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    "## How tu use\n",
    "\n",
    "- Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus):\n",
    "\n",
    "```bash\n",
    "pip install -U ultralyticsplus\n",
    "```\n",
    "\n",
    "- Load model and perform prediction:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "\n",
      "Found https://dl.ndl.go.jp/api/iiif/2534020/T0000001/full/full/0/default.jpg locally at default.jpg\n",
      "image 1/1 /Users/nakamura/git/hf/models/yolov8-ndl-layout/default.jpg: 640x640 1 1_overall, 1 3_typography, 510.9ms\n",
      "Speed: 2.2ms preprocess, 510.9ms inference, 1.8ms postprocess per image at shape (1, 3, 640, 640)\n"
     ]
    }
   ],
   "source": [
    "from ultralyticsplus import YOLO, render_result\n",
    "import os\n",
    "\n",
    "# load model\n",
    "model = YOLO('model_- 19 may 2024 15_13.pt')\n",
    "  \n",
    "# set model parameters\n",
    "conf_threshold = 0.25  # NMS confidence threshold\n",
    "iou_threshold = 0.45  # NMS IoU threshold\n",
    "\n",
    "# set image\n",
    "img = 'https://dl.ndl.go.jp/api/iiif/2534020/T0000001/full/full/0/default.jpg'\n",
    "\n",
    "# perform inference\n",
    "results = model.predict(img, conf=conf_threshold, iou=iou_threshold)\n",
    "render = render_result(model=model, image=img, result=results[0])  \n",
    "\n",
    "os.makedirs('results', exist_ok=True)\n",
    "\n",
    "# save\n",
    "render.save('results/1.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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