{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9a67092a",
   "metadata": {},
   "source": [
    "# Training notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4dfbc71a-a78d-4ebb-ab77-276dab5821c9",
   "metadata": {},
   "source": [
    "## Please install the requirements\n",
    "(if you don't have them already)"
   ]
  },
  {
   "cell_type": "code",
   "id": "20c8a661575d1c6f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-02T16:26:49.490115Z",
     "start_time": "2025-04-02T16:26:45.344210Z"
    }
   },
   "source": [
    "%pip install torchvision\n",
    "%pip install torch torchvision\n",
    "%pip install --upgrade ultralytics\n",
    "%pip install pillow_heif\n",
    "%pip install plotly\n",
    "%pip install Pillow\n",
    "%pip install tqdm\n",
    "%pip install ruamel.yaml"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: torchvision in ./.venv/lib/python3.12/site-packages (0.21.0)\r\n",
      "Requirement already satisfied: numpy in ./.venv/lib/python3.12/site-packages (from torchvision) (2.1.1)\r\n",
      "Requirement already satisfied: torch==2.6.0 in ./.venv/lib/python3.12/site-packages (from torchvision) (2.6.0)\r\n",
      "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in ./.venv/lib/python3.12/site-packages (from torchvision) (11.1.0)\r\n",
      "Requirement already satisfied: filelock in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (3.18.0)\r\n",
      "Requirement already satisfied: typing-extensions>=4.10.0 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (4.13.0)\r\n",
      "Requirement already satisfied: networkx in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (3.4.2)\r\n",
      "Requirement already satisfied: jinja2 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (3.1.6)\r\n",
      "Requirement already satisfied: fsspec in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (2025.3.2)\r\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (9.1.0.70)\r\n",
      "Requirement already satisfied: nvidia-cublas-cu12==12.4.5.8 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (12.4.5.8)\r\n",
      "Requirement already satisfied: nvidia-cufft-cu12==11.2.1.3 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (11.2.1.3)\r\n",
      "Requirement already satisfied: nvidia-curand-cu12==10.3.5.147 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (10.3.5.147)\r\n",
      "Requirement already satisfied: nvidia-cusolver-cu12==11.6.1.9 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (11.6.1.9)\r\n",
      "Requirement already satisfied: nvidia-cusparse-cu12==12.3.1.170 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (12.3.1.170)\r\n",
      "Requirement already satisfied: nvidia-cusparselt-cu12==0.6.2 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (0.6.2)\r\n",
      "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (2.21.5)\r\n",
      "Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-nvjitlink-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (12.4.127)\r\n",
      "Requirement already satisfied: triton==3.2.0 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (3.2.0)\r\n",
      "Requirement already satisfied: setuptools in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (78.1.0)\r\n",
      "Requirement already satisfied: sympy==1.13.1 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0->torchvision) (1.13.1)\r\n",
      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in ./.venv/lib/python3.12/site-packages (from sympy==1.13.1->torch==2.6.0->torchvision) (1.3.0)\r\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in ./.venv/lib/python3.12/site-packages (from jinja2->torch==2.6.0->torchvision) (3.0.2)\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: torch in ./.venv/lib/python3.12/site-packages (2.6.0)\r\n",
      "Requirement already satisfied: torchvision in ./.venv/lib/python3.12/site-packages (0.21.0)\r\n",
      "Requirement already satisfied: filelock in ./.venv/lib/python3.12/site-packages (from torch) (3.18.0)\r\n",
      "Requirement already satisfied: typing-extensions>=4.10.0 in ./.venv/lib/python3.12/site-packages (from torch) (4.13.0)\r\n",
      "Requirement already satisfied: networkx in ./.venv/lib/python3.12/site-packages (from torch) (3.4.2)\r\n",
      "Requirement already satisfied: jinja2 in ./.venv/lib/python3.12/site-packages (from torch) (3.1.6)\r\n",
      "Requirement already satisfied: fsspec in ./.venv/lib/python3.12/site-packages (from torch) (2025.3.2)\r\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in ./.venv/lib/python3.12/site-packages (from torch) (9.1.0.70)\r\n",
      "Requirement already satisfied: nvidia-cublas-cu12==12.4.5.8 in ./.venv/lib/python3.12/site-packages (from torch) (12.4.5.8)\r\n",
      "Requirement already satisfied: nvidia-cufft-cu12==11.2.1.3 in ./.venv/lib/python3.12/site-packages (from torch) (11.2.1.3)\r\n",
      "Requirement already satisfied: nvidia-curand-cu12==10.3.5.147 in ./.venv/lib/python3.12/site-packages (from torch) (10.3.5.147)\r\n",
      "Requirement already satisfied: nvidia-cusolver-cu12==11.6.1.9 in ./.venv/lib/python3.12/site-packages (from torch) (11.6.1.9)\r\n",
      "Requirement already satisfied: nvidia-cusparse-cu12==12.3.1.170 in ./.venv/lib/python3.12/site-packages (from torch) (12.3.1.170)\r\n",
      "Requirement already satisfied: nvidia-cusparselt-cu12==0.6.2 in ./.venv/lib/python3.12/site-packages (from torch) (0.6.2)\r\n",
      "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in ./.venv/lib/python3.12/site-packages (from torch) (2.21.5)\r\n",
      "Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-nvjitlink-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch) (12.4.127)\r\n",
      "Requirement already satisfied: triton==3.2.0 in ./.venv/lib/python3.12/site-packages (from torch) (3.2.0)\r\n",
      "Requirement already satisfied: setuptools in ./.venv/lib/python3.12/site-packages (from torch) (78.1.0)\r\n",
      "Requirement already satisfied: sympy==1.13.1 in ./.venv/lib/python3.12/site-packages (from torch) (1.13.1)\r\n",
      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in ./.venv/lib/python3.12/site-packages (from sympy==1.13.1->torch) (1.3.0)\r\n",
      "Requirement already satisfied: numpy in ./.venv/lib/python3.12/site-packages (from torchvision) (2.1.1)\r\n",
      "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in ./.venv/lib/python3.12/site-packages (from torchvision) (11.1.0)\r\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in ./.venv/lib/python3.12/site-packages (from jinja2->torch) (3.0.2)\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: ultralytics in ./.venv/lib/python3.12/site-packages (8.3.100)\r\n",
      "Requirement already satisfied: numpy<=2.1.1,>=1.23.0 in ./.venv/lib/python3.12/site-packages (from ultralytics) (2.1.1)\r\n",
      "Requirement already satisfied: matplotlib>=3.3.0 in ./.venv/lib/python3.12/site-packages (from ultralytics) (3.10.1)\r\n",
      "Requirement already satisfied: opencv-python>=4.6.0 in ./.venv/lib/python3.12/site-packages (from ultralytics) (4.11.0.86)\r\n",
      "Requirement already satisfied: pillow>=7.1.2 in ./.venv/lib/python3.12/site-packages (from ultralytics) (11.1.0)\r\n",
      "Requirement already satisfied: pyyaml>=5.3.1 in ./.venv/lib/python3.12/site-packages (from ultralytics) (6.0.2)\r\n",
      "Requirement already satisfied: requests>=2.23.0 in ./.venv/lib/python3.12/site-packages (from ultralytics) (2.32.3)\r\n",
      "Requirement already satisfied: scipy>=1.4.1 in ./.venv/lib/python3.12/site-packages (from ultralytics) (1.15.2)\r\n",
      "Requirement already satisfied: torch>=1.8.0 in ./.venv/lib/python3.12/site-packages (from ultralytics) (2.6.0)\r\n",
      "Requirement already satisfied: torchvision>=0.9.0 in ./.venv/lib/python3.12/site-packages (from ultralytics) (0.21.0)\r\n",
      "Requirement already satisfied: tqdm>=4.64.0 in ./.venv/lib/python3.12/site-packages (from ultralytics) (4.67.1)\r\n",
      "Requirement already satisfied: psutil in ./.venv/lib/python3.12/site-packages (from ultralytics) (7.0.0)\r\n",
      "Requirement already satisfied: py-cpuinfo in ./.venv/lib/python3.12/site-packages (from ultralytics) (9.0.0)\r\n",
      "Requirement already satisfied: pandas>=1.1.4 in ./.venv/lib/python3.12/site-packages (from ultralytics) (2.2.3)\r\n",
      "Requirement already satisfied: seaborn>=0.11.0 in ./.venv/lib/python3.12/site-packages (from ultralytics) (0.13.2)\r\n",
      "Requirement already satisfied: ultralytics-thop>=2.0.0 in ./.venv/lib/python3.12/site-packages (from ultralytics) (2.0.14)\r\n",
      "Requirement already satisfied: contourpy>=1.0.1 in ./.venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics) (1.3.1)\r\n",
      "Requirement already satisfied: cycler>=0.10 in ./.venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics) (0.12.1)\r\n",
      "Requirement already satisfied: fonttools>=4.22.0 in ./.venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics) (4.56.0)\r\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in ./.venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics) (1.4.8)\r\n",
      "Requirement already satisfied: packaging>=20.0 in ./.venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics) (24.2)\r\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in ./.venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics) (3.2.3)\r\n",
      "Requirement already satisfied: python-dateutil>=2.7 in ./.venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics) (2.9.0.post0)\r\n",
      "Requirement already satisfied: pytz>=2020.1 in ./.venv/lib/python3.12/site-packages (from pandas>=1.1.4->ultralytics) (2025.2)\r\n",
      "Requirement already satisfied: tzdata>=2022.7 in ./.venv/lib/python3.12/site-packages (from pandas>=1.1.4->ultralytics) (2025.2)\r\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in ./.venv/lib/python3.12/site-packages (from requests>=2.23.0->ultralytics) (3.4.1)\r\n",
      "Requirement already satisfied: idna<4,>=2.5 in ./.venv/lib/python3.12/site-packages (from requests>=2.23.0->ultralytics) (3.10)\r\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in ./.venv/lib/python3.12/site-packages (from requests>=2.23.0->ultralytics) (2.3.0)\r\n",
      "Requirement already satisfied: certifi>=2017.4.17 in ./.venv/lib/python3.12/site-packages (from requests>=2.23.0->ultralytics) (2025.1.31)\r\n",
      "Requirement already satisfied: filelock in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (3.18.0)\r\n",
      "Requirement already satisfied: typing-extensions>=4.10.0 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (4.13.0)\r\n",
      "Requirement already satisfied: networkx in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (3.4.2)\r\n",
      "Requirement already satisfied: jinja2 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (3.1.6)\r\n",
      "Requirement already satisfied: fsspec in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (2025.3.2)\r\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (9.1.0.70)\r\n",
