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Add notebook #37

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8cfd070
A new ass_subtitle_export notebook was added containing the exportati…
gretaia Dec 13, 2024
bf1860a
A new ass_subtitle_export notebook was added containing the exportati…
gretaia Dec 13, 2024
34ff5a5
Delete ass_subtitle_export_with_race.ipynb
gretaia Dec 13, 2024
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196 changes: 196 additions & 0 deletions inaFaceAnalyzer/ass_subtitle_export_with_race.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 78,
"id": "600f8011-eada-416e-a979-9821dcb954ea",
"metadata": {},
"outputs": [],
"source": [
"#!/usr/bin/env python\n",
"# encoding: utf-8\n",
"\n",
"# The MIT License\n",
"\n",
"# Copyright (c) 2019-2021 Ina (David Doukhan & Zohra Rezgui - http://www.ina.fr/)\n",
"\n",
"# Permission is hereby granted, free of charge, to any person obtaining a copy\n",
"# of this software and associated documentation files (the \"Software\"), to deal\n",
"# in the Software without restriction, including without limitation the rights\n",
"# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n",
"# copies of the Software, and to permit persons to whom the Software is\n",
"# furnished to do so, subject to the following conditions:\n",
"\n",
"# The above copyright notice and this permission notice shall be included in\n",
"# all copies or substantial portions of the Software.\n",
"\n",
"# THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n",
"# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n",
"# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n",
"# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n",
"# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n",
"# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n",
"# THE SOFTWARE.\n",
"\n",
"\"\"\"\n",
"Module :mod:`inaFaceAnalyzer.display_utils` contains functions allowing to\n",
"export video analysis results to formats allowing to display incrusted face\n",
"detection bounding boxes and classification estimates.\n",
"\n",
"- :func:`ass_subtitle_export` allows to export results as ASS subtitles (faster).\n",
"- :func:`video_export` generate a new video with incrusted information (longer).\n",
"\n",
"Display functions are currenly limited to the results obtained\n",
"with :class:`inaFaceAnalyzer.inaFaceAnalyzer.VideoAnalyzer` and\n",
":class:`inaFaceAnalyzer.inaFaceAnalyzer.VideoTracking` analysis pipelines.\n",
"\n",
">>> from inaFaceAnalyzer.inaFaceAnalyzer import VideoAnalyzer\n",
">>> from inaFaceAnalyzer.display_utils import ass_subtitle_export\n",
">>> va = VideoAnalyzer()\n",
">>> input_vid = './media/pexels-artem-podrez-5725953.mp4'\n",
">>> # define analysis_fps=2 in order to process 2 image frames per second of video\n",
">>> # analysis_fps should be used for analysis AND subtitle export\n",
">>> analysis_fps = 2\n",
">>> df = va(input_vid, fps=analysis_fps)\n",
">>> # export results to ass subtitle\n",
">>> ass_subtitle_export(vid_src, df, './mysubtitle.ass', analysis_fps=analysis_fps)\n",
"\"\"\"\n",
"\n",
"#sample_vid = r'frontiere_2.mp4'\n",
"#df_fps1 = va(sample_vid, fps=1)\n",
"\n",
"import cv2\n",
"import tempfile\n",
"import os\n",
"import pandas as pd\n",
"from Cheetah.Template import Template\n",
"import datetime\n",
"from inaFaceAnalyzer.opencv_utils import video_iterator, get_video_properties, analysisFPS2subsamp_coeff\n",
"\n",
"def _hex2rgb(hx):\n",
" return (int(hx[0:2],16), int(hx[2:4],16), int(hx[4:6],16))\n",
"\n",
"\n",
"def _sec2hmsms(s):\n",
" td = datetime.timedelta(seconds=s)\n",
" h,m,s = str(td).split(':')\n",
" return '%d:%d:%.2f' % (int(h), int(m), float(s))\n",
"\n",
"def _analysis2displaydf(df, fps, subsamp_coeff, text_pat=None, cols=None):\n",
" \"\"\"\n",
