diff --git a/.gitignore b/.gitignore
index 73ba032e2a..2bf0b12969 100644
--- a/.gitignore
+++ b/.gitignore
@@ -106,7 +106,7 @@ venv.bak/
 
 # custom
 mmaction/version.py
-data
+/data
 .vscode
 .idea
 *.pkl
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 740359421d..4b375d2044 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -10,7 +10,7 @@ repos:
   - repo: https://github.com/timothycrosley/isort
     rev: 4.3.21
     hooks:
-        - id: isort
+      - id: isort
   - repo: https://github.com/pre-commit/mirrors-yapf
     rev: v0.29.0
     hooks:
diff --git a/tools/data/ucf101/preparing_ucf101.md b/tools/data/ucf101/preparing_ucf101.md
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+# Preparing UCF-101
+
+For basic dataset information, you can refer to the dataset [website](https://www.crcv.ucf.edu/data/UCF101.php).
+Before we start, please make sure that the directory is located at `$MMACTION/tools/data/ucf101/`.
+
+## Step 1. Prepare Annotations
+
+First of all, you can run the following script to prepare annotations.
+
+```shell
+bash download_annotations.sh
+```
+
+## Prepare Videos
+
+Then, you can run the following script to prepare videos.
+
+```shell
+bash download_videos.sh
+```
+
+## Extract RGB and Flow
+
+This part is **optional** if you only want to use the video loader.
+
+Before extracting, please refer to [install.md](/docs/install.md) for installing [dense_flow](https://github.com/yjxiong/dense_flow).
+
+If you have plenty of SSD, then we recommend extracting frames there for better I/O performance. The extracted frames (RGB + Flow) will take up about 100GB.
+
+If you didn't install dense_flow in the installation or only want to play with RGB frames (since extracting optical flow can be time-comsuming), consider running the following script to extract **RGB-only** frames.
+
+```shell
+bash extract_rgb_frames.sh
+```
+
+If both are required, run the following script to extract frames.
+
+```shell
+bash extract_frames.sh
+```
+
+Then, You can run the following script to soft link the extracted frames.
+
+```shell
+# execute these two line (Assume the SSD is mounted at "/mnt/SSD/")
+mkdir /mnt/SSD/ucf101_extracted/
+ln -s /mnt/SSD/ucf101_extracted/ ../../../data/ucf101/rawframes
+```
+
+## Generate File List
+
+you can run the follow script to generate file list in the format of rawframes and videos.
+
+```shell
+bash generate_filelist.sh
+```
+
+## Directory Structure
+
+After the whole data process for UCF-101 preparation,
+you will get the rawframes (RGB + Flow), videos and annotation files for UCF-101.
+
+In the context of the whole project (for UCF-101 only), the folder structure will look like:
+
+```
+mmaction
+├── mmaction
+├── tools
+├── configs
+├── data
+│   ├── ucf101
+│   │   ├── ucf101_{train,val}_split_{1,2,3}_rawframes.txt
+│   │   ├── ucf101_{train,val}_split_{1,2,3}_videos.txt
+│   │   ├── annotations
+│   │   ├── videos
+│   │   │   ├── ApplyEyeMakeup
+│   │   │   │   ├── v_ApplyEyeMakeup_g01_c01.avi
+
+│   │   │   ├── YoYo
+│   │   │   │   ├── v_YoYo_g25_c05.avi
+│   │   ├── rawframes
+│   │   │   ├── ApplyEyeMakeup
+│   │   │   │   ├── v_ApplyEyeMakeup_g01_c01
+│   │   │   │   │   ├── img_00001.jpg
+│   │   │   │   │   ├── img_00002.jpg
+│   │   │   │   │   ├── ...
+│   │   │   │   │   ├── flow_x_00001.jpg
+│   │   │   │   │   ├── flow_x_00002.jpg
+│   │   │   │   │   ├── ...
+│   │   │   │   │   ├── flow_y_00001.jpg
+│   │   │   │   │   ├── flow_y_00002.jpg
+│   │   │   ├── ...
+│   │   │   ├── YoYo
+│   │   │   │   ├── v_YoYo_g01_c01
+│   │   │   │   ├── ...
+│   │   │   │   ├── v_YoYo_g25_c05
+
+```
+
+For training and evaluating on UCF-101, please refer to [getting_started.md](/docs/getting_started.md).