{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Label statistics\n",
    "This very simple notebook iterates through labels from Labels.py and counts anomalous, normal and not annotated images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from py.Labels import LABELS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Beaver_01: 0 anomalous, 74 normal, 0 not annotated, 695 max\n",
      "Marten_01: 732 anomalous, 2373 normal, 0 not annotated, 3105 max\n",
      "Fox_03: 246 anomalous, 3702 normal, 1547 not annotated, 5495 max\n",
      "GFox_03: 246 anomalous, 3702 normal, 1547 not annotated, 5495 max\n"
     ]
    }
   ],
   "source": [
    "for session_name, labels in LABELS.items():\n",
    "    anomalous = len(labels[\"anomalous\"]) if \"anomalous\" in labels else 0\n",
    "    normal = len(labels[\"normal\"]) if \"normal\" in labels else 0\n",
    "    not_annotated = len(labels[\"not_annotated\"]) if \"not_annotated\" in labels else 0\n",
    "    max_nr = labels[\"max\"] if \"max\" in labels else 0\n",
    "    print(f\"{session_name}: {anomalous} anomalous, {normal} normal, {not_annotated} not annotated, {max_nr} max\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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