sandbox.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from os import path\n",
    "import glob\n",
    "import re\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-audio-1705678317122.webm',\n",
       " 'testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.webm',\n",
       " 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-audio-1705678317128.webm',\n",
       " 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.webm',\n",
       " 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-audio-1705678317130.webm',\n",
       " 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.webm',\n",
       " 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-audio-1705678317125.webm',\n",
       " 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.webm']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "folder = 'test1'\n",
    "files = glob.glob(f'testVideos/{folder}/*')\n",
    "files.sort()\n",
    "files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'89a8a334-06cb-4127-8888-636b5ac97692': {'participant_id': '89a8a334-06cb-4127-8888-636b5ac97692',\n",
       "  'group_start': 1705678316133,\n",
       "  'dirname': 'testVideos/test1',\n",
       "  'audio_track_start': '0.956000',\n",
       "  'audio': 'testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-audio-1705678317122.webm',\n",
       "  'audio_start': 1705678317122,\n",
       "  'audio_offset': 989,\n",
       "  'video_track_start': '2.288000',\n",
       "  'video_resolution': '1280x720',\n",
       "  'video': 'testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.webm',\n",
       "  'video_start': 1705678317124,\n",
       "  'video_offset': 991},\n",
       " 'aa30144f-2005-495b-aa6b-dc790dbe12f1': {'participant_id': 'aa30144f-2005-495b-aa6b-dc790dbe12f1',\n",
       "  'group_start': 1705678316133,\n",
       "  'dirname': 'testVideos/test1',\n",
       "  'audio_track_start': '1.039000',\n",
       "  'audio': 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-audio-1705678317128.webm',\n",
       "  'audio_start': 1705678317128,\n",
       "  'audio_offset': 995,\n",
       "  'video_track_start': '2.285000',\n",
       "  'video_resolution': '1280x720',\n",
       "  'video': 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.webm',\n",
       "  'video_start': 1705678317131,\n",
       "  'video_offset': 998},\n",
       " 'c821f277-846c-4bbf-9dde-0bb3ff8cce79': {'participant_id': 'c821f277-846c-4bbf-9dde-0bb3ff8cce79',\n",
       "  'group_start': 1705678316133,\n",
       "  'dirname': 'testVideos/test1',\n",
       "  'audio_track_start': '0.968000',\n",
       "  'audio': 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-audio-1705678317130.webm',\n",
       "  'audio_start': 1705678317130,\n",
       "  'audio_offset': 997,\n",
       "  'video_track_start': '1.731000',\n",
       "  'video_resolution': '1280x720',\n",
       "  'video': 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.webm',\n",
       "  'video_start': 1705678317121,\n",
       "  'video_offset': 988},\n",
       " 'ce3e2c98-a999-4202-8139-2bdfe5d1cec2': {'participant_id': 'ce3e2c98-a999-4202-8139-2bdfe5d1cec2',\n",
       "  'group_start': 1705678316133,\n",
       "  'dirname': 'testVideos/test1',\n",
       "  'audio_track_start': '0.963000',\n",
       "  'audio': 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-audio-1705678317125.webm',\n",
       "  'audio_start': 1705678317125,\n",
       "  'audio_offset': 992,\n",
       "  'video_track_start': '2.336000',\n",
       "  'video_resolution': '1280x720',\n",
       "  'video': 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.webm',\n",
       "  'video_start': 1705678317126,\n",
       "  'video_offset': 993}}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group_data = {}\n",
    "for filepath in files:\n",
    "    if \".webm\" not in filepath:\n",
    "        continue\n",
    "    basename = path.basename(filepath)\n",
    "    participant_id = \"-\".join(basename.split(\"-\")[1:-3])\n",
    "    track_type = basename.split(\"-\")[-2]\n",
    "    track_start = int(basename.split(\"-\")[-1].split(\".\")[0])\n",
    "    group_start = int(basename.split(\"-\")[0])\n",
    "    \n",
    "    if participant_id not in group_data:\n",
    "        group_data[participant_id] = {\n",
    "        \"participant_id\": participant_id,\n",
    "        \"group_start\": int(basename.split(\"-\")[0]),\n",
    "        \"dirname\": path.dirname(filepath),\n",
    "    }\n",
    "\n",
    "    probe = ! ffprobe $filepath \n",
    "    \n",
    "    # get start offset\n",
    "    line = [line  for line in probe if \"start: \" in line][0]\n",
    "    start = re.search(r'start: (\\d+\\.\\d+)', line).group(1)\n",
    "    group_data[participant_id][track_type+\"_track_start\"] = start\n",
    "\n",
    "    if track_type == \"video\":    \n",
    "        # get resolution\n",
    "        line = [line  for line in probe if \"Stream \" in line][0]\n",
    "        resolution = re.search(r'\\d+x\\d+', line).group(0)\n",
    "        group_data[participant_id][track_type+\"_resolution\"] = resolution\n",
    "\n",
    "\n",
    "    group_data[participant_id][track_type] = filepath\n",
    "    group_data[participant_id][track_type+\"_start\"] = track_start\n",
    "    group_data[participant_id][track_type+\"_offset\"] = track_start - group_start\n",
    "\n",
    "\n",
    "group_data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FFMPEG notes:\n",
    "\n",
    "\n",
    "## Commands\n",
    "- commands generally list inputs with `-i filename` then have filters, then have and output.\n",
    "- Flags for inputs (or outputs) go in front of the input (output) they apply to, and if you have multiple inputs you can apply the flag to then individually\n",
    "\n",
    "## Filters\n",
    "- ffmpeg filters are made of chains of different filters. Different chains are separated by a semicolon, filters within a chain by a comma\n",
    "- filter consists of selectors (e.g.`[0:a][1:a]` etc.) then filter commands, then outputs []\n",
    "\n",
    "### Audio\n",
    "\n",
    "#### To split a stereo to mono:\n",
    "```\n",
    "ffmpeg -i stereo.wav -filter_complex \"[0:a]channelsplit=channel_layout=stereo:channels=FR[right]\" -map \"[right]\" front_right.wav\n",
    "```\n",
    "\n",
    "#### To merge 6 mono tracks to one multichannel output\n",
    "```\n",
    "ffmpeg -i front_left.wav -i front_right.wav -i front_center.wav -i lfe.wav -i back_left.wav -i back_right.wav \\\n",
    "-filter_complex \"[0:a][1:a][2:a][3:a][4:a][5:a]join=inputs=6:channel_layout=5.1[a]\" -map \"[a]\" output.wav\n",
    "```\n",
    "\n",
    "#### combine all audio tracks into one audio track\n",
    "- use the amerge filter to take audio streams from different files and add them as separate streams to the output\n",
    "```\n",
