diff --git a/testsingle.py b/testsingle.py
index a6f574f..38b3a52 100755
--- a/testsingle.py
+++ b/testsingle.py
@@ -13,12 +13,12 @@ import time
 #模型测试单张图片
 parser = argparse.ArgumentParser()
 parser.add_argument("--dataset", choices=["emptyJudge5"], default="emptyJudge5", help="Which dataset.")
-parser.add_argument("--img_size", default=320, type=int, help="Resolution size")
+parser.add_argument("--img_size", default=600, type=int, help="Resolution size")
 parser.add_argument('--split', type=str, default='overlap', help="Split method")  # non-overlap
 parser.add_argument('--slide_step', type=int, default=12, help="Slide step for overlap split")
 parser.add_argument('--smoothing_value', type=float, default=0.0, help="Label smoothing value\n")
-parser.add_argument("--pretrained_model", type=str, default="../module/ieemoo-ai-isempty/model/now/emptyjudge5_checkpoint.bin", help="load pretrained model")
-#parser.add_argument("--pretrained_model", type=str, default="output/ieemooempty_vit_checkpoint.pth", help="load pretrained model") #使用自定义VIT
+#parser.add_argument("--pretrained_model", type=str, default="../module/ieemoo-ai-isempty/model/now/emptyjudge5_checkpoint.bin", help="load pretrained model")
+parser.add_argument("--pretrained_model", type=str, default="output/ieemooempty_vit_checkpoint.pth", help="load pretrained model") #使用自定义VIT
 args = parser.parse_args()
 
 args.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -40,7 +40,7 @@ if args.pretrained_model is not None:
 model.to(args.device)
 model.eval()
 
-test_transform = transforms.Compose([transforms.Resize((320, 320), Image.BILINEAR),
+test_transform = transforms.Compose([transforms.Resize((600, 600), Image.BILINEAR),
                                      transforms.ToTensor(),
                                      transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])