chore: remove skvideo directory and transition to imageio

Author: Dammy Desktop

PupilProcessing/__pycache__/pupilpipeline.cpython-310.pyc

@@ -1,33 +1,19 @@
-import logging
-import math
-import os.path
-
 import joblib
 import pandas as pd
 
 from .psychophysicsUtils import *
 from . import utils
 from xdetectioncore.behaviour import load_aggregate_td_df, add_datetimecol
-from datetime import datetime, time, timedelta,timezone
-from matplotlib import pyplot as plt
+from datetime import datetime, timedelta,timezone
 import numpy as np
-from scipy import signal
-import time
 from copy import deepcopy as copy
-import glob
 import pathlib
 from pathlib import Path
-import yaml
 from loguru import logger
-from rich.logging import RichHandler
 from pyinspect import install_traceback
-import psutil
-import argparse
 import multiprocessing
-import platform
 from tqdm import tqdm
 import sys
-import pytz
 
 
 # script for building trial data and pupil data dict
@@ -54,18 +40,6 @@ def remove_missed_ttls(ts: np.ndarray) -> np.ndarray:
     return ts[good_idx]
 
 
-def has_handle(fpath):
-    for proc in psutil.process_iter():
-        try:
-            for item in proc.open_files():
-                if fpath == item.path:
-                    return True
-        except Exception:
-            pass
-
-    return False
-
-
 def get_dlc_est_path(recdir, filt_flag, non_plabs_str,name):
     dlc_estimates_files = []
     if filt_flag:

PupilProcessing/pupilpipeline.py

@@ -1,2 +1,2 @@
 from . inference_pupil_sense import Inference, get_center_and_radius
-from . import skvideo
+from . extract_pupil_pupil_sense import main

PupilSense/__init__.py

@@ -4,7 +4,7 @@
 import numpy as np
 
 import pandas as pd
-from . import skvideo
+import imageio.v3 as iio
 import time
 import signal  # <-- added for signal handling
 import sys     # <-- for sys.exit
@@ -43,7 +43,12 @@ def main(eye_video_paths,invert_gray_im, **kwargs):
         # load video using skvideo.io.vread
         num_frames_to_load = kwargs.get('num_frames',0) 
 
-        eye_video = skvideo.io.vread(str(eye_video_path), num_frames=num_frames_to_load, outputdict={'-pix_fmt': 'gray'}) 
+        # eye_video = skvideo.io.vread(str(eye_video_path), num_frames=num_frames_to_load, outputdict={'-pix_fmt': 'gray'}) 
+        eye_video = iio.imread(str(eye_video_path), 
+                               index=slice(0, num_frames_to_load) if num_frames_to_load > 0 else None,
+                               plugin="pyav", # Or "ffmpeg"
+                               format="gray"
+                               )
         load_end = time.time()
         print(f'load time: {round((load_end-load_start)/60,2)} mins')
         # eye_video = eye_video.dtype(np.uint8)