{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "16651843",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f46843d136af4c79a73841b997fa3284",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Accordion(children=(GridBox(children=(Label(value='CH2'), Label(value='CH3'), Label(value='CH4'…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Exception in thread Thread-3:\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\milos\\AppData\\Local\\Programs\\Python\\Python37\\lib\\threading.py\", line 917, in _bootstrap_inner\n",
      "    self.run()\n",
      "  File \"C:\\Users\\milos\\AppData\\Local\\Programs\\Python\\Python37\\lib\\threading.py\", line 865, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"c:\\users\\milos\\documents\\github\\portiloop-software\\portiloop\\src\\capture.py\", line 927, in start_capture\n",
      "    detector = detector_cls(threshold, channel=channel) if detector_cls is not None else None\n",
      "  File \"c:\\users\\milos\\documents\\github\\portiloop-software\\portiloop\\src\\detection.py\", line 56, in __init__\n",
      "    self.interpreters.append(edgetpu.make_interpreter(model_path))\n",
      "NameError: name 'edgetpu' is not defined\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from portiloop.src.capture import Capture\n",
    "from portiloop.src.detection import SleepSpindleRealTimeDetector\n",
    "from portiloop.src.stimulation import SleepSpindleRealTimeStimulator\n",
    "\n",
    "my_detector_class = SleepSpindleRealTimeDetector  # you may want to implement yours\n",
    "my_stimulator_class = SleepSpindleRealTimeStimulator  # you may also want to implement yours\n",
    "\n",
    "cap = Capture(detector_cls=my_detector_class, stimulator_cls=my_stimulator_class)"
   ]
  }
 ],
 "metadata": {
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   "language": "python",
   "name": "python3"
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0b2"
  },
  "vscode": {
   "interpreter": {
    "hash": "770b75f59a9c369b74cb4cefed633f309c892e213e0ed32eed0937c0a5627480"
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 },
 "nbformat": 4,
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}