proofs_of_concept.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison of Hauptstimme annotations and video annotations for two proofs of concept:\n",
    "\n",
    "Our proofs of concept are movement 1 of Beethoven's second symphony and movement 4 of Beach's 'Gaelic' symphony."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "from hauptstimme.compare_annotations import *\n",
    "from hauptstimme.segmentation import get_seg_pts_vec, evaluate_seg_pts, plot_seg_pts_eval\n",
    "from hauptstimme.constants import CORPUS_PATH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dir = \"proofs_of_concept\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Beethoven arguments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "score_mscz = CORPUS_PATH / \"Beethoven,_Ludwig_van/Symphony_No.2,_Op.36/1/Beethoven_Op.36_1.mscz\"\n",
    "\n",
    "aligned_annotations = f\"{dir}/{score_mscz.stem}_annotations_aligned.csv\"\n",
    "score_tstamp_col = f\"RNS_tstamp\"\n",
    "score_annotation_col = \"instrument\"\n",
    "\n",
    "video_annotations = f\"{dir}/RNS_{score_mscz.stem}.csv\"\n",
    "video_tstamp_col = \"scene_start\"\n",
    "video_annotation_col = \"focal_instrument\"\n",
    "\n",
    "start_time = datetime.strptime(\"00:00:07\", \"%H:%M:%S\").time()\n",
    "end_time = datetime.strptime(\"00:12:10\", \"%H:%M:%S\").time()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the above cell then go to \"The comparison\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Beach arguments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "score_mscz = CORPUS_PATH / \"Beach,_Amy/Symphony_in_E_minor_(Gaelic),_Op.32/4/Beach_Op.32_4.mscz\"\n",
    "\n",
    "aligned_annotations = f\"{dir}/{score_mscz.stem}_annotations_aligned.csv\"\n",
    "score_tstamp_col = f\"Seattle_tstamp\"\n",
    "score_annotation_col = \"instrument\"\n",
    "\n",
    "video_annotations = f\"{dir}/Seattle_{score_mscz.stem}.csv\"\n",
    "video_tstamp_col = \"scene_start\"\n",
    "video_annotation_col = \"focal_instrument\"\n",
    "\n",
    "start_time = datetime.strptime(\"00:00:00\", \"%H:%M:%S\").time()\n",