    "[0:a][1:a]amerge=inputs=2,\n",
    "```\n",
    "the output of this can be fed to a single stereo stream:\n",
    "```\n",
    "pan=mono|c0<c0+c1+c2+c3|\n",
    "```\n",
    "\n",
    "### Video\n",
    "\n",
    "#### Stack videos:\n",
    "https://ffmpeg.org/ffmpeg-filters.html#xstack-1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Notes on our videos\n",
    "\n",
    "The input videos have variable frame rate, it seems, so we re-encode using the output flag `-r 30` to get 30FPS\n",
    "\n",
    "The input videos also seem to have variable resolutions (urg...) need to work out how to deal with this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ffmpeg -itsoffset \"0.956000\" -i testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-audio-1705678317122.webm -itsoffset \"0.963000\" -i testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-audio-1705678317125.webm -itsoffset \"2.288000\" -i testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.webm -itsoffset \"2.336000\" -i testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.webm -filter_complex \"[0:a][1:a]amerge=inputs=2,pan=mono|c0<c0+c1+c2+c3|[a];[2:v]scale=1280:720[v0];[3:v]scale=1280:720[v1];[v0][v1]hstack=inputs=2[v]\" -map \"[a]\" -map \"[v]\" -r 30 testVideos/test1.webm'"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# format inputs\n",
    "audio_inputs = [f'-itsoffset \"{ group_data[i][\"audio_track_start\"] }\" -i {group_data[i][\"audio\"]}' for i in group_data]\n",
    "video_inputs = [f'-itsoffset \"{ group_data[i][\"video_track_start\"] }\" -i {group_data[i][\"video\"]}' for i in group_data]\n",
    "\n",
    "# format audio chain\n",
    "audioChain = \"\".join([f'[{i}:a]' for i in range(len(audio_inputs))]) + \\\n",
    "    f'amerge=inputs={len(audio_inputs)},' + \\\n",
    "    f'pan=mono|c0<{ \"+\".join([f\"c{j}\" for j in range(len(audio_inputs)*2)])}|[a]'\n",
    "\n",
    "# format video chain\n",
    "videoChain = \"\".join([f'[{i+len(audio_inputs)}:v]scale=1280:720[v{i}];' for i in range(len(video_inputs))]) + \\\n",
    "    f'{\"\".join([f\"[v{i}]\" for i in range(len(video_inputs))])}hstack=inputs={len(video_inputs)}[v]'\n",
    "\n",
    "cmd = f'ffmpeg {\" \".join(audio_inputs)} {\" \".join(video_inputs)} -filter_complex \"{audioChain};{videoChain}\" -map \"[a]\" -map \"[v]\" -r 30 testVideos/{folder}.webm'\n",
    "print(cmd)\n",
    "print()\n",
    "! $cmd -y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This kinda works, but the video gets stuck a lot. It doesn't handle stuck source videos well at all. If one of the source videos is missing frames, then the composed video will be stuck while all the source videos are stuck.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "measure_files = files + [f'testVideos/{folder}.webm']\n",
    "for i, filepath in enumerate(measure_files):\n",
    "    output = ! ffprobe -show_frames $filepath\n",
    "    frames = \"\\n\".join(output).split(\"[FRAME]\")[2:] \n",
    "    times = [float(re.search(r'pts_time=(\\d+\\.\\d+)', frame).group(1)) for frame in frames]\n",
    "    plt.subplot(len(measure_files), 1, i+1)\n",
    "    plt.hist(times, bins=range(int(min(times)), int(max(times)), 1), color= \"blue\" if \"audio\" in filepath else \"red\")\n",
    "    plt.title(filepath)\n",
    "\n",
    "plt.ylabel(\"frames per second\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reframe each video independently\n",
    "The problem was that when one webm file has problems, all the rest get stalled out too. a workaround is to resample all the videos at a constant frame rate prior to stitching them together. This is annoying, but kinda works?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.webm testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.mp4\n",
      "ffmpeg version 6.0 Copyright (c) 2000-2023 the FFmpeg developers\n",
      "  built with Apple clang version 15.0.0 (clang-1500.0.40.1)\n",
      "  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.0_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon\n",
      "  libavutil      58.  2.100 / 58.  2.100\n",
      "  libavcodec     60.  3.100 / 60.  3.100\n",
      "  libavformat    60.  3.100 / 60.  3.100\n",
      "  libavdevice    60.  1.100 / 60.  1.100\n",
      "  libavfilter     9.  3.100 /  9.  3.100\n",
      "  libswscale      7.  1.100 /  7.  1.100\n",
      "  libswresample   4. 10.100 /  4. 10.100\n",
      "  libpostproc    57.  1.100 / 57.  1.100\n",
      "Input #0, matroska,webm, from 'testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:59.283914Z\n",
      "  Duration: N/A, start: 2.288000, bitrate: N/A\n",
      "  Stream #0:0(eng): Video: vp8, yuv420p(progressive), 1280x720, SAR 1:1 DAR 16:9, 1k tbr, 1k tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (vp8 (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0musing SAR=1/1\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0musing cpu capabilities: ARMv8 NEON\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mprofile High, level 3.1, 4:2:0, 8-bit\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0m264 - core 164 r3108 31e19f9 - H.264/MPEG-4 AVC codec - Copyleft 2003-2023 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=15 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=24 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf60.3.100\n",
      "  Stream #0:0(eng): Video: h264 (avc1 / 0x31637661), yuv420p(tv, bt470bg/unknown/unknown, progressive), 1280x720 [SAR 1:1 DAR 16:9], q=2-31, 24 fps, 12288 tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 4112 fps=298 q=-1.0 Lsize=   21338kB time=00:02:51.20 bitrate=1021.0kbits/s dup=0 drop=1018 speed=12.4x    \n",
      "video:21289kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.227498%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mframe I:17    Avg QP:16.13  size: 73423\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mframe P:1084  Avg QP:19.89  size: 11889\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mframe B:3011  Avg QP:26.21  size:  2545\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mconsecutive B-frames:  0.7%  2.1%  9.0% 88.2%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mmb I  I16..4: 14.6% 60.4% 25.0%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mmb P  I16..4:  2.0%  3.9%  0.5%  P16..4: 32.7%  9.9%  4.0%  0.0%  0.0%    skip:47.0%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mmb B  I16..4:  0.2%  0.4%  0.0%  B16..8: 29.0%  1.4%  0.1%  direct: 0.7%  skip:68.1%  L0:49.9% L1:47.6% BI: 2.5%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0m8x8 transform intra:60.8% inter:72.9%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mcoded y,uvDC,uvAC intra: 43.3% 59.3% 31.9% inter: 8.0% 6.9% 0.3%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mi16 v,h,dc,p: 33% 22% 28% 16%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mi8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 31% 15% 31%  3%  3%  4%  3%  5%  4%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 48% 16% 15%  3%  4%  5%  3%  4%  2%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mi8c dc,h,v,p: 47% 21% 26%  6%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mWeighted P-Frames: Y:0.0% UV:0.0%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mref P L0: 59.3% 17.6% 18.3%  4.8%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mref B L0: 85.6% 12.8%  1.6%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mref B L1: 93.4%  6.6%\n",
