{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ultralyticsplus import YOLO, render_result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n.pt to 'yolov8n.pt'...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 6.23M/6.23M [00:00<00:00, 25.2MB/s]\n"
     ]
    },
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'default.jpg'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[2], line 14\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n\u001b[1;32m     12\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m image\u001b[38;5;241m.\u001b[39mstartswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttp\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m---> 14\u001b[0m     \u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mremove\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     16\u001b[0m \u001b[38;5;66;03m# perform inference\u001b[39;00m\n\u001b[1;32m     17\u001b[0m results \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mpredict(image, conf\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.25\u001b[39m, verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'default.jpg'"
     ]
    }
   ],
   "source": [
    "# load model\n",
    "model = YOLO('best.pt')\n",
    "# model = YOLO(\"nakamura196/yolov8s-layout-detection\")\n",
    "\n",
    "# set image\n",
    "image = \"https://dl.ndl.go.jp/api/iiif/1879314/R0000039/full/640,640/0/default.jpg\"\n",
    "\n",
    "filename = image.split(\"/\")[-1]\n",
    "\n",
    "import os\n",
    "\n",
    "if image.startswith(\"http\"):\n",
    "    if os.path.exists(filename):\n",
    "        os.remove(filename)\n",
    "\n",
    "# perform inference\n",
    "results = model.predict(image, conf=0.25, verbose=False)\n",
    "\n",
    "# observe results\n",
    "render = render_result(model=model, image=image, result=results[0])\n",
    "render.show()"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.11"
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 },
 "nbformat": 4,
 "nbformat_minor": 2
}