      "Requirement already satisfied: nvidia-cublas-cu12==12.4.5.8 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (12.4.5.8)\r\n",
      "Requirement already satisfied: nvidia-cufft-cu12==11.2.1.3 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (11.2.1.3)\r\n",
      "Requirement already satisfied: nvidia-curand-cu12==10.3.5.147 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (10.3.5.147)\r\n",
      "Requirement already satisfied: nvidia-cusolver-cu12==11.6.1.9 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (11.6.1.9)\r\n",
      "Requirement already satisfied: nvidia-cusparse-cu12==12.3.1.170 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (12.3.1.170)\r\n",
      "Requirement already satisfied: nvidia-cusparselt-cu12==0.6.2 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (0.6.2)\r\n",
      "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (2.21.5)\r\n",
      "Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (12.4.127)\r\n",
      "Requirement already satisfied: nvidia-nvjitlink-cu12==12.4.127 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (12.4.127)\r\n",
      "Requirement already satisfied: triton==3.2.0 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (3.2.0)\r\n",
      "Requirement already satisfied: setuptools in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (78.1.0)\r\n",
      "Requirement already satisfied: sympy==1.13.1 in ./.venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics) (1.13.1)\r\n",
      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in ./.venv/lib/python3.12/site-packages (from sympy==1.13.1->torch>=1.8.0->ultralytics) (1.3.0)\r\n",
      "Requirement already satisfied: six>=1.5 in ./.venv/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib>=3.3.0->ultralytics) (1.17.0)\r\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in ./.venv/lib/python3.12/site-packages (from jinja2->torch>=1.8.0->ultralytics) (3.0.2)\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: pillow_heif in ./.venv/lib/python3.12/site-packages (0.22.0)\r\n",
      "Requirement already satisfied: pillow>=10.1.0 in ./.venv/lib/python3.12/site-packages (from pillow_heif) (11.1.0)\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: plotly in ./.venv/lib/python3.12/site-packages (6.0.1)\r\n",
      "Requirement already satisfied: narwhals>=1.15.1 in ./.venv/lib/python3.12/site-packages (from plotly) (1.33.0)\r\n",
      "Requirement already satisfied: packaging in ./.venv/lib/python3.12/site-packages (from plotly) (24.2)\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: Pillow in ./.venv/lib/python3.12/site-packages (11.1.0)\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: tqdm in ./.venv/lib/python3.12/site-packages (4.67.1)\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: ruamel.yaml in ./.venv/lib/python3.12/site-packages (0.18.10)\r\n",
      "Requirement already satisfied: ruamel.yaml.clib>=0.2.7 in ./.venv/lib/python3.12/site-packages (from ruamel.yaml) (0.2.12)\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "execution_count": 19
  },
  {
   "cell_type": "code",
   "id": "45105e3c6e3463b4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-02T18:26:14.551559Z",
     "start_time": "2025-04-02T18:26:13.920851Z"
    }
   },
   "source": [
    "import os  # for file operations\n",
    "import json  # for loading the annotations file\n",
    "from PIL import Image, ImageDraw, ImageOps, ImageEnhance  # for processing the image data\n",
    "import numpy as np\n",
    "from random import shuffle\n",
    "import nvidia.cudnn\n",
    "import torch\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"1\""
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "id": "a9af0815fbb0b5f3",
   "metadata": {},
   "source": [
    "## Constants"
   ]
  },
  {
   "cell_type": "code",
   "id": "3af63db86b518835",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-02T18:28:34.762905Z",
     "start_time": "2025-04-02T18:28:34.760736Z"
    }
   },
   "source": [
    "DATA_PATH = \"./data/\"\n",
    "\n",
    "BATCH_SIZE = 8"
   ],
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## Training",
   "id": "4fbd4c7fafc63aff"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "Check if CUDA is available.",
   "id": "90dfc588a28e5f8f"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-02T18:22:59.808820Z",
     "start_time": "2025-04-02T18:22:59.805682Z"
    }
   },
   "cell_type": "code",
   "source": "torch.__version__",
   "id": "ce87239d4cbc1fa4",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.5.1'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-02T18:23:00.257484Z",
     "start_time": "2025-04-02T18:23:00.234930Z"
    }
   },
   "cell_type": "code",
   "source": "torch.cuda.is_available()",
   "id": "339df0da0ce8cd55",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-02T18:23:00.745613Z",
     "start_time": "2025-04-02T18:23:00.743832Z"
    }
   },
   "cell_type": "code",
   "source": "print(torch.version.cuda)",
   "id": "7034c3a061d9666d",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11.8\n"
     ]
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-02T19:22:10.013376Z",
     "start_time": "2025-04-02T18:47:55.735412Z"
    }
   },
   "cell_type": "code",
   "source": [
    "YOLO_CONFIG_PATH = \"yolo.yaml\"\n",
    "\n",
    "from ultralytics import YOLO\n",
    "\n",
    "model = YOLO(\"yolov8s.pt\")\n",
    "\n",
    "results = model.train(data=YOLO_CONFIG_PATH, epochs=144, verbose=True, imgsz=640, workers=4)"
   ],
   "id": "65fa97a1ae1c78f2",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ultralytics 8.3.100 🚀 Python-3.12.3 torch-2.5.1 CUDA:0 (NVIDIA GeForce RTX 3060 Ti, 7958MiB)\n",
      "\u001B[34m\u001B[1mengine/trainer: \u001B[0mtask=detect, mode=train, model=yolov8s.pt, data=yolo.yaml, epochs=144, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=4, project=None, name=train24, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, multi_scale=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=True, opset=None, workspace=None, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, copy_paste_mode=flip, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=/home/vlad/recycle4me/runs/detect/train24\n",
      "Overriding model.yaml nc=80 with nc=7\n",
      "\n",
      "                   from  n    params  module                                       arguments                     \n",
      "  0                  -1  1       928  ultralytics.nn.modules.conv.Conv             [3, 32, 3, 2]                 \n",
      "  1                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]                \n",
      "  2                  -1  1     29056  ultralytics.nn.modules.block.C2f             [64, 64, 1, True]             \n",
      "  3                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]               \n",
      "  4                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]           \n",
      "  5                  -1  1    295424  ultralytics.nn.modules.conv.Conv             [128, 256, 3, 2]              \n",
      "  6                  -1  2    788480  ultralytics.nn.modules.block.C2f             [256, 256, 2, True]           \n",
      "  7                  -1  1   1180672  ultralytics.nn.modules.conv.Conv             [256, 512, 3, 2]              \n",
      "  8                  -1  1   1838080  ultralytics.nn.modules.block.C2f             [512, 512, 1, True]           \n",
      "  9                  -1  1    656896  ultralytics.nn.modules.block.SPPF            [512, 512, 5]                 \n",
      " 10                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 11             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 12                  -1  1    591360  ultralytics.nn.modules.block.C2f             [768, 256, 1]                 \n",
      " 13                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 14             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 15                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]                 \n",
      " 16                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]              \n",
      " 17            [-1, 12]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 18                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]                 \n",
      " 19                  -1  1    590336  ultralytics.nn.modules.conv.Conv             [256, 256, 3, 2]              \n",
      " 20             [-1, 9]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 21                  -1  1   1969152  ultralytics.nn.modules.block.C2f             [768, 512, 1]                 \n",
      " 22        [15, 18, 21]  1   2118757  ultralytics.nn.modules.head.Detect           [7, [128, 256, 512]]          \n",
      "Model summary: 129 layers, 11,138,309 parameters, 11,138,293 gradients\n",
      "\n",
      "Transferred 349/355 items from pretrained weights\n",
      "Freezing layer 'model.22.dfl.conv.weight'\n",
      "\u001B[34m\u001B[1mAMP: \u001B[0mrunning Automatic Mixed Precision (AMP) checks...\n",
      "\u001B[34m\u001B[1mAMP: \u001B[0mchecks passed ✅\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001B[34m\u001B[1mtrain: \u001B[0mScanning /home/vlad/recycle4me/data.cache... 1473 images, 9 backgrounds, 1 corrupt: 100%|██████████| 1473/1473 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001B[34m\u001B[1mtrain: \u001B[0mWARNING ⚠️ /home/vlad/recycle4me/data/1089.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0551]\n",
      "\u001B[34m\u001B[1mtrain: \u001B[0mWARNING ⚠️ /home/vlad/recycle4me/data/1106.jpg: 1 duplicate labels removed\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "\u001B[34m\u001B[1mval: \u001B[0mScanning /home/vlad/recycle4me/val_data.cache... 16 images, 0 backgrounds, 0 corrupt: 100%|██████████| 16/16 [00:00<?, ?it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting labels to /home/vlad/recycle4me/runs/detect/train24/labels.jpg... \n",
      "\u001B[34m\u001B[1moptimizer:\u001B[0m 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n",
      "\u001B[34m\u001B[1moptimizer:\u001B[0m AdamW(lr=0.000909, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n",
      "Image sizes 640 train, 640 val\n",
      "Using 4 dataloader workers\n",
      "Logging results to \u001B[1m/home/vlad/recycle4me/runs/detect/train24\u001B[0m\n",