      "\u001b[1;36m[libx264 @ 0x12e708c20] \u001b[0mkb/s:1017.88\n",
      "testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.webm testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.mp4\n",
      "ffmpeg version 6.0 Copyright (c) 2000-2023 the FFmpeg developers\n",
      "  built with Apple clang version 15.0.0 (clang-1500.0.40.1)\n",
      "  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.0_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon\n",
      "  libavutil      58.  2.100 / 58.  2.100\n",
      "  libavcodec     60.  3.100 / 60.  3.100\n",
      "  libavformat    60.  3.100 / 60.  3.100\n",
      "  libavdevice    60.  1.100 / 60.  1.100\n",
      "  libavfilter     9.  3.100 /  9.  3.100\n",
      "  libswscale      7.  1.100 /  7.  1.100\n",
      "  libswresample   4. 10.100 /  4. 10.100\n",
      "  libpostproc    57.  1.100 / 57.  1.100\n",
      "Input #0, matroska,webm, from 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:59.285432Z\n",
      "  Duration: N/A, start: 2.285000, bitrate: N/A\n",
      "  Stream #0:0(eng): Video: vp8, yuv420p(progressive), 1280x720, SAR 1:1 DAR 16:9, 1k tbr, 1k tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (vp8 (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0musing SAR=1/1\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0musing cpu capabilities: ARMv8 NEON\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mprofile High, level 3.1, 4:2:0, 8-bit\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0m264 - core 164 r3108 31e19f9 - H.264/MPEG-4 AVC codec - Copyleft 2003-2023 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=15 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=24 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf60.3.100\n",
      "  Stream #0:0(eng): Video: h264 (avc1 / 0x31637661), yuv420p(tv, bt470bg/unknown/unknown, progressive), 1280x720 [SAR 1:1 DAR 16:9], q=2-31, 24 fps, 12288 tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "\u001b[1;35m[vost#0:0/libx264 @ 0x13990a440] \u001b[0m\u001b[0;33mMore than 1000 frames duplicatedup=982 drop=460 speed=14.1x    \n",
      "frame= 4113 fps=355 q=-1.0 Lsize=   12012kB time=00:02:51.25 bitrate= 574.6kbits/s dup=1527 drop=532 speed=14.8x       \n",
      "video:11962kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.410128%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mframe I:19    Avg QP:15.51  size: 45350\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mframe P:1044  Avg QP:17.77  size:  6685\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mframe B:3050  Avg QP:23.41  size:  1445\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mconsecutive B-frames:  0.6%  0.8%  2.1% 96.5%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mmb I  I16..4: 19.3% 60.7% 20.0%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mmb P  I16..4:  1.7%  3.3%  0.5%  P16..4: 21.3%  6.1%  2.5%  0.0%  0.0%    skip:64.7%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mmb B  I16..4:  0.2%  0.3%  0.0%  B16..8: 17.4%  0.8%  0.1%  direct: 0.4%  skip:80.7%  L0:47.4% L1:50.7% BI: 1.9%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0m8x8 transform intra:59.5% inter:81.7%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mcoded y,uvDC,uvAC intra: 47.4% 43.8% 17.9% inter: 4.4% 3.5% 0.1%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mi16 v,h,dc,p: 33% 20% 24% 23%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mi8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 32% 18% 26%  3%  4%  5%  4%  4%  4%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 45% 20% 19%  2%  3%  3%  3%  3%  1%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mi8c dc,h,v,p: 58% 19% 19%  4%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mWeighted P-Frames: Y:2.6% UV:0.2%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mref P L0: 60.1% 12.1% 21.1%  6.5%  0.2%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mref B L0: 82.8% 14.5%  2.7%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mref B L1: 92.4%  7.6%\n",
      "\u001b[1;36m[libx264 @ 0x13990a710] \u001b[0mkb/s:571.79\n",
      "testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.webm testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.mp4\n",
      "ffmpeg version 6.0 Copyright (c) 2000-2023 the FFmpeg developers\n",
      "  built with Apple clang version 15.0.0 (clang-1500.0.40.1)\n",
      "  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.0_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon\n",
      "  libavutil      58.  2.100 / 58.  2.100\n",
      "  libavcodec     60.  3.100 / 60.  3.100\n",
      "  libavformat    60.  3.100 / 60.  3.100\n",
      "  libavdevice    60.  1.100 / 60.  1.100\n",
      "  libavfilter     9.  3.100 /  9.  3.100\n",
      "  libswscale      7.  1.100 /  7.  1.100\n",
      "  libswresample   4. 10.100 /  4. 10.100\n",
      "  libpostproc    57.  1.100 / 57.  1.100\n",
      "Input #0, matroska,webm, from 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:58.736506Z\n",
      "  Duration: N/A, start: 1.731000, bitrate: N/A\n",
      "  Stream #0:0(eng): Video: vp8, yuv420p(progressive), 1280x720, SAR 1:1 DAR 16:9, 30 tbr, 1k tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (vp8 (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0musing SAR=1/1\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0musing cpu capabilities: ARMv8 NEON\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mprofile High, level 3.1, 4:2:0, 8-bit\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0m264 - core 164 r3108 31e19f9 - H.264/MPEG-4 AVC codec - Copyleft 2003-2023 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=15 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=24 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf60.3.100\n",
      "  Stream #0:0(eng): Video: h264 (avc1 / 0x31637661), yuv420p(tv, bt470bg/unknown/unknown, progressive), 1280x720 [SAR 1:1 DAR 16:9], q=2-31, 24 fps, 12288 tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "\u001b[1;35m[vost#0:0/libx264 @ 0x14b70b3f0] \u001b[0m\u001b[0;33mMore than 1000 frames duplicatedup=538 drop=604 speed=15.4x    \n",
      "frame= 4124 fps=414 q=-1.0 Lsize=    9375kB time=00:02:51.70 bitrate= 447.3kbits/s dup=1421 drop=632 speed=17.2x       \n",
