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# Preparing Jester
## Introduction
<!-- [DATASET] -->
```BibTeX
@InProceedings{Materzynska_2019_ICCV,
author = {Materzynska, Joanna and Berger, Guillaume and Bax, Ingo and Memisevic, Roland},
title = {The Jester Dataset: A Large-Scale Video Dataset of Human Gestures},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2019}
}
```
For basic dataset information, you can refer to the dataset [website](https://developer.qualcomm.com/software/ai-datasets/jester).
Before we start, please make sure that the directory is located at `$MMACTION2/tools/data/jester/`.
## Step 1. Prepare Annotations
First of all, you have to sign in and download annotations to `$MMACTION2/data/jester/annotations` on the official [website](https://developer.qualcomm.com/software/ai-datasets/jester).
## Step 2. Prepare RGB Frames
Since the [jester website](https://developer.qualcomm.com/software/ai-datasets/jester) doesn't provide the original video data and only extracted RGB frames are available, you have to directly download RGB frames from [jester website](https://developer.qualcomm.com/software/ai-datasets/jester).
You can download all RGB frame parts on [jester website](https://developer.qualcomm.com/software/ai-datasets/jester) to `$MMACTION2/data/jester/` and use the following command to extract.
```shell
cd $MMACTION2/data/jester/
cat 20bn-jester-v1-?? | tar zx
cd $MMACTION2/tools/data/jester/
```
For users who only want to use RGB frames, you can skip to step 5 to generate file lists in the format of rawframes. Since the prefix of official JPGs is "%05d.jpg" (e.g., "00001.jpg"),
we add `"filename_tmpl='{:05}.jpg'"` to the dict of `data.train`, `data.val` and `data.test` in the config files related with jester like this:
```
data = dict(
videos_per_gpu=16,
workers_per_gpu=2,
train=dict(
type=dataset_type,
ann_file=ann_file_train,
data_prefix=data_root,
filename_tmpl='{:05}.jpg',
pipeline=train_pipeline),
val=dict(
type=dataset_type,
ann_file=ann_file_val,
data_prefix=data_root_val,
filename_tmpl='{:05}.jpg',
pipeline=val_pipeline),
test=dict(
type=dataset_type,
ann_file=ann_file_test,
data_prefix=data_root_val,
filename_tmpl='{:05}.jpg',
pipeline=test_pipeline))
```
## Step 3. Extract Flow
This part is **optional** if you only want to use RGB frames.
Before extracting, please refer to [install.md](/docs/en/get_started/installation.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.
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/jester_extracted/
ln -s /mnt/SSD/jester_extracted/ ../../../data/jester/rawframes
```
Then, you can run the following script to extract optical flow based on RGB frames.
```shell
cd $MMACTION2/tools/data/jester/
bash extract_flow.sh
```
## Step 4. Encode Videos
This part is **optional** if you only want to use RGB frames.
You can run the following script to encode videos.
```shell
cd $MMACTION2/tools/data/jester/
bash encode_videos.sh
```
## Step 5. Generate File List
You can run the follow script to generate file list in the format of rawframes and videos.
```shell
cd $MMACTION2/tools/data/jester/
bash generate_{rawframes, videos}_filelist.sh
```
## Step 5. Check Directory Structure
After the whole data process for Jester preparation,
you will get the rawframes (RGB + Flow), and annotation files for Jester.
In the context of the whole project (for Jester only), the folder structure will look like:
```
mmaction2
β”œβ”€β”€ mmaction
β”œβ”€β”€ tools
β”œβ”€β”€ configs
β”œβ”€β”€ data
β”‚ β”œβ”€β”€ jester
β”‚ β”‚ β”œβ”€β”€ jester_{train,val}_list_rawframes.txt
β”‚ β”‚ β”œβ”€β”€ jester_{train,val}_list_videos.txt
β”‚ β”‚ β”œβ”€β”€ annotations
β”‚ | β”œβ”€β”€ videos
β”‚ | | β”œβ”€β”€ 1.mp4
β”‚ | | β”œβ”€β”€ 2.mp4
β”‚ | | β”œβ”€β”€...
β”‚ | β”œβ”€β”€ rawframes
β”‚ | | β”œβ”€β”€ 1
β”‚ | | | β”œβ”€β”€ 00001.jpg
β”‚ | | | β”œβ”€β”€ 00002.jpg
β”‚ | | | β”œβ”€β”€ ...
β”‚ | | | β”œβ”€β”€ flow_x_00001.jpg
β”‚ | | | β”œβ”€β”€ flow_x_00002.jpg
β”‚ | | | β”œβ”€β”€ ...
β”‚ | | | β”œβ”€β”€ flow_y_00001.jpg
β”‚ | | | β”œβ”€β”€ flow_y_00002.jpg
β”‚ | | | β”œβ”€β”€ ...
β”‚ | | β”œβ”€β”€ 2
β”‚ | | β”œβ”€β”€ ...
```
For training and evaluating on Jester, please refer to [Training and Test Tutorial](/docs/en/user_guides/train_test.md).