--- a
+++ b/tools/data/ucf101/README.md
@@ -0,0 +1,127 @@
+# Preparing UCF-101
+
+## Introduction
+
+<!-- [DATASET] -->
+
+```BibTeX
+@article{Soomro2012UCF101AD,
+  title={UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild},
+  author={K. Soomro and A. Zamir and M. Shah},
+  journal={ArXiv},
+  year={2012},
+  volume={abs/1212.0402}
+}
+```
+
+For basic dataset information, you can refer to the dataset [website](https://www.crcv.ucf.edu/research/data-sets/ucf101/).
+Before we start, please make sure that the directory is located at `$MMACTION2/tools/data/ucf101/`.
+
+## Step 1. Prepare Annotations
+
+First of all, you can run the following script to prepare annotations.
+
+```shell
+bash download_annotations.sh
+```
+
+## Step 2. Prepare Videos
+
+Then, you can run the following script to prepare videos.
+
+```shell
+bash download_videos.sh
+```
+
+For better decoding speed, you can resize the original videos into smaller sized, densely encoded version by:
+
+```
+python ../resize_videos.py ../../../data/ucf101/videos/ ../../../data/ucf101/videos_256p_dense_cache --dense --level 2 --ext avi
+```
+
+## Step 3. 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 [denseflow](https://github.com/open-mmlab/denseflow).
+
+If you have plenty of SSD space, then we recommend extracting frames there for better I/O performance. The extracted frames (RGB + Flow) will take up about 100GB.
+
+You can run the following script to soft link SSD.
+
+```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
+```
+
+If you only want to play with RGB frames (since extracting optical flow can be time-consuming), consider running the following script to extract **RGB-only** frames using denseflow.
+
+```shell
+bash extract_rgb_frames.sh
+```
+
+If you didn't install denseflow, you can still extract RGB frames using OpenCV by the following script, but it will keep the original size of the images.
+
+```shell
+bash extract_rgb_frames_opencv.sh
+```
+
+If both are required, run the following script to extract frames using "tvl1" algorithm.
+
+```shell
+bash extract_frames.sh
+```
+
+## Step 4. Generate File List
+
+you can run the follow script to generate file list in the format of rawframes and videos.
+
+```shell
+bash generate_videos_filelist.sh
+bash generate_rawframes_filelist.sh
+```
+
+## Step 5. Check 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:
+
+```
+mmaction2
+├── 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).