      "video:9326kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.527005%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mframe I:18    Avg QP:15.03  size: 57677\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mframe P:1043  Avg QP:17.08  size:  5267\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mframe B:3063  Avg QP:23.36  size:   985\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mconsecutive B-frames:  0.7%  0.3%  1.7% 97.3%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mmb I  I16..4: 18.9% 63.8% 17.4%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mmb P  I16..4:  1.2%  2.4%  0.3%  P16..4: 19.2%  4.3%  2.4%  0.0%  0.0%    skip:70.1%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mmb B  I16..4:  0.2%  0.2%  0.0%  B16..8: 14.3%  0.4%  0.0%  direct: 0.4%  skip:84.6%  L0:43.3% L1:55.8% BI: 0.9%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0m8x8 transform intra:61.1% inter:83.0%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mcoded y,uvDC,uvAC intra: 44.4% 52.3% 27.5% inter: 3.4% 4.0% 0.3%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mi16 v,h,dc,p: 29% 22% 27% 22%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mi8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 29% 18% 30%  3%  4%  5%  4%  4%  3%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 40% 23% 19%  2%  3%  3%  4%  2%  2%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mi8c dc,h,v,p: 54% 21% 22%  3%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mWeighted P-Frames: Y:0.2% UV:0.1%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mref P L0: 61.2% 12.5% 20.8%  5.5%  0.0%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mref B L0: 85.5% 12.5%  2.0%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mref B L1: 92.5%  7.5%\n",
      "\u001b[1;36m[libx264 @ 0x14b70b6c0] \u001b[0mkb/s:444.57\n",
      "testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.webm testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.mp4\n",
      "ffmpeg version 6.0 Copyright (c) 2000-2023 the FFmpeg developers\n",
      "  built with Apple clang version 15.0.0 (clang-1500.0.40.1)\n",
      "  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.0_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon\n",
      "  libavutil      58.  2.100 / 58.  2.100\n",
      "  libavcodec     60.  3.100 / 60.  3.100\n",
      "  libavformat    60.  3.100 / 60.  3.100\n",
      "  libavdevice    60.  1.100 / 60.  1.100\n",
      "  libavfilter     9.  3.100 /  9.  3.100\n",
      "  libswscale      7.  1.100 /  7.  1.100\n",
      "  libswresample   4. 10.100 /  4. 10.100\n",
      "  libpostproc    57.  1.100 / 57.  1.100\n",
      "Input #0, matroska,webm, from 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:59.349411Z\n",
      "  Duration: N/A, start: 2.336000, bitrate: N/A\n",
      "  Stream #0:0(eng): Video: vp8, yuv420p(progressive), 1280x720, SAR 1:1 DAR 16:9, 1k tbr, 1k tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (vp8 (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0musing SAR=1/1\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0musing cpu capabilities: ARMv8 NEON\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mprofile High, level 3.1, 4:2:0, 8-bit\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0m264 - core 164 r3108 31e19f9 - H.264/MPEG-4 AVC codec - Copyleft 2003-2023 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=15 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=24 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf60.3.100\n",
      "  Stream #0:0(eng): Video: h264 (avc1 / 0x31637661), yuv420p(tv, bt470bg/unknown/unknown, progressive), 1280x720 [SAR 1:1 DAR 16:9], q=2-31, 24 fps, 12288 tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "\u001b[1;35m[vost#0:0/libx264 @ 0x13d70be60] \u001b[0m\u001b[0;33mMore than 1000 frames duplicatedup=641 drop=481 speed=13.2x    \n",
      "frame= 4113 fps=333 q=-1.0 Lsize=   11929kB time=00:02:51.25 bitrate= 570.6kbits/s dup=1283 drop=524 speed=13.8x       \n",
      "video:11880kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.413091%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mframe I:18    Avg QP:15.09  size: 49630\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mframe P:1041  Avg QP:18.08  size:  6973\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mframe B:3054  Avg QP:23.12  size:  1314\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mconsecutive B-frames:  0.7%  0.5%  1.6% 97.3%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mmb I  I16..4: 21.4% 63.3% 15.3%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mmb P  I16..4:  2.0%  3.0%  0.3%  P16..4: 28.4%  7.2%  3.5%  0.0%  0.0%    skip:55.6%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mmb B  I16..4:  0.2%  0.2%  0.0%  B16..8: 20.3%  0.6%  0.0%  direct: 0.4%  skip:78.3%  L0:48.9% L1:50.0% BI: 1.1%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0m8x8 transform intra:57.4% inter:87.2%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mcoded y,uvDC,uvAC intra: 43.3% 48.9% 20.5% inter: 5.0% 5.0% 0.1%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mi16 v,h,dc,p: 31% 16% 25% 27%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mi8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 31% 17% 31%  3%  3%  5%  3%  4%  3%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 42% 20% 22%  2%  3%  4%  3%  2%  2%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mi8c dc,h,v,p: 57% 19% 19%  4%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mWeighted P-Frames: Y:1.3% UV:0.3%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mref P L0: 55.4% 11.5% 24.7%  8.3%  0.0%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mref B L0: 81.7% 14.5%  3.8%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mref B L1: 93.7%  6.3%\n",
      "\u001b[1;36m[libx264 @ 0x13d70c130] \u001b[0mkb/s:567.83\n"
     ]
    }
   ],
   "source": [
    "for filepath in files:\n",
    "    if filepath.endswith(\".mp4\") or \"audio\" in filepath:\n",
    "        continue\n",
    "    outfilePath = filepath.replace(\".webm\", \".mp4\")\n",
    "    print(filepath, outfilePath)\n",
    "    ! ffmpeg -i $filepath -r 24 $outfilePath -y\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'frames per second')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "folder = 'test1'\n",
    "measure_files = glob.glob(f'testVideos/{folder}/*.mp4')\n",
    "measure_files.sort()\n",
    "\n",
    "for i, filepath in enumerate(measure_files):\n",
    "    output = ! ffprobe -show_frames $filepath\n",
    "    frames = \"\\n\".join(output).split(\"[FRAME]\")[2:] \n",
    "    times = [float(re.search(r'pts_time=(\\d+\\.\\d+)', frame).group(1)) for frame in frames]\n",
    "    plt.subplot(len(measure_files), 1, i+1)\n",
