diff --git a/README.md b/README.md
index 9b1c87e..209f5ec 100644
--- a/README.md
+++ b/README.md
@@ -15,11 +15,11 @@ Prerequisites:
 You can use the `Dockerfile` provided to build the environment then enter the environment using `nvidia-docker run --rm -it -v HOST_FOLDER:/share DOCKER_IMAGE bash`.
 
 To train the model, just run `python start_train.py`. Default configuration can be found at `config.yml`. You need to prepare video dataset you plan to train/evaluate on. You may get the benchmark dataset videos from respective authors. For each dataset, put the training videos into `VIDEO_ROOT_PATH/DATASET_NAME/training_videos` and testing videos into `VIDEO_ROOT_PATH/DATASET_NAME/testing_videos`. Example structure of training videos for `avenue` dataset:
-`VIDEO_ROOT_PATH/avenue/training_videos`
-- `01.avi`
-- `02.avi`
-- ...
-- `16.avi`
+- `VIDEO_ROOT_PATH/avenue/training_videos`
+  - `01.avi`
+  - `02.avi`
+  - ...
+  - `16.avi`
 
 Once you have trained the model, you may now run `python start_test.py` after setting the parameters at the beginning of the file.