      "Starting training for 144 epochs...\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      1/144      3.56G      0.977       3.09      1.391         42        640: 100%|██████████| 92/92 [00:14<00:00,  6.43it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 13.73it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.225      0.409      0.316       0.21\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      2/144      3.73G      1.015      1.977      1.397         35        640: 100%|██████████| 92/92 [00:14<00:00,  6.49it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 12.56it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.368      0.236      0.241       0.12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      3/144      3.74G        1.1      2.021      1.473         57        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.36it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.696        0.2      0.157      0.113\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      4/144      3.74G      1.143      2.089      1.482         45        640: 100%|██████████| 92/92 [00:14<00:00,  6.31it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 10.22it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.845        0.3      0.405      0.261\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      5/144      3.74G      1.126      1.962      1.468         35        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 13.15it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.354      0.328      0.246      0.105\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      6/144      3.74G      1.063      1.858       1.43         39        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 12.24it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.57      0.175      0.149      0.114\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      7/144      3.74G      1.054      1.836      1.431         32        640: 100%|██████████| 92/92 [00:14<00:00,  6.54it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 13.70it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.812      0.416       0.49      0.286\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      8/144      3.74G      1.048      1.822      1.421         41        640: 100%|██████████| 92/92 [00:14<00:00,  6.53it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 13.31it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.752      0.525      0.502      0.278\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      9/144      3.74G     0.9926       1.74      1.403         32        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.80it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.523      0.354      0.385      0.245\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     10/144      3.74G     0.9892      1.661      1.388         39        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.68it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.759      0.444      0.419      0.314\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     11/144      3.74G     0.9407      1.628      1.362         47        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.52it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.747      0.446      0.488      0.228\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     12/144      3.74G     0.9775      1.624      1.383         40        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.02it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.602       0.35      0.296      0.207\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     13/144      3.74G     0.9265       1.56      1.348         41        640: 100%|██████████| 92/92 [00:14<00:00,  6.43it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.41it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.956      0.271      0.448       0.32\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     14/144      3.74G     0.9416      1.616      1.357         47        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.58it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.584       0.52      0.567       0.37\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     15/144      3.74G     0.9123      1.549      1.338         34        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.33it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.855      0.275      0.419      0.289\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     16/144      3.74G     0.8814      1.481      1.322         45        640: 100%|██████████| 92/92 [00:13<00:00,  6.61it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.32it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.399      0.475      0.352      0.233\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     17/144      3.74G     0.8867      1.467      1.305         48        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.39it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.792       0.35      0.432      0.244\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     18/144      3.74G      0.883      1.441      1.303         35        640: 100%|██████████| 92/92 [00:13<00:00,  6.61it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.78it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.727       0.55      0.608      0.452\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     19/144      3.74G     0.8745      1.416      1.286         39        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.64it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.765      0.447      0.465      0.343\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     20/144      3.74G     0.8956      1.419       1.31         29        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.70it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.866      0.425      0.563      0.423\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     21/144      3.74G     0.8334      1.347      1.282         41        640: 100%|██████████| 92/92 [00:13<00:00,  6.61it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.42it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.71      0.429      0.567      0.366\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     22/144      3.74G     0.8699      1.393      1.287         44        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.45it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.659       0.43      0.634      0.444\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     23/144      3.74G     0.8474      1.367      1.284         30        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.25it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.811      0.562      0.635      0.446\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     24/144      3.74G     0.8347      1.284      1.281         44        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.19it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.654      0.525      0.613      0.396\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     25/144      3.74G     0.8146      1.272      1.251         45        640: 100%|██████████| 92/92 [00:13<00:00,  6.61it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.37it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.79      0.575      0.816      0.505\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     26/144      3.74G     0.8154      1.299      1.257         35        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.69it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.551      0.475      0.623      0.493\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     27/144      3.74G     0.8188      1.254      1.266         45        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.37it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.682      0.525      0.494      0.387\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     28/144      3.74G     0.7758      1.217      1.236         52        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.53it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.789        0.3      0.403      0.307\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     29/144      3.74G     0.7962      1.167      1.237         35        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.48it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.797      0.507      0.544      0.409\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     30/144      3.74G     0.8094      1.211      1.251         46        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.14it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.917      0.431      0.632      0.456\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     31/144      3.74G     0.7602       1.18      1.215         43        640: 100%|██████████| 92/92 [00:13<00:00,  6.60it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.76it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.517      0.596      0.642      0.503\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     32/144      3.74G     0.7699      1.162      1.229         43        640: 100%|██████████| 92/92 [00:13<00:00,  6.59it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.03it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.811      0.559      0.661      0.461\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     33/144      3.74G     0.7568      1.111      1.214         50        640: 100%|██████████| 92/92 [00:13<00:00,  6.59it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 13.29it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.489      0.525      0.636      0.449\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     34/144      3.74G     0.7486      1.103       1.21         47        640: 100%|██████████| 92/92 [00:13<00:00,  6.61it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.66it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.686      0.425      0.623      0.453\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     35/144      3.74G     0.7492      1.028      1.207         41        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.96it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.813        0.6       0.87      0.596\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     36/144      3.74G     0.7326      1.063      1.206         31        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.92it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.842      0.557      0.699      0.475\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     37/144      3.74G     0.7523      1.048      1.209         39        640: 100%|██████████| 92/92 [00:13<00:00,  6.59it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.02it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.645      0.566      0.694      0.476\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     38/144      3.74G     0.7372      1.036      1.202         42        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 13.68it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.487       0.83      0.566      0.383\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     39/144      3.74G     0.7475      1.028        1.2         39        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.78it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.667      0.522       0.63      0.459\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     40/144      3.74G     0.7343      1.014      1.204         85        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.40it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.803      0.601      