    "    plt.hist(times, bins=range(int(min(times)), int(max(times)), 1), color= \"blue\" if \"audio\" in filepath else \"red\")\n",
    "    plt.title(filepath)\n",
    "\n",
    "plt.ylabel(\"frames per second\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ffmpeg -itsoffset \"0.956000\" -i testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-audio-1705678317122.webm -itsoffset \"1.039000\" -i testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-audio-1705678317128.webm -itsoffset \"0.968000\" -i testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-audio-1705678317130.webm -itsoffset \"0.963000\" -i testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-audio-1705678317125.webm -itsoffset \"2.288000\" -i testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.mp4 -itsoffset \"2.285000\" -i testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.mp4 -itsoffset \"1.731000\" -i testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.mp4 -itsoffset \"2.336000\" -i testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.mp4 -filter_complex \"[0:a][1:a][2:a][3:a]amerge=inputs=4,pan=mono|c0<c0+c1+c2+c3+c4+c5+c6+c7|[a];[4:v]scale=1280:720[v0];[5:v]scale=1280:720[v1];[6:v]scale=1280:720[v2];[7:v]scale=1280:720[v3];[v0][v1][v2][v3]hstack=inputs=4[v]\" -map \"[a]\" -map \"[v]\" testVideos/test1_resampled.mp4\n",
      "\n",
      "ffmpeg version 6.0 Copyright (c) 2000-2023 the FFmpeg developers\n",
      "  built with Apple clang version 15.0.0 (clang-1500.0.40.1)\n",
      "  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.0_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon\n",
      "  libavutil      58.  2.100 / 58.  2.100\n",
      "  libavcodec     60.  3.100 / 60.  3.100\n",
      "  libavformat    60.  3.100 / 60.  3.100\n",
      "  libavdevice    60.  1.100 / 60.  1.100\n",
      "  libavfilter     9.  3.100 /  9.  3.100\n",
      "  libswscale      7.  1.100 /  7.  1.100\n",
      "  libswresample   4. 10.100 /  4. 10.100\n",
      "  libpostproc    57.  1.100 / 57.  1.100\n",
      "Input #0, matroska,webm, from 'testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-audio-1705678317122.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:57.979393Z\n",
      "  Duration: N/A, start: 0.956000, bitrate: N/A\n",
      "  Stream #0:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)\n",
      "    Metadata:\n",
      "      title           : Audio\n",
      "Input #1, matroska,webm, from 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-audio-1705678317128.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:58.042254Z\n",
      "  Duration: N/A, start: 1.039000, bitrate: N/A\n",
      "  Stream #1:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)\n",
      "    Metadata:\n",
      "      title           : Audio\n",
      "Input #2, matroska,webm, from 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-audio-1705678317130.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:57.960131Z\n",
      "  Duration: N/A, start: 0.968000, bitrate: N/A\n",
      "  Stream #2:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)\n",
      "    Metadata:\n",
      "      title           : Audio\n",
      "Input #3, matroska,webm, from 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-audio-1705678317125.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:57.969927Z\n",
      "  Duration: N/A, start: 0.963000, bitrate: N/A\n",
      "  Stream #3:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)\n",
      "    Metadata:\n",
      "      title           : Audio\n",
      "Input #4, mov,mp4,m4a,3gp,3g2,mj2, from 'testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.mp4':\n",
      "  Metadata:\n",
      "    major_brand     : isom\n",
      "    minor_version   : 512\n",
      "    compatible_brands: isomiso2avc1mp41\n",
      "    encoder         : Lavf60.3.100\n",
      "  Duration: 00:02:51.33, start: 0.000000, bitrate: 1020 kb/s\n",
      "  Stream #4:0[0x1](eng): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt470bg/unknown/unknown, progressive), 1280x720 [SAR 1:1 DAR 16:9], 1017 kb/s, 24 fps, 24 tbr, 12288 tbn (default)\n",
      "    Metadata:\n",
      "      handler_name    : VideoHandler\n",
      "      vendor_id       : [0][0][0][0]\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "Input #5, mov,mp4,m4a,3gp,3g2,mj2, from 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.mp4':\n",
      "  Metadata:\n",
      "    major_brand     : isom\n",
      "    minor_version   : 512\n",
      "    compatible_brands: isomiso2avc1mp41\n",
      "    encoder         : Lavf60.3.100\n",
      "  Duration: 00:02:51.38, start: 0.000000, bitrate: 574 kb/s\n",
      "  Stream #5:0[0x1](eng): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt470bg/unknown/unknown, progressive), 1280x720 [SAR 1:1 DAR 16:9], 571 kb/s, 24 fps, 24 tbr, 12288 tbn (default)\n",
      "    Metadata:\n",
      "      handler_name    : VideoHandler\n",
      "      vendor_id       : [0][0][0][0]\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "Input #6, mov,mp4,m4a,3gp,3g2,mj2, from 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.mp4':\n",
      "  Metadata:\n",
      "    major_brand     : isom\n",
      "    minor_version   : 512\n",
      "    compatible_brands: isomiso2avc1mp41\n",
      "    encoder         : Lavf60.3.100\n",
      "  Duration: 00:02:51.83, start: 0.000000, bitrate: 446 kb/s\n",
      "  Stream #6:0[0x1](eng): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt470bg/unknown/unknown, progressive), 1280x720 [SAR 1:1 DAR 16:9], 444 kb/s, 24 fps, 24 tbr, 12288 tbn (default)\n",
      "    Metadata:\n",
      "      handler_name    : VideoHandler\n",
      "      vendor_id       : [0][0][0][0]\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "Input #7, mov,mp4,m4a,3gp,3g2,mj2, from 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.mp4':\n",
      "  Metadata:\n",
      "    major_brand     : isom\n",
      "    minor_version   : 512\n",
      "    compatible_brands: isomiso2avc1mp41\n",
      "    encoder         : Lavf60.3.100\n",
      "  Duration: 00:02:51.38, start: 0.000000, bitrate: 570 kb/s\n",
      "  Stream #7:0[0x1](eng): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt470bg/unknown/unknown, progressive), 1280x720 [SAR 1:1 DAR 16:9], 567 kb/s, 24 fps, 24 tbr, 12288 tbn (default)\n",
      "    Metadata:\n",
      "      handler_name    : VideoHandler\n",
      "      vendor_id       : [0][0][0][0]\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "Stream mapping:\n",
      "  Stream #0:0 (opus) -> amerge\n",
      "  Stream #1:0 (opus) -> amerge\n",
      "  Stream #2:0 (opus) -> amerge\n",
      "  Stream #3:0 (opus) -> amerge\n",
      "  Stream #4:0 (h264) -> scale:default\n",
      "  Stream #5:0 (h264) -> scale:default\n",
      "  Stream #6:0 (h264) -> scale:default\n",
      "  Stream #7:0 (h264) -> scale:default\n",