    "end_time = datetime.strptime(\"00:09:37\", \"%H:%M:%S\").time()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the above cell then go to \"The comparison\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The comparison:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get part relationship summary\n",
    "score_summary = score_mscz.parent / f\"{score_mscz.stem}_part_relations.csv\"\n",
    "score_summary_df = pd.read_csv(score_summary)\n",
    "\n",
    "# Get aligned Hauptstimme annotations\n",
    "aligned_annotations_df = pd.read_csv(aligned_annotations)\n",
    "\n",
    "# Get video annotations\n",
    "video_annotations_df = pd.read_csv(video_annotations)\n",
    "\n",
    "# Declare what to round each timestamp to\n",
    "round_to = 0.25\n",
    "# Declare the start and end timestamps of the video\n",
    "start_tstamp = (start_time.hour*60 + start_time.minute) * 60 + start_time.second\n",
    "end_tstamp = (end_time.hour*60 + end_time.minute) * 60 + end_time.second\n",
    "# Declare the tolerance when comparing timestamps\n",
    "tau = 4     # Tolerance of 1 second"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get a vector of the video annotations\n",
    "video_annotations_df[video_annotation_col] = get_default_instrument_names(\n",
    "\tvideo_annotations_df[video_annotation_col]\n",
    ")\n",
    "video_annotations_vec = get_annotations_vec(\n",
    "\tvideo_annotations_df, video_tstamp_col, video_annotation_col, round_to, start_tstamp, end_tstamp\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the instruments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Match percentage: 20.78822000866176\n",
      "Partial match percentage: 2.252057167605024\n",
      "No match percentage: 28.36725855348636\n",
      "Can't match percentage: 48.59246427024686\n"
     ]
    }
   ],
   "source": [
    "haupt_video_comparison(aligned_annotations_df, score_summary_df, video_annotations_vec, score_tstamp_col, round_to, start_tstamp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the timestamps:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get vectors for the annotation segmentation points\n",
    "haupt_seg_pts = aligned_annotations_df[score_tstamp_col].to_list()\n",
    "haupt_seg_pts_vec = get_seg_pts_vec(haupt_seg_pts, round_to, end_tstamp)\n",