0.715      0.543\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     41/144      3.74G      0.731     0.9961      1.186         87        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.05it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.531      0.817      0.756        0.6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     42/144      3.74G      0.735     0.9889       1.19         32        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.02it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.528      0.517      0.676      0.508\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     43/144      3.74G     0.7062     0.9738      1.184         55        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.35it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.903       0.45      0.657      0.529\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     44/144      3.74G     0.7364     0.9856      1.195         55        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.08it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.511        0.8      0.714      0.536\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     45/144      3.74G      0.707     0.9681      1.177         44        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.85it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.786      0.595       0.73      0.572\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     46/144      3.74G     0.7245     0.9194      1.186         44        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.70it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.46      0.909      0.742      0.577\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     47/144      3.74G     0.7056     0.9107      1.178         42        640: 100%|██████████| 92/92 [00:13<00:00,  6.59it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 13.87it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.615       0.55      0.656      0.511\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     48/144      3.74G     0.6889     0.9045      1.172         42        640: 100%|██████████| 92/92 [00:13<00:00,  6.59it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.11it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.523        0.8      0.792      0.567\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     49/144      3.74G     0.7037     0.9346      1.182         42        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.18it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.591      0.578      0.698      0.529\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     50/144      3.74G     0.6742     0.8669       1.15         37        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.71it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.487      0.851      0.679      0.511\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     51/144      3.74G     0.6842     0.8637      1.166         60        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.79it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.688      0.645      0.873      0.571\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     52/144      3.74G     0.6908     0.8534      1.161         47        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.70it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.78      0.446      0.696      0.495\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     53/144      3.74G     0.6793     0.8415      1.156         41        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.93it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.688      0.522      0.688      0.563\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     54/144      3.74G     0.6698     0.8511       1.17         37        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.46it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.567      0.889      0.801      0.605\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     55/144      3.74G      0.683     0.8571      1.158         58        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.25it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.417      0.775      0.628      0.507\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     56/144      3.74G     0.6493     0.8258      1.143         36        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.24it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.618      0.675      0.776      0.482\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     57/144      3.74G     0.6431     0.7907      1.141         59        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.71it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.509      0.887      0.789      0.598\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     58/144      3.74G     0.6742     0.8043      1.154         49        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.38it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.583      0.822      0.731      0.517\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     59/144      3.74G     0.6584     0.7954      1.146         45        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.23it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.485       0.77       0.66       0.49\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     60/144      3.74G     0.6506     0.7773      1.139         42        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.36it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.776      0.545      0.669      0.495\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     61/144      3.74G     0.6303     0.7519      1.133         35        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.40it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.559       0.85       0.78      0.582\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     62/144      3.74G     0.6386     0.7718      1.139         55        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.01it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.688      0.868      0.905      0.588\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     63/144      3.74G     0.6419     0.7526      1.129         44        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.69it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.805      0.632       0.88      0.599\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     64/144      3.74G     0.6588     0.7666      1.139         79        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.92it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.566      0.615      0.656      0.536\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     65/144      3.74G     0.6492      0.744      1.131         40        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.42it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.607      0.669      0.665      0.511\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     66/144      3.74G     0.6421     0.7682      1.124         48        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.69it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.819      0.483      0.723      0.581\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     67/144      3.74G     0.6392     0.7352      1.136         45        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.11it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.504        0.7       0.73      0.534\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     68/144      3.74G     0.6356     0.7302       1.13         49        640: 100%|██████████| 92/92 [00:13<00:00,  6.59it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.94it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.783      0.551      0.671      0.497\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     69/144      3.74G     0.6329     0.7131      1.123         35        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.67it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.547      0.825      0.736      0.521\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     70/144      3.74G     0.6108     0.6845      1.118         54        640: 100%|██████████| 92/92 [00:14<00:00,  6.53it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.97it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.869      0.528      0.738      0.616\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     71/144      3.74G     0.6126     0.6833      1.107         40        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.98it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.816      0.748      0.852      0.661\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     72/144      3.74G     0.6078      0.691       1.11         51        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.06it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.757      0.581      0.694      0.587\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     73/144      3.74G     0.6105     0.6695      1.103         34        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.30it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.486        0.9      0.852      0.635\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     74/144      3.74G     0.6033     0.6805      1.111         32        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.55it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.597      0.758      0.699      0.577\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     75/144      3.74G     0.6027     0.6876      1.111         35        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.68it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.58      0.866      0.714      0.573\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     76/144      3.74G     0.6058     0.6325      1.093         38        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.20it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.493       0.87      0.712      0.555\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     77/144      3.74G     0.5834     0.6308      1.089         35        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.39it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.581       0.75      0.643      0.508\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     78/144      3.74G     0.5812     0.6661      1.093         68        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.70it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.588      0.821      0.748        0.6\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     79/144      3.74G     0.5909      0.639      1.094         43        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.86it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.657       0.75      0.847      0.587\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     80/144      3.74G     0.5904     0.6375      1.104         37        