set_eval()
 
-    if os.path.isdir(args.input_image):
-        image_names = sorted(glob.glob(f'{args.input_image}/*.png'))
+    if os.path.isdir(args.input_path):
+        image_names = sorted(glob.glob(f'{args.input_path}/*.png'))
     else:
-        image_names = [args.input_image]
+        image_names = [args.input_path]
 
     print("=== use ram ===")
     model_vlm = ram(pretrained='./ckp/ram_swin_large_14m.pth',
@@ -68,7 +68,7 @@ if __name__ == "__main__":
     model_vlm.to("cuda")
 
     # make the output dir
-    os.makedirs(args.output_dir, exist_ok=True)
+    os.makedirs(args.output_path, exist_ok=True)
     print(f'There are {len(image_names)} images.')
     for image_name in image_names:
         
@@ -104,4 +104,4 @@ if __name__ == "__main__":
             if resize_flag:
                 output_pil.resize((int(args.upscale*ori_width), int(args.upscale*ori_height)))
 
-        output_pil.save(os.path.join(args.output_dir, bname))
+        output_pil.save(os.path.join(args.output_path, bname))