    "\n",
    "video_seg_pts = video_annotations_df[video_tstamp_col].to_list()\n",
    "video_seg_pts_vec = get_seg_pts_vec(\n",
    "    video_seg_pts, round_to, end_tstamp\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hauptstimme points compared to video points:\n",
      "P = 0.814;  R = 0.250;  F = 0.383\n"
     ]
    },
    {
     "data": {
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TM8x39/e1dOnSqlq1qiTPt31u7DdeabZs2aK//vpLUtafw759+2rfvn26/fbbnZ4YcaRKlSry8/OTJO3YscNpufQn57K7v3a1fpYnT56smTNnqnjx4vrggw/cWsZbxzrLly/X3r17JWXcB7tw4YK2b9+uvXv36tKlS+6uikv0s/1+TkxMtJJo99xzj5X0vnTpkhISEhQfH2/7Qgf2wa5c3tqXS6vH0zroZ8954zyIu/tgtWvXti5+ye4+2NX6vQ0A2ZGjyZW0Kx0rV66sgIAAp+XSHyymLeOuTZs2OazH2+1c7aZMmaLq1asrJCRERYoUUZUqVfT0009necXoc889Jyn1JE/a1XKXe/vttzOVtyvtfVC0aFGXOwORkZEKCwuTxHvAF1auXGlN16xZU6tXr9a9995rvaciIyNVqlQp9erVSwcPHvS4nf/++886QcD3gvf89NNPOnfunCTpqaeesk7GudK9e3edO3dOTzzxhO68806vxkM/O7Zo0SJr+vrrr7e17JEjR7RixQo988wzevfddyVJJUuW1BNPPOFRLElJSVqxYoWk1BP8aSfx7Thz5owSEhIk0c/pZdXPhQsXtqbTrnp0xBijU6dOSUo9ibJt27YM8z3Zz0pISNDZs2ddlnUkN/YbrwTnzp3T1q1bNWLECDVp0sRKeL344otOl1mxYoXGjh2rggULasyYMbbaK1q0qB5//HFJqRdB/P3335nKJCcna8iQIZnK23G1f5ZPnDihF154QZI0dOhQ62rlrHjrWOfyfbCtW7eqTZs2CgsLU+XKlRUVFaUSJUqoQ4cO2brKnX72rJ/Xr19vJU9q1qypU6dO6cUXX1TJkiV17bXXqkKFCipatKjuueceLVy40K062QfLWZ4eH7sjO/tyaQ4dOmRtb0/roJ99ex7E3e//gIAAVa5cWZJn2/5q/94GgOzKseTKhQsXrCx8VFSUy7LXXHONQkNDJcn6UnfXnj17rOms2omOjram7bZztdu0aZM2b96s8+fP68yZM9q2bZu+/vpr3XnnnXr44Yednrjp3Lmz9fiOnj17qmvXrpoxY4bi4uI0depUPfzww9YVXf369bNuJ7Yr7X2Q1XtA+r/3Ae+B3Jd+B3HBggVq2LCh5s6daz3STZIOHz6s0aNH6+abb9b69es9aofvhZyR/pFgaZ9rV77//nvNmTNHxYoV04gRI7weD/2cWUpKit5//33r/2m37rvStGlT+fn5yc/PT+Hh4WrYsKG+/PJLGWNUsmRJ/fLLLypWrJhH8YwfP97aF3j00Uc9qoN+zsydfk5/IiX9SZrLrVu3TmfOnLH+v3v37gzzPdn+xpgMy7kjt/Yb86qJEydan8PQ0FBVrVpVL7/8snWhQd++fdW+fXuHyyYlJalr164yxuiVV15R9erVbbc/YsQI3XLLLUpMTFTjxo311ltv6c8//9TKlSv11VdfqXbt2lq5cqVCQkL09ddfu/3IsfSu9s/ya6+9pgMHDui2227TM8884/Zy3tpu6ffB/v33X9WqVUtTp05VUlKS9frJkyf1zTffqFatWvrzzz/djjEn4r1SedrP6fsnJSVFtWvX1ieffKITJ05YrycmJurPP//UnXfeqaFDh7qsj32wnOfp8XFW1q9fr99++01SaqLN08TI8OHDreS8O/uDjtDPvj0Pkrb9Q0NDs9wXT9v+hw8fznDnkzvoZwDInhxLrqR/zmb6qyedSTtITn+A7+120trwpJ2rVUhIiB577DFNmDBBS5Ys0bp16/THH3+oX79+1oH1tGnT1LJlywwHZ2kKFCigr776SlOmTNFNN92kzz//XA