A computer-assisted exploration of visual themes in Taylor Swift's music videos

ts_videos.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A computer-assisted exploration of visual themes in Taylor Swift's music videos \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Eamonn Bell, Columbia University `<epb2125@columbia.edu>`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "For academic use only. WORK IN PROGRESS.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Summary\n",
    "\n",
    "In this notebook I show how to use the [Clarifai](http://www.clarifai.com/) neural-network-driven image tagging API on music videos released by Taylor Swift in order to demonstrate the utility of this technology to the study of music videos.\n",
    "\n",
    "## Abstract\n",
    "\n",
    "TBD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from clarifai.client import ClarifaiApi\n",
    "import glob\n",
    "import os\n",
    "import pandas \n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clarifai_api = ClarifaiApi()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "TS_WE_ARE_NEVER = 'WA4iX5D9Z64'\n",
    "TS_22 = 'AgFeZr5ptV8'\n",
    "video_ids = [TS_WE_ARE_NEVER, TS_22]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "for video_id in video_ids:\n",
    "    os.system(r\"youtube-dl {} -o '%(id)s'\".format(video_id))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "for video_id in video_ids:\n",
    "    os.system(r\"ffmpeg -i {0}.mp4 -r 1 {0}-%3d.jpeg\".format(video_id))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "results = {}\n",
    "\n",
    "# http://stackoverflow.com/a/434328\n",
    "def chunker(seq, size):\n",
    "    return (seq[pos:pos + size] for pos in xrange(0, len(seq), size))\n",
    "\n",
    "def tag_images_queue(queue):\n",
    "    results = []\n",
    "    \n",
    "    for frames in queue:\n",
    "        \n",
    "        open_files = [open(frame) for frame in frames]\n",
    "   \n",
    "       \n",
    "        api_response = clarifai_api.tag_images(open_files)\n",
    "        \n",
    "        closed = [f.close() for f in open_files]\n",
    "        \n",
    "        results.extend(api_response['results'])\n",
    "        \n",
    "    return results    \n",
    "\n",
    "def tag_batch(frames):\n",
    "    file_count = len(frames)\n",
    "    \n",
    "    q = []\n",
    "    \n",
    "    if file_count >= 127:\n",
    "        for chunk in chunker(frames, 127):\n",
    "            q.append(chunk)\n",
    "    else:\n",
    "        q.append(frames)\n",
    "    \n",
    "    return tag_images_queue(q)\n",
    "    \n",
    "for video_id in video_ids:\n",
    "    frames = sorted(glob.glob('{}-*.jpeg'.format(video_id)))\n",
    "    api_response_results = tag_batch(frames)\n",
    "    results[video_id] = api_response_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "245"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(results['AgFeZr5ptV8'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def parse_video_results(video_results):\n",
    "    classes_seen = []\n",
    "    tags_dicts = []\n",
    "    \n",
    "    for frame_result in video_results:\n",
    "        classes_seen.extend(frame_result['result']['tag']['classes'])\n",
    "        \n",
    "    for frame_result in video_results:\n",
    "        classes = frame_result['result']['tag']['classes']\n",
    "        probs = frame_result['result']['tag']['probs']\n",
    "        \n",
    "        tags_dict = dict(zip(classes, probs))\n",
    "        \n",
    "        unseen_classes = (class_ for class_ in classes_seen if class_ not in classes)\n",
    "        \n",
    "        for unseen_class in unseen_classes:\n",
    "            tags_dict[unseen_class] = np.nan\n",
    "        \n",
    "        tags_dicts.append(tags_dict)\n",
    "           \n",
    "    return tags_dicts            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def parse_results_dict(results_dict):\n",
    "    _ = []\n",
    "    \n",
    "    for video_id in results_dict.keys():\n",
    "        video_results = results_dict[video_id]\n",
    "        \n",
    "        parsed_video = parse_video_results(video_results)\n",
    "        video_df = pandas.DataFrame(parsed_video)\n",
    "        video_df['_video_id'] = video_id\n",
    "        video_df.index.names = ['frame']\n",
    "        _.append(video_df)\n",
    "        \n",
    "    \n",
    "    return pandas.concat(_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = parse_results_dict(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_video_id</th>\n",
       "      <th>abstract</th>\n",
       "      <th>action</th>\n",
       "      <th>actor</th>\n",
       "      <th>actress</th>\n",
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       "      <th>affection</th>\n",
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       "      <th>woodland</th>\n",
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       "      <th>young</th>\n",
       "      <th>youth</th>\n",
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       "    </tr>\n",
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       "      <th>frame</th>\n",
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       "      <th>4</th>\n",
       "      <td>WA4iX5D9Z64</td>\n",
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      "text/plain": [
       "         _video_id  abstract  action  actor  actress  adult  affection  \\\n",
       "frame                                                                    \n",
       "0      WA4iX5D9Z64  0.987164     NaN    NaN      NaN    NaN        NaN   \n",
       "1      WA4iX5D9Z64  0.978400     NaN    NaN      NaN    NaN        NaN   \n",
       "2      WA4iX5D9Z64       NaN     NaN    NaN      NaN    NaN        NaN   \n",
       "3      WA4iX5D9Z64       NaN     NaN    NaN      NaN    NaN        NaN   \n",
       "4      WA4iX5D9Z64       NaN     NaN    NaN      NaN    NaN        NaN   \n",
       "\n",
       "       ailment  animal  anticipation   ...    winter  woman  women  wood  \\\n",
       "frame                                  ...                                 \n",
       "0          NaN     NaN           NaN   ...       NaN    NaN    NaN   NaN   \n",