      "  pan:default -> Stream #0:0 (aac)\n",
      "  hstack:default -> Stream #0:1 (libx264)\n",
      "Press [q] to stop, [?] for help\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x14ef283e0] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14ef283e0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;36m[libx264 @ 0x102108830] \u001b[0musing SAR=1/1\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0musing cpu capabilities: ARMv8 NEON\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mprofile High, level 5.0, 4:2:0, 8-bit\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0m264 - core 164 r3108 31e19f9 - H.264/MPEG-4 AVC codec - Copyleft 2003-2023 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=15 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=24 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'testVideos/test1_resampled.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf60.3.100\n",
      "  Stream #0:0: Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, mono, fltp, 69 kb/s\n",
      "    Metadata:\n",
      "      encoder         : Lavc60.3.100 aac\n",
      "  Stream #0:1: Video: h264 (avc1 / 0x31637661), yuv420p(progressive), 5120x720 [SAR 1:1 DAR 64:9], q=2-31, 24 fps, 12288 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 4171 fps= 82 q=-1.0 Lsize=   53376kB time=00:02:53.66 bitrate=2517.8kbits/s dup=56 drop=12328 speed= 3.4x    \n",
      "video:51778kB audio:1479kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.222990%\n",
      "\u001b[1;36m[aac @ 0x102107430] \u001b[0mQavg: 196.730\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mframe I:17    Avg QP:14.49  size:240978\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mframe P:1057  Avg QP:18.22  size: 29689\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mframe B:3097  Avg QP:24.33  size:  5664\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mconsecutive B-frames:  0.7%  0.5%  0.9% 97.9%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mmb I  I16..4: 15.5% 64.7% 19.8%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mmb P  I16..4:  1.9%  3.7%  0.4%  P16..4: 25.7%  6.8%  2.8%  0.0%  0.0%    skip:58.8%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mmb B  I16..4:  0.2%  0.3%  0.0%  B16..8: 19.4%  0.7%  0.1%  direct: 0.4%  skip:78.9%  L0:46.5% L1:51.8% BI: 1.6%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0m8x8 transform intra:62.1% inter:82.8%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mcoded y,uvDC,uvAC intra: 44.0% 55.6% 23.1% inter: 4.2% 5.3% 0.1%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mi16 v,h,dc,p: 31% 19% 23% 27%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mi8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 31% 17% 28%  3%  4%  5%  4%  5%  3%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 43% 19% 18%  3%  4%  5%  4%  3%  2%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mi8c dc,h,v,p: 53% 20% 23%  5%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mWeighted P-Frames: Y:0.0% UV:0.0%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mref P L0: 61.6% 12.1% 20.5%  5.8%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mref B L0: 85.5% 12.3%  2.2%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mref B L1: 94.3%  5.7%\n",
      "\u001b[1;36m[libx264 @ 0x102108830] \u001b[0mkb/s:2440.63\n"
     ]
    }
   ],
   "source": [
    "# format inputs\n",
    "audio_inputs = [f'-itsoffset \"{ group_data[i][\"audio_track_start\"] }\" -i {group_data[i][\"audio\"]}' for i in group_data]\n",
    "video_inputs = [f'-itsoffset \"{ group_data[i][\"video_track_start\"] }\" -i {group_data[i][\"video\"].replace(\".webm\", \".mp4\")}' for i in group_data]\n",
    "\n",
    "# format audio chain\n",
    "audioChain = \"\".join([f'[{i}:a]' for i in range(len(audio_inputs))]) + \\\n",
    "    f'amerge=inputs={len(audio_inputs)},' + \\\n",
    "    f'pan=mono|c0<{ \"+\".join([f\"c{j}\" for j in range(len(audio_inputs)*2)])}|[a]'\n",
    "\n",
    "# format video chain\n",
    "videoChain = \"\".join([f'[{i+len(audio_inputs)}:v]scale=1280:720[v{i}];' for i in range(len(video_inputs))]) + \\\n",
    "    f'{\"\".join([f\"[v{i}]\" for i in range(len(video_inputs))])}hstack=inputs={len(video_inputs)}[v]'\n",
    "\n",
    "cmd = f'ffmpeg {\" \".join(audio_inputs)} {\" \".join(video_inputs)} -filter_complex \"{audioChain};{videoChain}\" -map \"[a]\" -map \"[v]\" testVideos/{folder}_resampled.mp4'\n",
    "\n",
    "print(cmd)\n",
    "print()\n",
    "! $cmd -y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Can we write an ffmpeg command that resamples the videos prior to stitching them, all in one go?\n",
    "Maybe, but it doesn't seem to help"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ffmpeg -itsoffset \"0.956000\" -i testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-audio-1705678317122.webm -itsoffset \"1.039000\" -i testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-audio-1705678317128.webm -itsoffset \"0.968000\" -i testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-audio-1705678317130.webm -itsoffset \"0.963000\" -i testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-audio-1705678317125.webm -itsoffset \"2.288000\" -i testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.webm -itsoffset \"2.285000\" -i testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.webm -itsoffset \"1.731000\" -i testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.webm -itsoffset \"2.336000\" -i testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.webm -filter_complex \"[0:a][1:a][2:a][3:a]amerge=inputs=4,pan=mono|c0<c0+c1+c2+c3+c4+c5+c6+c7|[a];[4:v]fps=fps=30,scale=1280:720[v0];[5:v]fps=fps=30,scale=1280:720[v1];[6:v]fps=fps=30,scale=1280:720[v2];[7:v]fps=fps=30,scale=1280:720[v3];[v0][v1][v2][v3]hstack=inputs=4[v]\" -map \"[a]\" -map \"[v]\" testVideos/test12.mp4\n",
      "ffmpeg version 6.0 Copyright (c) 2000-2023 the FFmpeg developers\n",
      "  built with Apple clang version 15.0.0 (clang-1500.0.40.1)\n",
      "  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.0_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon\n",
      "  libavutil      58.  2.100 / 58.  2.100\n",
      "  libavcodec     60.  3.100 / 60.  3.100\n",
      "  libavformat    60.  3.100 / 60.  3.100\n",
      "  libavdevice    60.  1.100 / 60.  1.100\n",
      "  libavfilter     9.  3.100 /  9.  3.100\n",
      "  libswscale      7.  1.100 /  7.  1.100\n",
      "  libswresample   4. 10.100 /  4. 10.100\n",
      "  libpostproc    57.  1.100 / 57.  1.100\n",
      "Input #0, matroska,webm, from 'testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-audio-1705678317122.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:57.979393Z\n",
      "  Duration: N/A, start: 0.956000, bitrate: N/A\n",
      "  Stream #0:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)\n",