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.27it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.492       0.82      0.694      0.523\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     81/144      3.74G     0.5702     0.6327      1.087         35        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.76it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.568      0.727      0.675      0.509\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     82/144      3.74G     0.5842     0.6171      1.097         79        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.18it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.565       0.75      0.733      0.599\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     83/144      3.74G     0.5922     0.6329        1.1         40        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.46it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.603      0.744      0.708      0.549\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     84/144      3.74G     0.5711      0.607      1.084         38        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.70it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.53      0.775        0.7       0.57\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     85/144      3.74G     0.5661     0.6085      1.086         55        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.67it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.588      0.824       0.76      0.592\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     86/144      3.74G     0.5956     0.5995      1.106         41        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.03it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.534       0.82      0.733       0.63\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     87/144      3.74G     0.5717     0.5821       1.08         73        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.91it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.632      0.766      0.715      0.602\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     88/144      3.74G     0.5786     0.5909      1.092         34        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.31it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.637       0.79      0.755      0.588\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     89/144      3.74G     0.5656     0.5949      1.082         43        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.76it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.63      0.799      0.771      0.603\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     90/144      3.74G      0.555     0.5685      1.078         49        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.83it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.582      0.825      0.763      0.592\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     91/144      3.74G     0.5663     0.5725      1.075         40        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.37it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.816      0.786      0.877      0.661\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     92/144      3.74G     0.5585     0.5789      1.085         62        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.55it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.624      0.925       0.89      0.665\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     93/144      3.74G     0.5583     0.5779      1.078         76        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.30it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.629      0.874      0.876      0.684\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     94/144      3.74G     0.5471     0.5667      1.064         53        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.42it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.73      0.832      0.877       0.62\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     95/144      3.74G     0.5519     0.5734      1.078         49        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.71it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.765       0.69       0.78      0.599\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     96/144      3.74G     0.5383     0.5508      1.061         53        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.88it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.768      0.834      0.889      0.614\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     97/144      3.74G     0.5434     0.5465       1.08         47        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.58it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.512      0.811      0.728      0.588\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     98/144      3.74G     0.5414     0.5523      1.067         43        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.54it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.551      0.867      0.739      0.524\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "     99/144      3.74G      0.527     0.5288      1.053         35        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.67it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.491      0.674      0.713      0.566\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    100/144      3.74G     0.5545     0.5385       1.06         36        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.70it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.535      0.806      0.728      0.584\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    101/144      3.74G     0.5307     0.5196      1.059         37        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.82it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.552      0.841      0.742      0.541\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    102/144      3.74G     0.5474     0.5413      1.074         47        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.60it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.466      0.749      0.692      0.529\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    103/144      3.74G     0.5337     0.5218      1.056         54        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.32it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.53       0.85      0.702      0.538\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    104/144      3.74G     0.5359     0.5297      1.061         45        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.30it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.561      0.859      0.749      0.536\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    105/144      3.74G      0.524     0.5265      1.059         41        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.46it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.677      0.809      0.777      0.624\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    106/144      3.74G     0.5169     0.5138      1.047         49        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.15it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.632      0.679      0.769      0.582\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    107/144      3.74G     0.5205     0.5043      1.049         44        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.90it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.572      0.874      0.775      0.578\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    108/144      3.74G     0.5185     0.5038      1.049         47        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.04it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.639      0.846      0.774      0.604\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    109/144      3.74G      0.528     0.5084       1.05         41        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.52it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.826        0.6      0.706      0.571\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    110/144      3.74G     0.5088     0.4835      1.045         38        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.83it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.701      0.809      0.772      0.595\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    111/144      3.74G     0.4956     0.4908      1.047         41        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.03it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.651       0.87      0.794      0.597\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    112/144      3.74G     0.5159     0.4858      1.044         42        640: 100%|██████████| 92/92 [00:14<00:00,  6.51it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.95it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.496      0.899      0.746      0.576\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    113/144      3.74G     0.5087      0.495      1.049         38        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.66it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.56       0.87      0.786       0.57\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    114/144      3.74G     0.5035     0.4812      1.039         44        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.20it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.565      0.905      0.773      0.564\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    115/144      3.74G     0.5138     0.4921      1.048         53        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.32it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.548      0.878      0.776      0.601\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    116/144      3.74G        0.5     0.4744      1.035         37        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.39it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.557      0.876      0.744       0.59\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    117/144      3.74G     0.4894     0.4628      1.037         39        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.56it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.882      0.649      0.789      0.605\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    118/144      3.74G     0.5012      0.466       1.04         41        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.64it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.578      0.884      0.775      0.617\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    119/144      3.74G     0.4894     0.4626      1.044         37        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.48it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.665       0.62      0.749      0.635\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    120/144      3.74G     0.4873     0.4373       1.04         55        