diff --git a/README.md b/README.md
index 69eccea3db856f0d8a55c541007652ce9d471f27..b1cc15d261a396ba8a8846375854283324a5f6a0 100644
--- a/README.md
+++ b/README.md
@@ -47,7 +47,7 @@ We adopt yolox as the detection method. We used stronger data augmentation and r
 
 ### Training 
 
-Download the pretrained model at [Onedrive](https://mailstsinghuaeducn-my.sharepoint.com/:f:/g/personal/liuxy21_mails_tsinghua_edu_cn/EkCTrRfHUZVEtD7eHwLkYSkBCTXlh9ekDteSzK6jM4oo-A?e=6TCh8y) (password: groupji) and put it in the folder `pretrained_models/yolox`. Then use the following command:
+Download the pretrained model at [Onedrive](https://mailstsinghuaeducn-my.sharepoint.com/:f:/g/personal/liuxy21_mails_tsinghua_edu_cn/EkCTrRfHUZVEtD7eHwLkYSkBCTXlh9ekDteSzK6jM4oo-A?e=m0aNCy) (password: groupji) and put it in the folder `pretrained_models/yolox`. Then use the following command:
 
 `./det/yolox/tools/train_yolox.sh <config_path> <gpu_ids> (other args)`
 
diff --git a/core/gdrn_modeling/engine/gdrn_evaluator.py b/core/gdrn_modeling/engine/gdrn_evaluator.py
index 0704ef041a8916c0c1cbe277cc49ae3c5be2e4ec..e1cb3186cdb028d93a373a805b32b7c4a35d7252 100644
--- a/core/gdrn_modeling/engine/gdrn_evaluator.py
+++ b/core/gdrn_modeling/engine/gdrn_evaluator.py
@@ -518,8 +518,6 @@ class GDRN_Evaluator(DatasetEvaluator):
                 net_cfg = cfg.MODEL.POSE_NET
                 crop_res = net_cfg.OUTPUT_RES
 
-
-
                 for _ in range(cfg.TEST.DEPTH_REFINE_ITER):
                     self.ren.clear()
                     self.ren.set_cam(K_crop)