      "    Metadata:\n",
      "      title           : Audio\n",
      "Input #1, matroska,webm, from 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-audio-1705678317128.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:58.042254Z\n",
      "  Duration: N/A, start: 1.039000, bitrate: N/A\n",
      "  Stream #1:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)\n",
      "    Metadata:\n",
      "      title           : Audio\n",
      "Input #2, matroska,webm, from 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-audio-1705678317130.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:57.960131Z\n",
      "  Duration: N/A, start: 0.968000, bitrate: N/A\n",
      "  Stream #2:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)\n",
      "    Metadata:\n",
      "      title           : Audio\n",
      "Input #3, matroska,webm, from 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-audio-1705678317125.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:57.969927Z\n",
      "  Duration: N/A, start: 0.963000, bitrate: N/A\n",
      "  Stream #3:0(eng): Audio: opus, 48000 Hz, stereo, fltp (default)\n",
      "    Metadata:\n",
      "      title           : Audio\n",
      "Input #4, matroska,webm, from 'testVideos/test1/1705678316133-89a8a334-06cb-4127-8888-636b5ac97692-cam-video-1705678317124.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:59.283914Z\n",
      "  Duration: N/A, start: 2.288000, bitrate: N/A\n",
      "  Stream #4:0(eng): Video: vp8, yuv420p(progressive), 1280x720, SAR 1:1 DAR 16:9, 1k tbr, 1k tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "Input #5, matroska,webm, from 'testVideos/test1/1705678316133-aa30144f-2005-495b-aa6b-dc790dbe12f1-cam-video-1705678317131.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:59.285432Z\n",
      "  Duration: N/A, start: 2.285000, bitrate: N/A\n",
      "  Stream #5:0(eng): Video: vp8, yuv420p(progressive), 1280x720, SAR 1:1 DAR 16:9, 1k tbr, 1k tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "Input #6, matroska,webm, from 'testVideos/test1/1705678316133-c821f277-846c-4bbf-9dde-0bb3ff8cce79-cam-video-1705678317121.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:58.736506Z\n",
      "  Duration: N/A, start: 1.731000, bitrate: N/A\n",
      "  Stream #6:0(eng): Video: vp8, yuv420p(progressive), 1280x720, SAR 1:1 DAR 16:9, 30 tbr, 1k tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "Input #7, matroska,webm, from 'testVideos/test1/1705678316133-ce3e2c98-a999-4202-8139-2bdfe5d1cec2-cam-video-1705678317126.webm':\n",
      "  Metadata:\n",
      "    encoder         : GStreamer matroskamux version 1.22.3\n",
      "    creation_time   : 2024-01-19T15:31:59.349411Z\n",
      "  Duration: N/A, start: 2.336000, bitrate: N/A\n",
      "  Stream #7:0(eng): Video: vp8, yuv420p(progressive), 1280x720, SAR 1:1 DAR 16:9, 1k tbr, 1k tbn (default)\n",
      "    Metadata:\n",
      "      title           : Video\n",
      "Stream mapping:\n",
      "  Stream #0:0 (opus) -> amerge\n",
      "  Stream #1:0 (opus) -> amerge\n",
      "  Stream #2:0 (opus) -> amerge\n",
      "  Stream #3:0 (opus) -> amerge\n",
      "  Stream #4:0 (vp8) -> fps:default\n",
      "  Stream #5:0 (vp8) -> fps:default\n",
      "  Stream #6:0 (vp8) -> fps:default\n",
      "  Stream #7:0 (vp8) -> fps:default\n",
      "  pan:default -> Stream #0:0 (aac)\n",
      "  hstack:default -> Stream #0:1 (libx264)\n",
      "Press [q] to stop, [?] for help\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x14412ab80] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14412ab80] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0musing SAR=1/1\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0musing cpu capabilities: ARMv8 NEON\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mprofile High, level 5.0, 4:2:0, 8-bit\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0m264 - core 164 r3108 31e19f9 - H.264/MPEG-4 AVC codec - Copyleft 2003-2023 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=15 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'testVideos/test12.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf60.3.100\n",
      "  Stream #0:0: Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, mono, fltp, 69 kb/s\n",
      "    Metadata:\n",
      "      encoder         : Lavc60.3.100 aac\n",
      "  Stream #0:1: Video: h264 (avc1 / 0x31637661), yuv420p(progressive), 5120x720 [SAR 1:1 DAR 64:9], q=2-31, 30 fps, 15360 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc60.3.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x144132870] \u001b[0m\u001b[0;33mNo channel layout for input 1/s dup=70 drop=0 speed=6.16x    \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144132870] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x144012770] \u001b[0m\u001b[0;33mNo channel layout for input 1bits/s dup=147 drop=0 speed=2.93x    \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144012770] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14360bcf0] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14360bcf0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144218000] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144218000] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;35m[vost#0:1/libx264 @ 0x144213380] \u001b[0m\u001b[0;33mMore than 1000 frames duplicated/s dup=147 drop=0 speed=3.39x    \n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x14412f690] \u001b[0m\u001b[0;33mNo channel layout for input 1/s dup=1051 drop=0 speed=4.94x        \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14412f690] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x14360aed0] \u001b[0m\u001b[0;33mNo channel layout for input 1/s dup=1129 drop=0 speed=4.69x        \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14360aed0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x144408c40] \u001b[0m\u001b[0;33mNo channel layout for input 1/s dup=1131 drop=0 speed=3.51x        \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144408c40] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x143704500] \u001b[0m\u001b[0;33mNo channel layout for input 1bits/s dup=1426 drop=0 speed=3.53x    \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x143704500] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144224590] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144224590] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14400c7f0] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14400c7f0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x1437177d0] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x1437177d0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x143704650] \u001b[0m\u001b[0;33mNo channel layout for input 1bits/s dup=1538 drop=0 speed=3.54x    \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x143704650] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x1441309a0] \u001b[0m\u001b[0;33mNo