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+++ b/tools/data/mmit/README.md
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+# Preparing Multi-Moments in Time
+
+## Introduction
+
+<!-- [DATASET] -->
+
+```BibTeX
+@misc{monfort2019multimoments,
+    title={Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding},
+    author={Mathew Monfort and Kandan Ramakrishnan and Alex Andonian and Barry A McNamara and Alex Lascelles, Bowen Pan, Quanfu Fan, Dan Gutfreund, Rogerio Feris, Aude Oliva},
+    year={2019},
+    eprint={1911.00232},
+    archivePrefix={arXiv},
+    primaryClass={cs.CV}
+}
+```
+
+For basic dataset information, you can refer to the dataset [website](http://moments.csail.mit.edu).
+Before we start, please make sure that the directory is located at `$MMACTION2/tools/data/mmit/`.
+
+## Step 1. Prepare Annotations and Videos
+
+First of all, you have to visit the official [website](http://moments.csail.mit.edu/), fill in an application form for downloading the dataset. Then you will get the download link. You can use `bash preprocess_data.sh` to prepare annotations and videos. However, the download command is missing in that script. Remember to download the dataset to the proper place follow the comment in this script.
+
+For better decoding speed, you can resize the original videos into smaller sized, densely encoded version by:
+
+```
+python ../resize_videos.py ../../../data/mmit/videos/ ../../../data/mmit/videos_256p_dense_cache --dense --level 2
+```
+
+## Step 2. 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).
+
+First, 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/mmit_extracted/
+ln -s /mnt/SSD/mmit_extracted/ ../../../data/mmit/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 3. Generate File List
+
+you can run the follow script to generate file list in the format of rawframes or videos.
+
+```shell
+bash generate_rawframes_filelist.sh
+bash generate_videos_filelist.sh
+```
+
+## Step 4. Check Directory Structure
+
+After the whole data process for Multi-Moments in Time preparation,
+you will get the rawframes (RGB + Flow), videos and annotation files for Multi-Moments in Time.
+
+In the context of the whole project (for Multi-Moments in Time only), the folder structure will look like:
+
+```
+mmaction2/
+└── data
+    └── mmit
+        ├── annotations
+        │   ├── moments_categories.txt
+        │   ├── trainingSet.txt
+        │   └── validationSet.txt
+        ├── mmit_train_rawframes.txt
+        ├── mmit_train_videos.txt
+        ├── mmit_val_rawframes.txt
+        ├── mmit_val_videos.txt
+        ├── rawframes
+        │   ├── 0-3-6-2-9-1-2-6-14603629126_5
+        │   │   ├── flow_x_00001.jpg
+        │   │   ├── flow_x_00002.jpg
+        │   │   ├── ...
+        │   │   ├── flow_y_00001.jpg
+        │   │   ├── flow_y_00002.jpg
+        │   │   ├── ...
+        │   │   ├── img_00001.jpg
+        │   │   └── img_00002.jpg
+        │   │   ├── ...
+        │   └── yt-zxQfALnTdfc_56
+        │   │   ├── ...
+        │   └── ...
+
+        └── videos
+            └── adult+female+singing
+                ├── 0-3-6-2-9-1-2-6-14603629126_5.mp4
+                └── yt-zxQfALnTdfc_56.mp4
+            └── ...
+```
+
+For training and evaluating on Multi-Moments in Time, please refer to [getting_started.md](/docs/getting_started.md).