sushi-bar-fresh-samples.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: hurry.filesize in /opt/conda/lib/python3.8/site-packages (0.9)\n",
      "Requirement already satisfied: setuptools in /opt/conda/lib/python3.8/site-packages (from hurry.filesize) (49.6.0.post20201009)\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "!{sys.executable} -m pip install hurry.filesize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "import proglog\n",
    "proglog.notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "from moviepy.editor import *\n",
    "\n",
    "srcclip = VideoFileClip(\"./sushi-bar-fresh-samples.mp4\", audio=False, target_resolution=(512,None))\n",
    "srcclip = srcclip.fx(vfx.crop, y1=srcclip.h - srcclip.w*9/16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "audio = AudioFileClip(\"sounds-like-an-earful.wav\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[37.604, 60.144, 68.038, 92.862, 96.941, 98.945, 104.932, 107.341, 118.868, 122.251, 124.98, 134.294, 140.768, 145.446, 171.927, 174.237, 189.078, 192.239, 201.358, 205.785, 208.988, 214.474, 218.162, 224.108, 231.765, 237.097, 244.698, 248.778, 255.595, 258.365, 266.983, 273.665, 277.383, 280.599, 285.36]\n"
     ]
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "from datetime import datetime\n",
    "import re\n",
    "log = Path(\"sushi-bar-fresh-samples.txt\").read_text()\n",
    "lines = log.splitlines()\n",
    "\n",
    "events = []\n",
    "\n",
    "for line in lines:\n",
    "    if re.search(r\"Loading [^/]+/[^/]+$\", line):\n",
    "        ts0 = datetime.strptime(line.split(\" \")[1], \"%H:%M:%S.%f\")\n",
    "    if re.search(r\"Snapping\", line):\n",
    "        ts = datetime.strptime(line.split(\" \")[1], \"%H:%M:%S.%f\") - ts0\n",
    "        events.append(ts.total_seconds())\n",
    "        \n",
    "print(events)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [],
   "source": [
    "event_offset = 2.5\n",
    "extract_duration = 1.5\n",
    "final_extract_duration = 5\n",
    "extracts = [srcclip.subclip(event_offset + t, event_offset + t + extract_duration) for t in events[:-1]]\n",
    "extracts.append(srcclip.subclip(event_offset + events[-1], event_offset + events[-1] + final_extract_duration))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "fade_duration=0.1\n",
    "fade_color=[0,0,0]\n",
    "\n",
    "def fade_concat(clips):\n",
    "    fades = []\n",
    "    start = 0\n",
    "    for i in range(0, len(clips)):\n",
    "        clip = clips[i]\n",
    "        if i < len(clips) - 1:\n",
    "            clip = clip.fx(vfx.fadeout, duration=fade_duration, final_color=fade_color)\n",
    "        if i > 0:\n",
    "            clip = clip.fx(vfx.fadein, duration=fade_duration, initial_color=fade_color)\n",
    "        clip = clip.with_start(start)\n",
    "        start = start + clip.duration\n",
    "        fades.append(clip)\n",
    "    return CompositeVideoClip(fades)\n",
    "\n",
    "concatenated = fade_concat(extracts).fx(vfx.fadein, duration=.5).fx(vfx.fadeout, duration=.5)\n",
    "\n",
    "audio_clipped = audio.with_duration(concatenated.duration).audio_fadein(1).audio_fadeout(1)\n",
    "\n",
    "outclip = concatenated.with_audio(audio_clipped)\n",
    "\n",
    "# outclip.ipython_display(autoplay=True, maxduration=120, width=1024)\n",
    "\n",
    "outclip.write_videofile(\"out.mp4\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4M\n"
     ]
    },
    {
     "data": {
      "text/html": [