channel layout for input 1/s dup=1540 drop=0 speed= 3.6x        \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x1441309a0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14400d1b0] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14400d1b0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x14400ad80] \u001b[0m\u001b[0;33mNo channel layout for input 1/s dup=1649 drop=0 speed=3.62x        \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14400ad80] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14400d640] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14400d640] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x143616650] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x143616650] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x14371b710] \u001b[0m\u001b[0;33mNo channel layout for input 1/s dup=1883 drop=0 speed=3.69x        \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14371b710] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x123641040] \u001b[0m\u001b[0;33mNo channel layout for input 1/s dup=1885 drop=0 speed=3.67x        \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x123641040] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14360bd40] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14360bd40] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14360b400] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14360b400] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144124a90] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144124a90] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x144133d80] \u001b[0m\u001b[0;33mNo channel layout for input 1/s dup=1992 drop=0 speed=3.67x        \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144133d80] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144014140] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144014140] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x123638000] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x123638000] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x144227d60] \u001b[0m\u001b[0;33mNo channel layout for input 1bits/s dup=2171 drop=0 speed=3.66x    \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144227d60] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x1444152e0] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x1444152e0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x12363a4c0] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x12363a4c0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14400d6c0] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x14400d6c0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[1;32m[Parsed_amerge_0 @ 0x144129b50] \u001b[0m\u001b[0;33mNo channel layout for input 1bits/s dup=2171 drop=0 speed=3.69x    \n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144129b50] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144418d60] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144418d60] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144416480] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144416480] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144019890] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144019890] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144404be0] \u001b[0m\u001b[0;33mNo channel layout for input 1\n",
      "\u001b[0m\u001b[1;32m[Parsed_amerge_0 @ 0x144404be0] \u001b[0m\u001b[0;33mInput channel layouts overlap: output layout will be determined by the number of distinct input channels\n",
      "frame= 5209 fps=121 q=-1.0 Lsize=   33862kB time=00:02:53.53 bitrate=1598.5kbits/s dup=3419 drop=0 speed=4.03x       \n",
      "video:32226kB audio:1474kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.480396%\n",
      "\u001b[1;36m[aac @ 0x14370d850] \u001b[0mQavg: 197.789\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mframe I:22    Avg QP:13.78  size:274177\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mframe P:1312  Avg QP:16.77  size: 12888\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mframe B:3875  Avg QP:24.82  size:  2596\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mconsecutive B-frames:  0.7%  0.2%  0.2% 98.9%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mmb I  I16..4: 15.4% 60.4% 24.2%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mmb P  I16..4:  0.8%  1.5%  0.2%  P16..4: 11.1%  2.6%  1.2%  0.0%  0.0%    skip:82.5%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mmb B  I16..4:  0.1%  0.1%  0.0%  B16..8:  8.5%  0.3%  0.0%  direct: 0.2%  skip:90.8%  L0:47.8% L1:50.8% BI: 1.4%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0m8x8 transform intra:59.8% inter:80.9%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mcoded y,uvDC,uvAC intra: 53.0% 58.1% 33.9% inter: 2.0% 2.0% 0.1%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mi16 v,h,dc,p: 31% 20% 26% 24%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mi8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 32% 17% 25%  3%  4%  5%  4%  5%  4%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 46% 19% 16%  3%  4%  4%  3%  3%  2%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mi8c dc,h,v,p: 52% 20% 23%  6%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mWeighted P-Frames: Y:0.0% UV:0.0%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mref P L0: 61.0% 13.3% 20.2%  5.5%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mref B L0: 84.6% 13.5%  2.0%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mref B L1: 93.1%  6.9%\n",
      "\u001b[1;36m[libx264 @ 0x144212ce0] \u001b[0mkb/s:1520.39\n"
     ]
    }
   ],
   "source": [
    "# format inputs\n",
    "audio_inputs = [f'-itsoffset \"{ group_data[i][\"audio_track_start\"] }\" -i {group_data[i][\"audio\"]}' for i in group_data]\n",
    "video_inputs = [f'-itsoffset \"{ group_data[i][\"video_track_start\"] }\" -i {group_data[i][\"video\"]}' for i in group_data]\n",
    "\n",
    "# format audio chain\n",
    "audioChain = \"\".join([f'[{i}:a]' for i in range(len(audio_inputs))]) + \\\n",
    "    f'amerge=inputs={len(audio_inputs)},' + \\\n",
    "    f'pan=mono|c0<{ \"+\".join([f\"c{j}\" for j in range(len(audio_inputs)*2)])}|[a]'\n",
    "\n",
    "# format video chain\n",
    "videoChain = \"\".join([f'[{i+len(audio_inputs)}:v]fps=fps=30,scale=1280:720[v{i}];' for i in range(len(video_inputs))]) + \\\n",
    "    f'{\"\".join([f\"[v{i}]\" for i in range(len(video_inputs))])}hstack=inputs={len(video_inputs)}[v]'\n",
    "\n",
    "cmd = f'ffmpeg {\" \".join(audio_inputs)} {\" \".join(video_inputs)} -filter_complex \"{audioChain};{videoChain}\" -map \"[a]\" -map \"[v]\" testVideos/{folder}2.mp4'\n",
    "print(cmd)\n",
    "\n",
    "! $cmd -y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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