Prepare dataset

Suppose you have downloaded the original dataset, we need to preprocess the data and save it as pickle file. Remember to set your path to the root of processed dataset in configs/*.yaml.

Preprocess

CASIA-B

Download URL: http://www.cbsr.ia.ac.cn/GaitDatasetB-silh.zip
- Original
CASIA-B 001 (subject) bg-01 (type) 000 (view) 001-bg-01-000-001.png (frame) 001-bg-01-000-002.png (frame) ...... ...... ...... ......
- Run python datasets/pretreatment.py --input_path CASIA-B --output_path CASIA-B-pkl
- Processed
CASIA-B-pkl 001 (subject) bg-01 (type) 000 (view) 000.pkl (contains all frames) ...... ...... ......
OUMVLP

Step1: Download URL: http://www.am.sanken.osaka-u.ac.jp/BiometricDB/GaitMVLP.html

Step2: Unzip the dataset, you will get a structure directory like:

python datasets/OUMVLP/extractor.py --input_path Path_of_OUMVLP-base --output_path Path_of_OUMVLP-raw --password Given_Password

• Original
  OUMVLP-raw Silhouette_000-00 (view-sequence) 00001 (subject) 0001.png (frame) 0002.png (frame) ...... 00002 0001.png (frame) 0002.png (frame) ...... ...... Silhouette_000-01 00001 0001.png (frame) 0002.png (frame) ...... 00002 0001.png (frame) 0002.png (frame) ...... ...... Silhouette_015-00 ...... Silhouette_015-01 ...... ......
  Step3 : To rearrange directory of OUMVLP dataset, turning to id-type-view structure, Run

python datasets/OUMVLP/rearrange_OUMVLP.py --input_path Path_of_OUMVLP-raw --output_path Path_of_OUMVLP-rearranged

Step4: Transforming images to pickle file, run

python datasets/pretreatment.py --input_path Path_of_OUMVLP-rearranged --output_path Path_of_OUMVLP-pkl

• Processed
  OUMVLP-pkl 00001 (subject) 00 (sequence) 000 (view) 000.pkl (contains all frames) 015 (view) 015.pkl (contains all frames) ... 01 (sequence) 000 (view) 000.pkl (contains all frames) 015 (view) 015.pkl (contains all frames) ...... 00002 (subject) ...... ......

GREW

Step1: Download the data

Step2: Unzip the dataset, you will get a structure directory like:

• Original
  ```
  GREW-raw
  ├── train
  ├── 00001
  ├── 4XPn5Z28
  ├── 00001.png
  ├── 00001_2d_pose.txt
  ├── 00001_3d_pose.txt
  ├── 4XPn5Z28_gei.png
  ├── test
  ├── gallery
  ├── 00001
  ├── 79XJefi8
  ├── 00001.png
  ├── 00001_2d_pose.txt
  ├── 00001_3d_pose.txt
  ├── 79XJefi8_gei.png
  ├── probe
  ├── 01DdvEHX
  ├── 00001.png
  ├── 00001_2d_pose.txt
  ├── 00001_3d_pose.txt
  ├── 01DdvEHX_gei.png
  ...
  ...

Step3 : To rearrange directory of GREW dataset, turning to id-type-view structure, Run

python datasets/GREW/rearrange_GREW.py --input_path Path_of_GREW-raw --output_path Path_of_GREW-rearranged

Step4: Transforming images to pickle file, run

python datasets/pretreatment.py --input_path Path_of_GREW-rearranged --output_path Path_of_GREW-pkl

• Processed
  GREW-pkl ├── 00001train (subject in training set) ├── 00 ├── 4XPn5Z28 ├── 4XPn5Z28.pkl ├──5TXe8svE ├── 5TXe8svE.pkl ...... ├── 00001 (subject in testing set) ├── 01 ├── 79XJefi8 ├── 79XJefi8.pkl ├── 02 ├── t16VLaQf ├── t16VLaQf.pkl ├── probe ├── etaGVnWf ├── etaGVnWf.pkl ├── eT1EXpgZ ├── eT1EXpgZ.pkl ... ...

Split dataset

You can use the partition file in dataset folder directly, or you can create yours. Remember to set your path to the partition file in configs/*.yaml.