899JDq1KmjNm3aaNq0abrjjjs0d+5cvfPOOx7HmfY+yMn3GrLv2LFj1vRzzz0nPz8/vfPOO9q9e7cuXryof/75x3qUyYEDB9SqVSvrimo7+F7wvt27d1snaBs2bGhdHeXMsWPH1Lt3b0nSkCFDFBER4fWY6OfMPvroI+vxDa1bt3b5aKWs/O9//9PmzZvVqFEjj5bfsWOH+vXrJym1f15//XWP6qGfM3Onn++//37r7o8RI0ZYiYv0UlJSrD5Kc/lz0nNr++fWfuOV5uabb1ZsbKyGDBni9G7BoUOH6p9//lGFChXUv39/j9opVaqUlixZoo8//liFChXSwIEDdc8996hBgwbq2LGj/v77b3Xp0kVr1qzJ8EgpO67mz/KSJUv0+eefKyAgQGPHjnXrzs803tpu6ffBXnjhBZ09e1a9e/fW1q1bdfHiRW3fvl2vvvqq/Pz8dPr0aT366KOZkq25Ge+VKDv9nL5/hg4dqq1bt+q+++5TbGysLly4oEOHDmnMmDEqWrSojDHq27ev9RgxR3WxD5Zzsnt87MrFixfVpUsX626RtLuI7Vq1apU+/vhjSakny7t37+5RPfSzb8+DeHKOQ+KcGgDkthy9cyWNq2dzpkl7BmzaeAw50U7658zabedqtXfvXk2aNEldunRRo0aNdPPNN+uee+7RO++8o3/++Ue1atWSlHpVrLPHUGzevFlff/21NmzY4HD+ihUr9MUXX1jPgfZE2vsgJ99ryL70j4m5cOGCvvjiC/Xr10/R0dEKDAxU9erVFRMTo2effVZS6rOi7T7eJK3uNHwveMe3335rjYfjzl0rr7zyig4dOqR69epZ/elt9HNGixYtUt++fSVJERERbn92YmJitGHDBv39999avHixRowYoSpVqujTTz9Vp06dPHpE37lz59S6dWvrar5Ro0apTJkytuuR6OfLudvP0dHR1iMm9u7dq9tuu02//vqrTp06pQsXLmjlypVq3ry55syZk2G7Xr7dcmv759Z+Y17VqlUrbdiwQRs2bFBsbKwmTZqkhx9+WH/99Zcef/xxzZw50+FyW7dutU6+ffrppypUqJDHMcyfP1/ffvutw8982qDqEydO9Hgw+6v1s5yYmKhnn31Wxhj17t1bNWrUsLW8t7bb5ftgb731lkaMGKHKlSsrMDBQFStW1LBhw6z304kTJ6xHwfki3itNdvv58v655557NHPmTNWpU0dBQUEKDw/Xc889p5kzZ1qDWr/++usOxypkHyxneeP42JlevXpZ45U8/fTTatGihe34Dh48qEceeUTJycny8/PTV199ZY3HYRf97NvzIJ6c45A4pwYAuS3Hkitpg/BJcusgLO3WRbsHhXbaSX97ZHYOPq8mrm4/LVWqlH766ScVLFhQUurJs8stWbJEDRo00IwZM1S2bFl98803OnDggBITE5WQkKDRo0crJCREP/zwg+rWrat//vnHozjT3gc5+V5D9qX/vN5444166qmnHJZ77733rB23H3/8MVvt8L3gHd98842k1B3qdu3auSy7cOFCxcTEqECBAho7dqx1EsDb6Of/888//+jhhx9WcnKygoODNWXKFLevVK1QoYJq1KihmjVrqnHjxurdu7f+/vtvNW/e3DqxY+cRT8nJyXr00Uetx/p1797d1uDal6Of/4/dfv7ggw/UvHlzSanPTW/VqpWKFi2qQoUKqUGDBvr9999Vu3btDI+uKVKkSIY6cmv759Z+Y15VrFgx1ahRQzVq1FCdOnX02GOPaerUqfr666+1Y8cOtWzZUhMnTsy0XLdu3XThwgW1adPG6mtPfPLJJ3rooYcUFxen22+/XXPnztXJkyd18eJFbdq0Sa+88oqOHTumoUOH6s477/ToatWr9bP83nvv6d9//9W1115rDS5uh7e2W/p6SpYsqT59+jis49VXX7XGL5w8ebLDk/e5Ee+Vxpv9LKXeveJoEPJGjRqpdevWklJP3F5+0pZ9sJyX3eNjZ4YMGaLPP/9cklSnTh2NHj3admynT5/WAw88YO23vf/++9kab4d+diy3zoN4co5D4pwaAOS2HEuupD84d+cALO1qHXduefS0nfRXBNltB45VrFhR99xzjyRp27Zt2rdvnzXv4sWLevzxx3Xy5EmVLl1aK1eu1JNPPqlSpUqpYMGCioqKUo8ePbR48WIFBwdr3759evrppz2KI+19kJPvNWRf+s/rvffe67RciRIlVLt2bUmpzx22e5Us3wveFRsbq3///VeS9NBDD7k82Lh48aK6desmKfWxUjfffHOOxUU/p9q5c6fuvfdeHT9+XAUKFNAPP/yg22+/PVt1BgcHKyYmRiEhIUpISNBrr73m1nLGGHXs2FGzZs2SlPqM708//TRbsdDPqTzp56CgIM2YMUMTJkzQzTffnOERNREREerXr5+WLFmS4eTpNddck6GO3Nr+ubXfeKV56qmn9OijjyolJUW9evXK8OigL7/8UgsWLFCRIkX0ySefeNzG33//rZdeeknGGN19992aP3++7r77boWFhSkwMFDXX3+9hg8frvHjx0uSli1b5tHJ46vxs/zvv/9ad3+MGjUqw+NU3OWt7Za+nqZNmzq9OjkgIEB33XWXpNTHS+3YscMn8V5JvN3P4eHh1lXxjjRr1syaXr16tTXNPlje4Or42Jlx48bpjTfekJQ6YPisWbNsv48uXLigli1bas2aNZJS72Byd//NGfrZudw4D+LJOQ6Jc2oAkNsCcqri4OBglShRQkePHs3yitfjx49bX9LpB8hyR/oBt7JqJ/2AW3bbgXPVq1e3TqTt3bvXevTLnDlzrFtcn3/+eesquMvdcMMNevLJJ/X5559rzZo1Wr9+vW666SZbMURFRengwYNuXV2d9j7gPZD7oqOjtXLlSms6q7JS6pgAx44dc/r+cYTvBe+yM5D91KlT9d9//6lgwYKqXr26fvjhh0xl0g/aunHjRqtMvXr1VKFCBbfjop+lffv26e6779a+ffvk5+enL7/8Ui1btvRK3SVLltRtt92muXPn6tdff1VSUpJ1hZ4zPXv21HfffScpdcyPb7/9NttXzZYtW9aapp/t97O/v7+6dOmiLl266PTp0zp48KBCQkJUunRpq2+2bt1qlb98MPTLP2clS5Z02lba9vfz88tyQNTL5dZ+45WoZcuWmjx5ss6ePas5c+ZYA9unDWjdpEkTLVmyxOGyhw4dsqbTvmtDQ0MzPGomJiZGKSkpkqTBgwc7vFpeSh2c9/3339fWrVs1ceJEffDBB7bGlLgaP8sfffSREhMTVbFiRZ07d87hb+LGjRut6fnz5+vAgQOSpBYtWig0NNRrv3Xp/+/uPpiUOjhypUqVXJZPj372rJ/Tr7+dAaUPHz5sTbMPlnc4Oz52ZNKkSerRo4ckqVy5cpo7d67L31pHkpOT1bZtWy1YsECS1KVLFw0fPtzD6P8P/exaTp8HiYqK0qpVq3T27FmdOHHC5QVuads/PDw8w6O73HE1fm8DgDflWHJFSv2xWbJkibZt26bk5GRrYNXLpV0RLUnXX3+97TYc1ePtduCcswPrzZs3W9O33HKLyzpuvfVW6zbof//913ZypXr16lqzZo1OnjypAwcOON2B2b9/vzVAOu+B3HfDDTdoypQpkmQN1OhM+vnOvjucqVq1qgoUKKBLly7xvZBNSUlJ1oF3RESE7rvvPpfl024VT0pKUteuXbOs/+eff9bPP/8sKfUEn50D+6u9n48cOaJ77rnHuqp41KhRbo2HY0d4eLik1DFUjhw5osjISKdl+/TpYz1z+vbbb9fPP/+cZTLGHUWKFFF0dLQSEhLoZ2Wvn4sUKZLpsV+XLl3SX3/9JSn1KszLT+hcvp/l6krotO0fHR3t0ZXbubHfeCVK+xxK0q5du6zptO/bmTNnOh2TJb3HH39cUurJu/TJFTv7a7fccou2bt2qY8eO6dChQypVqpR7K6Gr87Oc1kc7duywtr8rb7/9tjW9c+dOhYaGeu1Y54YbbrCmc3IfjH72rJ+90T/sg+Ud7iaep0+frg4dOiglJUWRkZGaN2+e7YsTUlJS9NRTT2nGjBmSpHbt2mncuHG2Y3aEfnYtp8+DVK9e3fqM/vvvv6pfv77DOpKTk7V9+3ZJnm37q/F7GwC8KcceCyalPhNWSr11MO32VEcWLVpkTd9222222qhQoYJ1hUD6ehxZvHixpNTMfPny5W21A+fSXwGV/qqc9Dv7ycnJLutISkpyuJy70t5rkuv3QXbea8i+9I+wyeoxE2k7iMHBwSpevLitdgIDA1W3bl1JqQMFunqsWNp7IigoyHoUGf7Pb7/9pqNHj0qS2rdv79HnM6dczf188uRJNWvWzPr+ff/999WzZ0+vt5N+gE1Xt/6/8847GjZsmKTU54TPnDnTq89hTvuO37Jli3W1ryP57Ts+N/p5wYIF1mfc0XhK7v6+HjhwQP/9958kz7d9buw3Xonc/Rx6yhf7a1fbZzk7vHWs48k+WFpddtHP9pUrV07XXnutJCk+Pt7lWDfZ7R9vuJr3wdzh7Pg4vXnz5qlt27ZKTk5WiRIlNHfuXFt3iaXp1q2bdSFUixYtvHLXcBr62bWcPg/i7j5YXFycdUdvdvfB+N4GAA+YHLRq1SojyUgy3bp1c1jm0qVL5vrrrzeSTLFixUxiYqLtdrp37261s2LFCodlVqxYYZXp0aOH7Tbg2I4dO0xgYKCRZCpVqpRh3k8//WRt89dee81lPW3atLHKrlmzxnYc+/fvN/7+/kaSadasmdNyzZo1M5KMv7+/2b9/v+128oudO3da2/vpp5/2uJ6BAwda9SxYsCDL8snJySY8PNxIMuXKlTPJyckOy+3YscPqz7vuusuj2IYOHWrFNmnSJIdlEhISTIECBYwk07x5c4/aycu80c8PP/ywVce6deu8EteCBQusOgcOHJituq7Gfj579qy57bbbrPXu169fjrSTkJBgfb+XK1fOabmPP/7YiqVmzZrm6NGjXo/lxx9/tNoYMmSIwzJnz54111xzjZFkqlev7vUYcltu9HNKSorVRsGCBc2OHTsclkvbTytevLg5e/aswzJDhgyxYp08ebJH8eTWfuOVpnnz5rZ+a9Nr0qSJtawzvXr1ssrMmjXLabnExEQTGRlpJJmiRYualJQUW7EYc3V+lrPizr6Ut451atWqZSSZ0NBQc+LECYdlTp06ZcLCwhzu27uLfs7MnX7u3bu3VWbu3LlO62ratKlVbvfu3bbiYB8s57k6Pk6zbNkyExoaan2fxsXFedRW+vfMXXfdZS5cuJCd0B2inx3LjfMgFy9eNEWLFjWSzPXXX+/0d7dbt25WHbGxsR6tD9/bAOC5HE2uGGNM48aNjSQTEBBgli9fnmn+sGHDXO7gpd8BdHZycMuWLdaPee3atc25c+cyzD937pypXbu2Fcd///3njVXL96ZPn26SkpKczj9w4IB1kCbJfPjhhxnmHz9+3ISEhBhJpkiRIubvv/92WM+sWbOsE+lly5Y1ly5dylQm/cmBnTt3OqznqaeesspMmTIl0/zJkyd7JaGQH/gquWJMxh10R5/5pKQkc99997nsy/TxN2nSxGE7R48etXZGy5UrZ44cOZJhfnJysmnRooXHJ6yuBNnt56NHj1oHDTVr1vRaXO4e2NPPmV28eNHce++91vq88MILtuvYsmWLmTdvnssyJ06csH6/JZn+/fs7LPfll18aPz8/I8lUrVrVHDhwwHY8xhirHWdJnMTERFOxYkUjyYSFhZlt27ZlKtOjRw+rnpiYGI/iyCu80c/GGHPkyBGnJ1qSk5MzbLMBAwY4reeLL76wyvXs2TPT/G3btlknYytXrux036FcuXJZnujP7n7jlSQmJsacP3/eZZkRI0ZY61uhQgWnFyU4405y5ffff7fK3HjjjebkyZMOy73++utWuccff9xhGT7L9rmzL+WtY530J886duzosEyXLl2sMsOHD3dYhn62z51+3rVrlwkODrb2uxx9Fr/55hurngceeMB2HOyDZU92j4+NMWbdunWmWLFiRkpNdC5dutSjWNK/pxo2bGjOnDljuw762bG8dB6kf//+VjvDhg3LNH/58uUmICDAZR8aw/c2AOSkHE+urF271hQqVMhIMoULFzbvvfeeWbFihZk/f7559tlnrS/nqlWrmlOnTmVa3p3kijHG9O3b1ypXq1Yt88MPP5jVq1ebH374IcMP3+uvv56Da5u/lCtXzpQpU8Y8//zz5vvvvzfLly8369atM3PnzjX9+vUzJUuWtLZro0aNHJ7Aeeutt6wyhQsXNq+//rqZP3++WbdunZkzZ47p3r27tTMgyXzzzTcOY3EnubJ7927rroiAgADTp08fs2TJErNkyRLTp08fq53w8HCTkJDgzU2V5y1ZssTExMRYf8OHD7e252233ZZhnqsdpcvLtWzZ0qqnT58+GeYtWbLEYR3nz583t9xyi7XcY489ZmbPnm3WrFljJk+ebBo0aGDNa968ucMrdNw5EDDGmLFjx1rlKlWqZL788kuzevVq8+uvv5o77rgjy5NEVxpv9XOa0aNHW8t/8MEHXovTmwf2xlxd/dy6dWtrfe68807z999/mw0bNjj927JlS6Y60rb/TTfdZAYOHGimT59uYmNjzdq1a82sWbNMv379TOnSpa12atSo4