" Convert analysis results to a generic pandas dataframe containing\n",
" formatted information to be displayed using export functions defined below.\n",
" \"\"\"\n",
" if isinstance(df, str):\n",
" df = pd.read_csv(df)\n",
" df.bbox = df.bbox.map(lambda x: eval(x))\n",
"\n",
" ret = pd.DataFrame()\n",
" ret['frame'] = df.frame\n",
" ret['bbox'] = df.bbox\n",
" ret[['x1', 'y1', 'x2', 'y2']] = df.apply(lambda x: x.bbox, axis=1, result_type=\"expand\")\n",
" ret['start'] = df.frame.map(lambda x: _sec2hmsms(x / fps))\n",
" ret['stop'] = df.frame.map(lambda x: _sec2hmsms((x + subsamp_coeff) / fps))\n",
"\n",
" if text_pat is None:\n",
" if 'face_id' in df.columns:\n",
" ret['rgb_color'] = df.sex_label_avg.map(lambda x: '0000FF' if x == 'm' else '00FF00')\n",
" text_pat = 'id: %s'\n",
" cols = ['face_id']\n",
" if 'sex_label_avg' in df.columns:\n",
" text_pat += ' - sex: %s (%.1f)'\n",
" cols += ['sex_label_avg', 'sex_decfunc_avg']\n",
" if 'age_label_avg' in df.columns:\n",
" text_pat += ' - age: %.1f'\n",
" cols += ['age_label_avg']\n",
" else:\n",
" text_pat = 'sex: %s (%.1f)'\n",
" cols = ['sex_label', 'sex_decfunc']\n",
" ret['rgb_color'] = df.sex_label.map(lambda x: '0000FF' if x == 'm' else '00FF00')\n",
" if 'age_label' in df.columns:\n",
" text_pat += ' - age: %.1f'\n",
" cols += ['age_label']\n",
" if 'race_label' in df.columns:\n",
" text_pat += ' - race: %s'\n",
" cols += ['race_label']\n",
"\n",
" ret['bgr_color'] = ret.rgb_color.map(lambda x: x[4:] + x[2:4] + x[:2])\n",
" ret['text'] = df.apply(lambda x: text_pat % tuple([x[e] for e in cols if e in x]), axis=1)\n",
" return ret\n",
"\n",
"def ass_subtitle_export(vid_src, result_df, ass_dst, analysis_fps=None):\n",
" \"\"\"\n",
" Export inaFaceAnalyzer results to\n",
" `ASS subtitles <https://en.wikipedia.org/wiki/SubStation_Alpha>`_ .\n",
" ASS can embed complex shapes such as annotated face bounding boxes and\n",
" classification predictions.\n",
"\n",
" Subtitles are a good option for sharing results, since they do not require\n",
" a large amount of storage size, and do not alter original videos.\n",
" Ass subtitles can be displayed in `VLC <https://www.videolan.org/vlc/>`_,\n",
" `Aegisub <http://www.aegisub.org/>`_\n",
" or `ELAN <https://archive.mpi.nl/tla/elan>`_ annotation software.\n",
"\n",
" >>> # displaying mysample_FP2.ass subtitle with vlc\n",
" >>> vlc --sub-file ./mysample_FPS2.ass ./sample_vid.mp4\n",
"\n",
" Args:\n",
" vid_src (str): path to the input video.\n",
" result_df (str or pandas.DataFrame): video analysis result provided as :class:`pandas.DataFrame` or path to saved csv.\n",
" ass_dst (str): output filepath used to save the resulting subtitle. Must have ass extension.\n",
" analysis_fps (numeric or None, optional): Amount of frames per second which were analyzed \\\n",
" (fps analysis argument) \\\n",
" if set to None, then consider that all video frames were processed. Defaults to None.\n",
" \"\"\"\n",
"\n",
"\n",
" assert ass_dst[-4:].lower() == '.ass', ass_dst\n",
"\n",
" video_props = get_video_properties(vid_src)\n",
" fps, width, height = [video_props[e] for e in ['fps', 'width', 'height']]\n",
"\n",
" if analysis_fps is None:\n",
" subsamp_coeff = 1\n",
" else:\n",
" subsamp_coeff = analysisFPS2subsamp_coeff(vid_src, analysis_fps)\n",
"\n",
" displaydf = _analysis2displaydf(result_df, fps, subsamp_coeff)\n",
"\n",
" p = os.getcwd()\n",
" t = Template(file = p + '/template.ass')\n",
"\n",
" t.height = height\n",
" t.width = width\n",
" t.display_df = displaydf\n",
" # text font size set to 4% video height\n",
" t.text_font_size = int(0.04 * height)\n",
"\n",
" with open(ass_dst, 'wt') as fid:\n",
" print(t, file=fid)\n",
"\n",
"#ass_subtitle_export(sample_vid, df_fps1, './my_sample_fps1.ass', analysis_fps=1)"
]
}
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