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.81it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.599      0.923      0.785      0.644\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    121/144      3.74G     0.4934      0.451      1.038         40        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.37it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.623      0.827      0.781      0.659\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    122/144      3.74G     0.4805     0.4562      1.029         39        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.76it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.585      0.883      0.756      0.572\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    123/144      3.74G     0.4709     0.4503      1.023         30        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.94it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.631      0.851      0.772      0.628\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    124/144      3.74G     0.4795     0.4509      1.028         32        640: 100%|██████████| 92/92 [00:14<00:00,  6.54it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.38it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.639      0.753      0.741      0.618\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    125/144      3.74G     0.4888     0.4518      1.041         37        640: 100%|██████████| 92/92 [00:14<00:00,  6.52it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.44it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.644       0.67      0.749      0.597\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    126/144      3.74G     0.4796     0.4467      1.035         38        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.00it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.857      0.587      0.741      0.577\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    127/144      3.74G     0.4756     0.4568      1.035         39        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.40it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.572      0.903       0.78      0.596\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    128/144      3.74G     0.4771     0.4303      1.029         45        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.98it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.598      0.585      0.731      0.571\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    129/144      3.74G     0.4757     0.4371      1.041         31        640: 100%|██████████| 92/92 [00:13<00:00,  6.58it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.98it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.85      0.568      0.737      0.584\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    130/144      3.74G     0.4731     0.4505      1.029         55        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.83it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.604      0.806      0.752      0.582\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    131/144      3.74G     0.4722     0.4339      1.022         46        640: 100%|██████████| 92/92 [00:14<00:00,  6.54it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.06it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.656      0.778      0.745      0.587\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    132/144      3.74G     0.4679      0.423      1.027         35        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.40it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.632       0.84      0.864       0.65\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    133/144      3.74G     0.4642     0.4215      1.028         54        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.04it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.782      0.756      0.884      0.664\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    134/144      3.74G     0.4458     0.4025      1.013         61        640: 100%|██████████| 92/92 [00:14<00:00,  6.54it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.79it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.656      0.798      0.758      0.614\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Closing dataloader mosaic\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    135/144      3.74G     0.3361      0.286     0.9135         21        640: 100%|██████████| 92/92 [00:14<00:00,  6.44it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.16it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.728      0.787      0.755      0.583\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    136/144      3.74G     0.3241     0.2618     0.9108         17        640: 100%|██████████| 92/92 [00:14<00:00,  6.55it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.40it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.718      0.791       0.74      0.594\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    137/144      3.74G     0.3184     0.2541     0.9052         20        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.30it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.697      0.777       0.73       0.59\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    138/144      3.74G     0.3209     0.2561     0.9102         17        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.34it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.672      0.801      0.752      0.577\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    139/144      3.74G     0.3177     0.2471     0.9046         24        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.02it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.734       0.79      0.778      0.613\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    140/144      3.74G     0.3109     0.2451     0.9025         67        640: 100%|██████████| 92/92 [00:13<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.60it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.733      0.792      0.766      0.605\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    141/144      3.74G     0.3114     0.2443     0.9117         19        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.07it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.733      0.822      0.783      0.639\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    142/144      3.74G     0.3051     0.2365      0.894         22        640: 100%|██████████| 92/92 [00:14<00:00,  6.57it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.39it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.706      0.828      0.777      0.612\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "    143/144      3.74G     0.3036     0.2337     0.9016         16        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.33it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.747      0.818      0.868      0.679\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "    144/144      3.74G     0.2987     0.2318     0.8952         30        640: 100%|██████████| 92/92 [00:14<00:00,  6.56it/s]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 14.93it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18       0.76      0.817      0.851      0.669\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "144 epochs completed in 0.569 hours.\n",
      "Optimizer stripped from /home/vlad/recycle4me/runs/detect/train24/weights/last.pt, 22.5MB\n",
      "Optimizer stripped from /home/vlad/recycle4me/runs/detect/train24/weights/best.pt, 22.5MB\n",
      "\n",
      "Validating /home/vlad/recycle4me/runs/detect/train24/weights/best.pt...\n",
      "Ultralytics 8.3.100 🚀 Python-3.12.3 torch-2.5.1 CUDA:0 (NVIDIA GeForce RTX 3060 Ti, 7958MiB)\n",
      "Model summary (fused): 72 layers, 11,128,293 parameters, 0 gradients\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 13.37it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all         16         18      0.629      0.875      0.876      0.684\n",
      "               plastic          7          8       0.41      0.625      0.627       0.41\n",
      "                 glass          1          1      0.488          1      0.995      0.697\n",
      "                 metal          4          4      0.829       0.75      0.768      0.768\n",
      "               organic          1          1      0.418          1      0.995      0.895\n",
      "                 other          3          4          1      0.999      0.995      0.647\n",
      "Speed: 0.3ms preprocess, 3.4ms inference, 0.0ms loss, 0.2ms postprocess per image\n",
      "Results saved to \u001B[1m/home/vlad/recycle4me/runs/detect/train24\u001B[0m\n"
     ]
    }
   ],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-26T20:32:23.797810Z",
     "start_time": "2024-05-26T20:32:23.797762Z"
    }
   },
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "torch.save(model.state_dict(), \"yolov8n.pt\")",
   "id": "138880b6a127671a"
  },
  {
   "cell_type": "markdown",
   "id": "f7f1d169ae7634d5",
   "metadata": {},
   "source": [
    "## Inferencing\n",
    "Retrieve the class mapping that was discovered earlier and used in training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "78e0a2a59ce4f120",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-27T12:02:53.498360Z",
     "start_time": "2024-05-27T12:02:53.485443Z"
    }
   },
   "outputs": [],
   "source": [
    "# Get the class mapping\n",
    "from ruamel.yaml import YAML\n",
    "\n",
    "yaml = YAML()\n",
    "\n",
    "with open(\"yolo.yaml\", \"r\") as file:\n",
    "    data = yaml.load(file)\n",
    "    class_mapping = data[\"names\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "465e92c274b08cca",
   "metadata": {},
   "source": [
    "### With live webcam feed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cf66bcb81e1b29f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-26T16:53:48.532397Z",
     "start_time": "2024-05-26T16:50:58.288905Z"
    }
   },
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mKeyboardInterrupt\u001B[0m                         Traceback (most recent call last)",
