Breakthrough

"""
Parallel chunked scene detection experiment.
Each thread opens the video independently, seeks to its chunk, and runs detection.
Chunks are spaced every 30s with a small overlap so cuts near boundaries aren't missed.

> time python parallel.py 
Video: 82.6s @ 24000/1001fps -> 3 chunks, 4 workers
  chunk 60s-     end  ->  5 cuts  (541 frames @ 411.5 fps)
  chunk 0s-   32.0s  ->  5 cuts  (767 frames @ 440.0 fps)
  chunk 30s-   62.0s  ->  11 cuts  (767 frames @ 444.9 fps)

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// Add --remote-debugging-port=9222 to launch args, run game
// Go to  http://localhost:9222 and select the main game window with Firefox/Chrome
var connection = indexedDB.open('c3-localstorage-n3ijmdgu0mm', 2)

connection.onsuccess = (e) => {
  var db = e.target.result;
  var txn = db.transaction('keyvaluepairs', 'readwrite')
  var o = txn.objectStore('keyvaluepairs')
  console.info('original config:')
  console.info(o.get('kinduoFrostSteam'));

Breakthrough

import threading
import time
import cv2
import numpy as np
import queue


class EndOfVideo:
    pass

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import json

from scenedetect import VideoManager
from scenedetect import SceneManager
from scenedetect.detectors import ContentDetector
from scenedetect.scene_manager import save_images

def get_scenes_json(video_path, threshold=30.0):
    # Create our video & scene managers, then add the detector.
    video_manager = VideoManager([video_path])

Breakthrough

$> sudo strace -p `pidof "ntfsresize"`  -e trace=write 2>&1 | grep 'write(1'

[...]

write(1, " 87.38 percent completed\r", 25) = 25
write(1, " 87.38 percent completed\r", 25) = 25
write(1, " 87.92 percent completed\r", 25) = 25
write(1, " 87.92 percent completed\r", 25) = 25

[...]