fBuhV9++cU62RcWFmZmz57tMpYNGzY4PfDP6oDPGGN+++036wC0VKlSZtSoUWbVqlVmzpw5Ga76a9Soke0T0HmNN/rZGGOmTJliSpUqZV544QUzdepUExcXZ5YuXWo+++wzc/PNN1tt3H///ebixYtO40lOTs5wF02bNm3MnDlzzKpVq8yoUaNMRESEkVLvCnV154M7yZXs7jdeScqVK2eKFy9uunbtar766iuzdOlS89dff5klS5aYzz77LMM2DwwMdHkluzPuJFeMMebOO++0ylWoUMF8/PHHZvny5Wbt2rVm8uTJGS56CA0NNf/++6/Devgs2+fuhSreOtZJfydUs2bNzLRp08zatWvNr7/+mmFerVq1nCb/6Gf73O3n9Ank6667znz55ZcmLi7OzJ8/3/Tq1SvD764nFwyyD5Y92T0+3rZtm/WbKcl89NFHWe47HTx4MFMcI0eOtOooW7asWbp0aZb1OLrTk352LC+dBzl16pSpWrWqVe7ZZ5818+fPNytWrDDvvfeeKVy4sJFkChUq5PIpA3xvA0DOyfHkijGpmf+0Kxod/VWtWtVs3brV4bLuJlcuXbpkOnfu7LQNSeaZZ55xeDUAHEt/EsTVX5s2bczx48cd1pGSkmJefPFF68pmZ38FCxZ0enWcMe4lV4wxZuXKlRlOCl7+V7p0abNy5cpsbpkrz9NPP+1WX2Z1AsZOHa4+r/v27TO33nqry+WbN2/u9MSZuwcCxhgzYMAAl++/5s2bZ3nl8JXCW/2cpl69ekaSKVCggFcfo+ftA3tjrp5+ttO/zg6g0m//rP4eeOABc+jQIYex2H2/Sc5PKLmKN73x48dbd1M5+qtbt645fPiwza2a93ijn41JTa64Ws7Pz8907tzZrceIHD582NSpU8dpXUFBQWbChAku63AnuWJM9vYbryTu7mdFRUWZP/74w6M23E2uHDt2LMMJMmd/4eHhLpM8fJbtc/eku7eOdU6fPp3hzjhHf3Xq1HH5u08/22fnbu++ffu63KeJiIhweGefO9gHy57sHh/HxMTY/o131E/pv9vd/XN0DE0/O5aXzoMYY8zWrVtNlSpVnNYRFhZmZsyY4bIOvrcBIOfkSnLFGGPi4+NN7969TdWqVU1ISIgpVqyYqV27thk6dKjT53cb435yJc1vv/1mWrZsacqUKWMCAwNNmTJlTMuWLV1eSQnHFi5caAYPHmzuu+8+U7VqVVO8eHETEBBgihUrZmrWrGm6devm9o59XFycee6550yNGjVMkSJFTIECBUzRokXNrbfeal566SWnV92mcTe5YkzqCaA333zT1KhRwxQuXNgULlzY1KxZ07z55puZbmO+WuS15IoxqY//Gjt2rGnSpIkJDw83BQsWNKVLlzYPPfSQmTp1qstl7RwIGJP6XOP27dub6OhoExgYaCIiIsw999xjvv/++yyXvZJ4M7ny33//WeXuu+8+r8aZEwf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      "text/plain": [
       "<Figure size 800x300 with 6 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 303,
       "width": 811
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "P, R, F, _, _, _, _, _ = evaluate_seg_pts(\n",
    "    haupt_seg_pts_vec, video_seg_pts_vec, tau\n",
    ")\n",
    "print(\"Hauptstimme points compared to video points:\")\n",
    "print(\"P = %0.3f;  R = %0.3f;  F = %0.3f\" % (P, R, F))\n",
    "fig, ax = plot_seg_pts_eval(\n",
    "    haupt_seg_pts_vec, video_seg_pts_vec, tau, round_to, other_seg_pts=\"Video\"\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "imp_env",
   "language": "python",
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