      "Cell \u001B[0;32mIn[20], line 28\u001B[0m\n\u001B[1;32m     25\u001B[0m success, img \u001B[38;5;241m=\u001B[39m cap\u001B[38;5;241m.\u001B[39mread()\n\u001B[1;32m     26\u001B[0m results \u001B[38;5;241m=\u001B[39m model(img, stream\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mTrue\u001B[39;00m, verbose\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mFalse\u001B[39;00m)\n\u001B[0;32m---> 28\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m r \u001B[38;5;129;01min\u001B[39;00m results:\n\u001B[1;32m     29\u001B[0m     boxes \u001B[38;5;241m=\u001B[39m r\u001B[38;5;241m.\u001B[39mboxes\n\u001B[1;32m     31\u001B[0m     \u001B[38;5;28;01mfor\u001B[39;00m box \u001B[38;5;129;01min\u001B[39;00m boxes:\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/torch/utils/_contextlib.py:35\u001B[0m, in \u001B[0;36m_wrap_generator.<locals>.generator_context\u001B[0;34m(*args, **kwargs)\u001B[0m\n\u001B[1;32m     32\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m     33\u001B[0m     \u001B[38;5;66;03m# Issuing `None` to a generator fires it up\u001B[39;00m\n\u001B[1;32m     34\u001B[0m     \u001B[38;5;28;01mwith\u001B[39;00m ctx_factory():\n\u001B[0;32m---> 35\u001B[0m         response \u001B[38;5;241m=\u001B[39m \u001B[43mgen\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msend\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;28;43;01mNone\u001B[39;49;00m\u001B[43m)\u001B[49m\n\u001B[1;32m     37\u001B[0m     \u001B[38;5;28;01mwhile\u001B[39;00m \u001B[38;5;28;01mTrue\u001B[39;00m:\n\u001B[1;32m     38\u001B[0m         \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m     39\u001B[0m             \u001B[38;5;66;03m# Forward the response to our caller and get its next request\u001B[39;00m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/ultralytics/engine/predictor.py:248\u001B[0m, in \u001B[0;36mBasePredictor.stream_inference\u001B[0;34m(self, source, model, *args, **kwargs)\u001B[0m\n\u001B[1;32m    246\u001B[0m \u001B[38;5;66;03m# Inference\u001B[39;00m\n\u001B[1;32m    247\u001B[0m \u001B[38;5;28;01mwith\u001B[39;00m profilers[\u001B[38;5;241m1\u001B[39m]:\n\u001B[0;32m--> 248\u001B[0m     preds \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43minference\u001B[49m\u001B[43m(\u001B[49m\u001B[43mim\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m    249\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39margs\u001B[38;5;241m.\u001B[39membed:\n\u001B[1;32m    250\u001B[0m         \u001B[38;5;28;01myield from\u001B[39;00m [preds] \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(preds, torch\u001B[38;5;241m.\u001B[39mTensor) \u001B[38;5;28;01melse\u001B[39;00m preds  \u001B[38;5;66;03m# yield embedding tensors\u001B[39;00m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/ultralytics/engine/predictor.py:142\u001B[0m, in \u001B[0;36mBasePredictor.inference\u001B[0;34m(self, im, *args, **kwargs)\u001B[0m\n\u001B[1;32m    136\u001B[0m \u001B[38;5;250m\u001B[39m\u001B[38;5;124;03m\"\"\"Runs inference on a given image using the specified model and arguments.\"\"\"\u001B[39;00m\n\u001B[1;32m    137\u001B[0m visualize \u001B[38;5;241m=\u001B[39m (\n\u001B[1;32m    138\u001B[0m     increment_path(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39msave_dir \u001B[38;5;241m/\u001B[39m Path(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mbatch[\u001B[38;5;241m0\u001B[39m][\u001B[38;5;241m0\u001B[39m])\u001B[38;5;241m.\u001B[39mstem, mkdir\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mTrue\u001B[39;00m)\n\u001B[1;32m    139\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39margs\u001B[38;5;241m.\u001B[39mvisualize \u001B[38;5;129;01mand\u001B[39;00m (\u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39msource_type\u001B[38;5;241m.\u001B[39mtensor)\n\u001B[1;32m    140\u001B[0m     \u001B[38;5;28;01melse\u001B[39;00m \u001B[38;5;28;01mFalse\u001B[39;00m\n\u001B[1;32m    141\u001B[0m )\n\u001B[0;32m--> 142\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mmodel\u001B[49m\u001B[43m(\u001B[49m\u001B[43mim\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43maugment\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43margs\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43maugment\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mvisualize\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mvisualize\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43membed\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43margs\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43membed\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/torch/nn/modules/module.py:1532\u001B[0m, in \u001B[0;36mModule._wrapped_call_impl\u001B[0;34m(self, *args, **kwargs)\u001B[0m\n\u001B[1;32m   1530\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_compiled_call_impl(\u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs)  \u001B[38;5;66;03m# type: ignore[misc]\u001B[39;00m\n\u001B[1;32m   1531\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m-> 1532\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_call_impl\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/torch/nn/modules/module.py:1541\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[0;34m(self, *args, **kwargs)\u001B[0m\n\u001B[1;32m   1536\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[1;32m   1537\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[1;32m   1538\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks\n\u001B[1;32m   1539\u001B[0m         \u001B[38;5;129;01mor\u001B[39;00m _global_backward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[1;32m   1540\u001B[0m         \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[0;32m-> 1541\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m   1543\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m   1544\u001B[0m     result \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mNone\u001B[39;00m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/ultralytics/nn/autobackend.py:453\u001B[0m, in \u001B[0;36mAutoBackend.forward\u001B[0;34m(self, im, augment, visualize, embed)\u001B[0m\n\u001B[1;32m    451\u001B[0m \u001B[38;5;66;03m# PyTorch\u001B[39;00m\n\u001B[1;32m    452\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mpt \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mnn_module:\n\u001B[0;32m--> 453\u001B[0m     y \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mmodel\u001B[49m\u001B[43m(\u001B[49m\u001B[43mim\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43maugment\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43maugment\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mvisualize\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mvisualize\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43membed\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43membed\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m    455\u001B[0m \u001B[38;5;66;03m# TorchScript\u001B[39;00m\n\u001B[1;32m    456\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mjit:\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/torch/nn/modules/module.py:1532\u001B[0m, in \u001B[0;36mModule._wrapped_call_impl\u001B[0;34m(self, *args, **kwargs)\u001B[0m\n\u001B[1;32m   1530\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_compiled_call_impl(\u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs)  \u001B[38;5;66;03m# type: ignore[misc]\u001B[39;00m\n\u001B[1;32m   1531\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m-> 1532\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_call_impl\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/torch/nn/modules/module.py:1541\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[0;34m(self, *args, **kwargs)\u001B[0m\n\u001B[1;32m   1536\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[1;32m   1537\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[1;32m   1538\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks\n\u001B[1;32m   1539\u001B[0m         \u001B[38;5;129;01mor\u001B[39;00m _global_backward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[1;32m   1540\u001B[0m         \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[0;32m-> 1541\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m   1543\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m   1544\u001B[0m     result \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mNone\u001B[39;00m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/ultralytics/nn/tasks.py:89\u001B[0m, in \u001B[0;36mBaseModel.forward\u001B[0;34m(self, x, *args, **kwargs)\u001B[0m\n\u001B[1;32m     87\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(x, \u001B[38;5;28mdict\u001B[39m):  \u001B[38;5;66;03m# for cases of training and validating while training.\u001B[39;00m\n\u001B[1;32m     88\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mloss(x, \u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs)\n\u001B[0;32m---> 89\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mpredict\u001B[49m\u001B[43m(\u001B[49m\u001B[43mx\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/ultralytics/nn/tasks.py:107\u001B[0m, in \u001B[0;36mBaseModel.predict\u001B[0;34m(self, x, profile, visualize, augment, embed)\u001B[0m\n\u001B[1;32m    105\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m augment:\n\u001B[1;32m    106\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_predict_augment(x)\n\u001B[0;32m--> 107\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_predict_once\u001B[49m\u001B[43m(\u001B[49m\u001B[43mx\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mprofile\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mvisualize\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43membed\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/ultralytics/nn/tasks.py:128\u001B[0m, in \u001B[0;36mBaseModel._predict_once\u001B[0;34m(self, x, profile, visualize, embed)\u001B[0m\n\u001B[1;32m    126\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m profile:\n\u001B[1;32m    127\u001B[0m     \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_profile_one_layer(m, x, dt)\n\u001B[0;32m--> 128\u001B[0m x \u001B[38;5;241m=\u001B[39m \u001B[43mm\u001B[49m\u001B[43m(\u001B[49m\u001B[43mx\u001B[49m\u001B[43m)\u001B[49m  \u001B[38;5;66;03m# run\u001B[39;00m\n\u001B[1;32m    129\u001B[0m y\u001B[38;5;241m.\u001B[39mappend(x \u001B[38;5;28;01mif\u001B[39;00m m\u001B[38;5;241m.\u001B[39mi \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39msave \u001B[38;5;28;01melse\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m)  \u001B[38;5;66;03m# save output\u001B[39;00m\n\u001B[1;32m    130\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m visualize:\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/torch/nn/modules/module.py:1532\u001B[0m, in \u001B[0;36mModule._wrapped_call_impl\u001B[0;34m(self, *args, **kwargs)\u001B[0m\n\u001B[1;32m   1530\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_compiled_call_impl(\u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs)  \u001B[38;5;66;03m# type: ignore[misc]\u001B[39;00m\n\u001B[1;32m   1531\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m-> 1532\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_call_impl\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/torch/nn/modules/module.py:1541\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[0;34m(self, *args, **kwargs)\u001B[0m\n\u001B[1;32m   1536\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[1;32m   1537\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[1;32m   1538\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks\n\u001B[1;32m   1539\u001B[0m         \u001B[38;5;129;01mor\u001B[39;00m _global_backward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[1;32m   1540\u001B[0m         \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[0;32m-> 1541\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m   1543\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m   1544\u001B[0m     result \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mNone\u001B[39;00m\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/ultralytics/nn/modules/head.py:47\u001B[0m, in \u001B[0;36mDetect.forward\u001B[0;34m(self, x)\u001B[0m\n\u001B[1;32m     45\u001B[0m \u001B[38;5;250m\u001B[39m\u001B[38;5;124;03m\"\"\"Concatenates and returns predicted bounding boxes and class probabilities.\"\"\"\u001B[39;00m\n\u001B[1;32m     46\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m i \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28mrange\u001B[39m(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mnl):\n\u001B[0;32m---> 47\u001B[0m     x[i] \u001B[38;5;241m=\u001B[39m torch\u001B[38;5;241m.\u001B[39mcat((\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcv2\u001B[49m\u001B[43m[\u001B[49m\u001B[43mi\u001B[49m\u001B[43m]\u001B[49m\u001B[43m(\u001B[49m\u001B[43mx\u001B[49m\u001B[43m[\u001B[49m\u001B[43mi\u001B[49m\u001B[43m]\u001B[49m\u001B[43m)\u001B[49m, \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mcv3[i](x[i])), \u001B[38;5;241m1\u001B[39m)\n\u001B[1;32m     48\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mtraining:  \u001B[38;5;66;03m# Training path\u001B[39;00m\n\u001B[1;32m     49\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m x\n",
