diff --git a/PaddleCV/PaddleDetection/docs/QUICK_STARTED.md b/PaddleCV/PaddleDetection/docs/QUICK_STARTED.md
index c6649f71f7b41c2fda00141e20c16dffc1f93e40..18b8602328075a2734dc139c16215e95a6025a3d 100644
--- a/PaddleCV/PaddleDetection/docs/QUICK_STARTED.md
+++ b/PaddleCV/PaddleDetection/docs/QUICK_STARTED.md
@@ -26,7 +26,7 @@ Training:
 python -u tools/train.py -c configs/yolov3_mobilenet_v1_fruit.yml \
                         --use_tb=True \
                         --tb_log_dir=tb_fruit_dir/scalar \
-                        --eval \
+                        --eval
 ```
 
 Use `yolov3_mobilenet_v1` to fine-tune the model from COCO dataset. Meanwhile, loss and mAP can be observed on tensorboard.  
diff --git a/PaddleCV/PaddleDetection/docs/QUICK_STARTED_cn.md b/PaddleCV/PaddleDetection/docs/QUICK_STARTED_cn.md
index 8c02ffb798250a0fa29db02ab7e4b38f04e4daac..c11f041ba4405ebbf6c60365bbe937df55e6374d 100644
--- a/PaddleCV/PaddleDetection/docs/QUICK_STARTED_cn.md
+++ b/PaddleCV/PaddleDetection/docs/QUICK_STARTED_cn.md
@@ -26,7 +26,7 @@ export CUDA_VISIBLE_DEVICES=0
 python -u tools/train.py -c configs/yolov3_mobilenet_v1_fruit.yml \
                         --use_tb=True \
                         --tb_log_dir=tb_fruit_dir/scalar \
-                        --eval \
+                        --eval
 ```
 
 训练使用`yolov3_mobilenet_v1`基于COCO数据集训练好的模型进行finetune。训练期间可以通过tensorboard实时观察loss和精度值，启动命令如下：
diff --git a/PaddleCV/PaddleDetection/ppdet/utils/download.py b/PaddleCV/PaddleDetection/ppdet/utils/download.py
index 73f909e966f267ba551e5149294c24315e9facb4..772e19044c320bc0fb7ba5e75216951915074cf5 100644
--- a/PaddleCV/PaddleDetection/ppdet/utils/download.py
+++ b/PaddleCV/PaddleDetection/ppdet/utils/download.py
@@ -74,6 +74,7 @@ DATASETS = {
     'fruit': ([(
         'https://dataset.bj.bcebos.com/PaddleDetection_demo/fruit-detection.tar',
         'ee4a1bf2e321b75b0850cc6e063f79d7', ), ], ["fruit-detection"]),
+    'objects365': (),
 }
 
 DOWNLOAD_RETRY_LIMIT = 3
@@ -104,6 +105,11 @@ def get_dataset_path(path, annotation, image_dir):
         if os.path.split(path.strip().lower())[-1] == name:
             logger.info("Parse dataset_dir {} as dataset "
                         "{}".format(path, name))
+            if name == 'objects365':
+                raise NotImplementedError(
+                    "Dataset {} is not valid for download automatically."
+                    "Please apply and download the dataset from."
+                    "https://www.objects365.org/download.html")
             data_dir = osp.join(DATASET_HOME, name)
 
             # For voc, only check dir VOCdevkit/VOC2012, VOCdevkit/VOC2007