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
        ......
    ......

Step3-1 : To rearrange directory of OUMVLP dataset(for silhouette), turning to id-type-view structure, Run

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

Step3-2 : To rearrange directory of OUMVLP dataset(for pose), turning to id-type-view structure, Run

python datasets/OUMVLP/rearrange_OUMVLP_pose.py --input_path Path_of_OUMVLP-pose --output_path Path_of_OUMVLP-pose-rearranged

Step4-1: Transforming images to pickle file, run

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

Step4-2: Transforming pose txts to pickle file, run

Important

Before extracting pose pkls, you need to possess the pose selection index files (Why). Here are two ways to get it:
Approach 1: Directly download it:

Open Download Link, choose AlphaPose or OpenPose version

Find a suitable location to unzip it, like <somewhere>/OUMVLP/Pose/match_idx.

Move the zip file into the match_idx dir and unzip it there.

You will finally get the index root: <somewhere>/OUMVLP/Pose/match_idx/AlphaPose
(Here we take AlphaPose version as an example, this path is what we call Path_of_OUMVLP-pose-index below)
Approach 2: Run the following command to generate it by yourself (rearranged silhouette dataset is needed):
python datasets/OUMVLP/pose_index_extractor.py \
-p Path_of_OUMVLP-pose-rearranged \
-s Path_of_OUMVLP-silu-rearranged \
-o Path_of_OUMVLP-pose-index

python datasets/pretreatment.py \
--input_path Path_of_OUMVLP-pose-rearranged \
--output_path Path_of_OUMVLP-pose-pkl \
--pose \
--dataset OUMVLP \
--oumvlp_index_dir Path_of_OUMVLP-pose-index

gernerate the 17 Number of Pose Points Format from 18 Number of Pose Points

python datasets/OUMVLP/rearrange_OUMVLP_pose.py --input_path Path_of_OUMVLP-pose18 --output_path Path_of_OUMVLP-pose17

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)
        ......
    ......