      "File \u001B[0;32m~/miniconda3/envs/tf/lib/python3.10/site-packages/torch/nn/modules/module.py:1528\u001B[0m, in \u001B[0;36mModule._wrapped_call_impl\u001B[0;34m(self, *args, **kwargs)\u001B[0m\n\u001B[1;32m   1525\u001B[0m             tracing_state\u001B[38;5;241m.\u001B[39mpop_scope()\n\u001B[1;32m   1526\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m result\n\u001B[0;32m-> 1528\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21m_wrapped_call_impl\u001B[39m(\u001B[38;5;28mself\u001B[39m, \u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs):\n\u001B[1;32m   1529\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_compiled_call_impl \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[1;32m   1530\u001B[0m         \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_compiled_call_impl(\u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs)  \u001B[38;5;66;03m# type: ignore[misc]\u001B[39;00m\n",
      "\u001B[0;31mKeyboardInterrupt\u001B[0m: "
     ]
    }
   ],
   "source": [
    "from ultralytics import YOLO\n",
    "import os\n",
    "\n",
    "model = YOLO(\"runs/detect/train26/weights/best.pt\")\n",
    "\n",
    "import cv2 as cv\n",
    "import numpy as np\n",
    "import torchvision.transforms as transforms\n",
    "from PIL import Image, ImageFont, ImageDraw\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "\n",
    "# Start the webcam\n",
    "import numpy as np\n",
    "import math\n",
    "cap = cv.VideoCapture(0)\n",
    "cap.set(3, 640)\n",
    "cap.set(4, 640)\n",
    "\n",
    "\n",
    "font = ImageFont.truetype(\"/usr/share/fonts/truetype/dejavu/DejaVuSansMono.ttf\", 20)\n",
    "\n",
    "while True:\n",
    "    success, img = cap.read()\n",
    "    results = model(img, stream=True, verbose=False)\n",
    "\n",
    "    for r in results:\n",
    "        boxes = r.boxes\n",
    "\n",
    "        for box in boxes:\n",
    "            confidence = round(float(box.conf[0] * 100))\n",
    "\n",
    "            # Skip unsure detections\n",
    "            if confidence < 0:\n",
    "                continue\n",
    "            \n",
    "            # Get coordinates and draw the bounding box\n",
    "            x1, y1, x2, y2 = box.xyxy[0]\n",
    "            x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)\n",
    "            \n",
    "            cv.rectangle(img, (x1, y1), (x2, y2), (255, 255, 255), 2)\n",
    "            cv.rectangle(img, (x1-1, y1-1), (x2+1, y2+1), (136, 150, 0), 2)\n",
    "            \n",
    "            cls = int(box.cls[0])\n",
    "\n",
    "            # Object label\n",
    "            img_pil = Image.fromarray(img)\n",
    "            draw = ImageDraw.Draw(img_pil)\n",
    "            draw.text((x1, y1),\n",
    "                      f\"[{confidence}%] {class_mapping[cls]}\",\n",
    "                      font=font,\n",
    "                      fill=(255, 255, 255),\n",
    "                      stroke_width=1,\n",
    "                      stroke_fill=(0, 0, 0))\n",
    "            img = np.array(img_pil)\n",
    "\n",
    "\n",
    "    cv.imshow(\"Webcam capture demo\", img)\n",
    "    if cv.waitKey(1) == 27:    # escape\n",
    "        break\n",
    "\n",
    "# Stop the webcam\n",
    "cap.release()\n",
    "cv.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd61781e5b705868",
   "metadata": {},
   "source": [
    "### From a photo file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5c3a7e358cf3efb5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-27T12:10:16.377820Z",
     "start_time": "2024-05-27T12:10:13.435471Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "0: 640x640 1 Glass, 5.3ms\n",
      "Speed: 2.6ms preprocess, 5.3ms inference, 1.9ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 (no detections), 3.5ms\n",
      "Speed: 1.4ms preprocess, 3.5ms inference, 0.3ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 (no detections), 5.3ms\n",
      "Speed: 1.8ms preprocess, 5.3ms inference, 1.1ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 (no detections), 3.1ms\n",
      "Speed: 1.6ms preprocess, 3.1ms inference, 0.4ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Metal, 3.7ms\n",
      "Speed: 2.5ms preprocess, 3.7ms inference, 6.5ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 (no detections), 6.2ms\n",
      "Speed: 2.0ms preprocess, 6.2ms inference, 0.8ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 (no detections), 2.8ms\n",
      "Speed: 1.5ms preprocess, 2.8ms inference, 0.3ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 480x640 1 Plastic, 3.3ms\n",
      "Speed: 1.3ms preprocess, 3.3ms inference, 0.5ms postprocess per image at shape (1, 3, 480, 640)\n",
      "\n",
      "0: 640x640 5 Plastics, 6.0ms\n",
      "Speed: 3.1ms preprocess, 6.0ms inference, 1.1ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Metal, 3.3ms\n",
      "Speed: 2.0ms preprocess, 3.3ms inference, 5.7ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Plastic, 2.7ms\n",
      "Speed: 1.4ms preprocess, 2.7ms inference, 0.5ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 (no detections), 5.1ms\n",
      "Speed: 3.3ms preprocess, 5.1ms inference, 0.6ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Glass, 4.9ms\n",
      "Speed: 2.1ms preprocess, 4.9ms inference, 1.1ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Plastic, 5.1ms\n",
      "Speed: 1.7ms preprocess, 5.1ms inference, 1.1ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Paper, 5.2ms\n",
      "Speed: 2.9ms preprocess, 5.2ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Glass, 2.6ms\n",
      "Speed: 2.0ms preprocess, 2.6ms inference, 0.8ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 (no detections), 3.3ms\n",
      "Speed: 1.7ms preprocess, 3.3ms inference, 0.3ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Paper, 3.1ms\n",
      "Speed: 2.3ms preprocess, 3.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 (no detections), 2.9ms\n",
      "Speed: 1.6ms preprocess, 2.9ms inference, 0.3ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Plastic, 2.8ms\n",
      "Speed: 1.4ms preprocess, 2.8ms inference, 0.5ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 2 Papers, 2.6ms\n",
      "Speed: 1.4ms preprocess, 2.6ms inference, 0.6ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Metal, 2.6ms\n",
      "Speed: 1.5ms preprocess, 2.6ms inference, 0.6ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Glass, 3.0ms\n",
      "Speed: 1.9ms preprocess, 3.0ms inference, 0.6ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Plastic, 2.6ms\n",
      "Speed: 2.2ms preprocess, 2.6ms inference, 0.5ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Plastic, 2.6ms\n",
      "Speed: 1.8ms preprocess, 2.6ms inference, 0.6ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Plastic, 5.4ms\n",
      "Speed: 2.0ms preprocess, 5.4ms inference, 1.7ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Plastic, 2.6ms\n",
      "Speed: 1.8ms preprocess, 2.6ms inference, 0.5ms postprocess per image at shape (1, 3, 640, 640)\n",
      "\n",
      "0: 640x640 1 Plastic, 3.7ms\n",
      "Speed: 3.0ms preprocess, 3.7ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)\n"
     ]
    }
   ],
   "source": [
    "from ultralytics import YOLO\n",
    "import os\n",
    "\n",
    "model = YOLO(\"runs/detect/train28/weights/best.pt\")\n",
    "\n",
    "import cv2 as cv\n",
    "import numpy as np\n",
    "import torchvision.transforms as transforms\n",
    "from PIL import Image, ImageFont, ImageDraw\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "\n",
    "import numpy as np\n",
    "import math\n",
    "\n",
    "font = ImageFont.truetype(\"/usr/share/fonts/truetype/dejavu/DejaVuSansMono.ttf\", 20)\n",
    "\n",
    "image_dir = \"./test_data/\"\n",
    "output_dir = \"./output/\"\n",
    "\n",
    "for image_path in os.scandir(image_dir):\n",
    "    img = cv.imread(image_path.path)\n",
    "    results = model(img)\n",
    "    \n",
    "    for r in results:\n",
    "        boxes = r.boxes\n",
    "        \n",
    "        # Geometric mean of the confidence values\n",
    "        min_confidence = np.mean([box.conf[0].cpu() for box in boxes]) * 87.5\n",
    "    \n",
    "        for box in boxes:\n",
    "            confidence = round(float(box.conf[0] * 100))\n",
    "    \n",
    "            # Skip unsure detections\n",
    "            if confidence < min_confidence:\n",
    "                continue\n",
    "            \n",
    "            # Get coordinates and draw the bounding box\n",
    "            x1, y1, x2, y2 = box.xyxy[0]\n",
    "            x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)\n",
    "            \n",
    "            cv.rectangle(img, (x1, y1), (x2, y2), (255, 255, 255), 2)\n",
    "            cv.rectangle(img, (x1-1, y1-1), (x2+1, y2+1), (136, 150, 0), 2)\n",
    "            \n",
    "            cls = int(box.cls[0])\n",
    "    \n",
    "            img_pil = Image.fromarray(img)\n",
    "            draw = ImageDraw.Draw(img_pil)\n",
    "            \n",
    "            draw.text((x1, y1),\n",
    "                      f\"[{confidence}%] {class_mapping[cls]}\",\n",
    "                      font=font,\n",
    "                      fill=(255, 255, 255),\n",
    "                      stroke_width=1,\n",
    "                      stroke_fill=(0, 0, 0))\n",
    "            img = np.array(img_pil)\n",
    "    \n",
    "    cv.imwrite(os.path.join(output_dir, os.path.basename(image_path.path)), img)\n",
    "    #cv.imshow(\"Photo\", img)\n",
    "    #cv.waitKey(27)         # escape\n",
    "    #cv.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9a640c08f07c223f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}