       "1          NaN     NaN           NaN   ...       NaN    NaN    NaN   NaN   \n",
       "2          NaN     NaN           NaN   ...       NaN    NaN    NaN   NaN   \n",
       "3          NaN     NaN           NaN   ...       NaN    NaN    NaN   NaN   \n",
       "4          NaN     NaN           NaN   ...       NaN    NaN    NaN   NaN   \n",
       "\n",
       "       woodland  wool  writing  young  youth  zombie  \n",
       "frame                                                 \n",
       "0           NaN   NaN      NaN    NaN    NaN     NaN  \n",
       "1           NaN   NaN      NaN    NaN    NaN     NaN  \n",
       "2           NaN   NaN      NaN    NaN    NaN     NaN  \n",
       "3           NaN   NaN      NaN    NaN    NaN     NaN  \n",
       "4           NaN   NaN      NaN    NaN    NaN     NaN  \n",
       "\n",
       "[5 rows x 535 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data.to_pickle('video_data.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Recurring imagery"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def most_common_images(video_id, limit=100):\n",
    "    video_data = data[data._video_id == video_id]\n",
    "    return video_data.count().order(ascending=False).head(limit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "_video_id      217\n",
       "people         192\n",
       "adult          183\n",
       "women          172\n",
       "portrait       163\n",
       "clothing       141\n",
       "one            123\n",
       "politics       122\n",
       "men            117\n",
       "two            103\n",
       "music           98\n",
       "group           91\n",
       "recreation      91\n",
       "indoors         89\n",
       "festival        82\n",
       "room            72\n",
       "musician        67\n",
       "child           59\n",
       "protest         55\n",
       "performance     51\n",
       "religion        48\n",
       "singer          43\n",
       "light           40\n",
       "night           39\n",
       "education       38\n",
       "conflict        37\n",
       "fashion         36\n",
       "furniture       36\n",
       "family          31\n",
       "dark            31\n",
       "              ... \n",
       "backstage       15\n",
       "stage           14\n",
       "shape           14\n",
       "nature          14\n",
       "dress           14\n",
       "health care     14\n",
       "youth           14\n",
       "graphic         14\n",
       "action          14\n",
       "museum          13\n",
       "war             13\n",
       "election        12\n",
       "industry        12\n",
       "retro           12\n",
       "funeral         12\n",
       "three           12\n",
       "school          12\n",
       "hospital        11\n",
       "violence        11\n",
       "building        11\n",
       "love            10\n",
       "seat            10\n",
       "city            10\n",
       "ceremony        10\n",
       "colour          10\n",
       "side view       10\n",
       "street          10\n",
       "monochrome      10\n",
       "modern          10\n",
       "sepia           10\n",
       "dtype: int64"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most_common_images(TS_WE_ARE_NEVER)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Narratology: male/female dynamics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10a7b3450>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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phEr20Z49OinkvlsyhiVjIxjVGJvScOCh3l1vqn/kCkSxpj34nX4TKdx2G3T3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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1092efe10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[data._video_id == TS_WE_ARE_NEVER][['women', 'men']].plot()\n",
    "plt.title('Taylor Swift - We Are Never Getting Back Together')\n",
    "plt.xlabel('Video location (s)')\n",
    "plt.ylabel('Tag class confidence (proprietary)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x109c80ed0>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HZhO1t3Ej/PznslI/5ZRDz5zSIx4Hux2eeqrwvj174M9/1v4fGhLLbLKkMDyskUI0aiSF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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10955d0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[data._video_id == TS_22][['women', 'men']].plot()\n",
    "plt.title('Taylor Swift - 22')\n",
    "plt.xlabel('Video location (s)')\n",
    "plt.ylabel('Tag class confidence (proprietary)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10cea9290>"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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p22eizLsH8ZZhmQMVr3n3g2EZbufqtvjIsOyuTx+XDMvg30iUeedAxcW7bFle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\nIQri/wNbxF/bMfpgMQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10cacbe10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = data[data._video_id == TS_22][['women', 'men']].interpolate()\n",
    "\n",
    "woman_on_screen = pandas.rolling_mean(d['women'], 2) > 0.90\n",
    "to_plot = woman_on_screen.apply(lambda x: 0.85 if x else 0.35)\n",
    "to_plot.plot(color='red')\n",
    "\n",
    "men_on_screen = pandas.rolling_mean(d['men'], 2) > 0.90\n",
    "to_plot = men_on_screen.apply(lambda x: 0.75 if x else 0.25)\n",
    "to_plot.plot(color='blue')\n",
    "plt.title('Gendered Screentime : Taylor Swift - 22')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10cb35f10>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4RG1XmmMktfGbGz7mxjEzM8PMzEyh60gK/JuBxcb3xfRTOj4bkfTOk97fdcCh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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c9aa290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = data[data._video_id == TS_WE_ARE_NEVER][['women', 'men']].interpolate()\n",
    "\n",
    "woman_on_screen = pandas.rolling_mean(d['women'], 2) > 0.90\n",
    "to_plot = woman_on_screen.apply(lambda x: 0.85 if x else 0.35)\n",
    "to_plot.plot(color='red')\n",
    "\n",
    "men_on_screen = pandas.rolling_mean(d['men'], 2) > 0.90\n",
    "to_plot = men_on_screen.apply(lambda x: 0.75 if x else 0.25)\n",
    "to_plot.plot(color='blue')\n",
    "plt.title('Gendered Screentime : We Are Never Getting Back Together')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}