Collab_Dataset/batch_scripts/tracking.py

import re
from pathlib import Path
import pandas as pd
import videobatch

# for extraction of ROI names from files
ROI_PATTERN = re.compile(r"_([a-zA-Z]+)\.png")

# base spec, used in videobatch
base_spec = {
    "command": "pixylation",
    "mode":    "CM",
    "colors":  dict(Magenta=[260,360], Green=[90,225]),
    "sources": ["*.mp4"]
}

# the root repository dir
rootdir  = Path().resolve().parent

# dataset dirs
rawdir   = rootdir / "datasets" / "raw"
trkdir   = rootdir / "datasets" / "tracking"

# read info from SESSIONS
sessions = pd.read_csv(str(rootdir / "SESSIONS.csv"))

# iterate over sessions
for rowidx in range(sessions.shape[0]):
    session = sessions.iloc[rowidx]
    sname   = f"session{session.date}-{session.index:03d}"

    # source video directory
    srcdir    = rawdir / session.subject / sname / "video"

    # read ROI info
    roidir    = trkdir / session.subject / sname / "ROI" # may not be in the repository
    ROIs      = {}
    for child in roidir.iterdir():
        is_ROIfile = ROI_PATTERN.search(child.name)
        if not is_ROIfile:
            continue
        else:
            ROIname = is_ROIfile.group(1)
            ROIs[ROIname] = str(child)

    # output directories
    resultdir = trkdir / session.subject / sname / "tracked"
    maskdir   = trkdir / session.subject / sname / "mask"  # not in the repository

    # configure specs
    spec = base_spec.copy()
    spec['sourcedir'] = str(srcdir)
    spec['Rois']      = ROIs
    spec['resultdir'] = str(resultdir)
    spec['maskdir']   = str(maskdir)

    # run videobatch for this session
    videobatch.run(spec)