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Diffstat (limited to 'megapixels/notebooks/datasets/duke_mtmc/duke_mtmc_timestamps.ipynb')
| -rw-r--r-- | megapixels/notebooks/datasets/duke_mtmc/duke_mtmc_timestamps.ipynb | 213 |
1 files changed, 213 insertions, 0 deletions
diff --git a/megapixels/notebooks/datasets/duke_mtmc/duke_mtmc_timestamps.ipynb b/megapixels/notebooks/datasets/duke_mtmc/duke_mtmc_timestamps.ipynb new file mode 100644 index 00000000..5179cc7c --- /dev/null +++ b/megapixels/notebooks/datasets/duke_mtmc/duke_mtmc_timestamps.ipynb @@ -0,0 +1,213 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Duke MTMC Timestamps\n", + "\n", + "- use pymediainfo to extract timestamps\n", + "- save data to CSV" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "%reload_ext autoreload\n", + "%autoreload 2\n", + "\n", + "import os\n", + "from os.path import join\n", + "import math\n", + "import time\n", + "from glob import glob\n", + "import datetime\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "from pathlib import Path\n", + "from tqdm import tqdm_notebook as tqdm\n", + "from pymediainfo import MediaInfo" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [], + "source": [ + "fp_dir_videos = '/data_store/datasets/people/duke_mtmc/dataset/videos/'\n", + "fp_times = '/data_store/datasets/people/duke_mtmc/processed/video_times.csv'" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "fps_video = glob(join(fp_dir_videos, '**/*.MTS'), recursive=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "def mediainfo(fp_in, raw=False):\n", + " \"\"\"Get media info using pymediainfo\"\"\"\n", + " \n", + " media_info_raw = MediaInfo.parse(fp_in).to_data()\n", + " media_info = {}\n", + "\n", + " if raw:\n", + " for d in media_info_raw['tracks']:\n", + " if d['track_type'] == 'Video':\n", + " media_info['video'] = d\n", + " elif d['track_type'] == 'Audio':\n", + " media_info['audio'] = d\n", + " else:\n", + " for d in media_info_raw['tracks']:\n", + " if d['track_type'] == 'Video':\n", + " media_info['video'] = {\n", + " 'codec_cc': d.get('codec_cc', ''),\n", + " 'duration': int(d.get('duration','')),\n", + " 'display_aspect_ratio': float(d.get('display_aspect_ratio', '')),\n", + " 'width': int(d['width']),\n", + " 'height': int(d['height']),\n", + " 'frame_rate': float(d['frame_rate']),\n", + " 'frame_count': int(d['frame_count']),\n", + " }\n", + " \n", + " return media_info" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "87\n" + ] + } + ], + "source": [ + "print(len(fps_video))" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "def modification_date(fp):\n", + " t = os.path.getmtime(fp)\n", + " return datetime.datetime.fromtimestamp(t)" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9cb4c25594cc44d9995da82392acca0a", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(IntProgress(value=0, max=87), HTML(value='')))" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Get file timestamp\n", + "meta = []\n", + "for fp_video in tqdm(fps_video):\n", + " time_start = modification_date(fp_video)\n", + " camera = int(Path(fp_video).parent.name[-1])\n", + " fn = Path(fp_video).name\n", + " m = mediainfo(fp_video)\n", + " m = m.get('video')\n", + " duration = int(m.get('duration'))\n", + " minutes = duration / 1000 / 60\n", + " time_end = time_start + datetime.timedelta(0, duration//1000) # ms to s\n", + " meta.append(\n", + " {\n", + " 'fn': fn, \n", + " 'camera': camera,\n", + " 'time_start': str(time_start),\n", + " 'time_end': str(time_end),\n", + " 'duration': duration, # ms\n", + " 'frame_count': m.get('frame_count'),\n", + " 'frame_rate': m.get('frame_rate'),\n", + " 'width': m.get('width'),\n", + " 'height': m.get('height'),\n", + " 'minutes': f'{minutes:.3f}',\n", + " })" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [], + "source": [ + "df_meta = pd.DataFrame.from_dict(meta)\n", + "df_meta.to_csv(fp_times, index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total minutes: 888.7956166666667\n" + ] + } + ], + "source": [ + "print('Total minutes:', df_meta['duration'].sum()/1000/60)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "megapixels", + "language": "python", + "name": "megapixels" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} |