diff --git "a/NumberPlate_detection_using_YOLOv8.ipynb" "b/NumberPlate_detection_using_YOLOv8.ipynb"
--- "a/NumberPlate_detection_using_YOLOv8.ipynb"
+++ "b/NumberPlate_detection_using_YOLOv8.ipynb"
@@ -16,7 +16,14 @@
         "id": "WvRyifGfTQQ2"
       },
       "source": [
-        "# instance segmentation using various different approach"
+        "# license plate object detection using YOLOv8"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "#### dataset : https://huggingface.co/datasets/keremberke/license-plate-object-detection\n"
       ]
     },
     {
@@ -27,150 +34,106 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "yVFdjWeRS8jh",
-        "outputId": "8c057c2b-39c5-4407-ee03-b9358fe17c0b"
+        "outputId": "6a9c0a99-5dc3-4705-aa8b-14ea3db5c04c"
       },
       "outputs": [
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
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+            "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch>=1.8.0->ultralytics) (12.1.105)\n",
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+            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch>=1.8.0->ultralytics) (1.3.0)\n",
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+            "\u001b[?25hDownloading ultralytics-8.3.68-py3-none-any.whl (913 kB)\n",
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+            "\u001b[?25hDownloading dill-0.3.8-py3-none-any.whl (116 kB)\n",
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+            "\u001b[?25hDownloading multiprocess-0.70.16-py311-none-any.whl (143 kB)\n",
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-            "\u001b[?25hUsing cached setuptools-75.8.0-py3-none-any.whl (1.2 MB)\n",
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-            "\u001b[?25hInstalling collected packages: py-cpuinfo, mpmath, triton, sympy, setuptools, opencv-python, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, networkx, MarkupSafe, nvidia-cusparse-cu12, nvidia-cudnn-cu12, jinja2, nvidia-cusolver-cu12, torch, ultralytics-thop, torchvision, ultralytics\n",
-            "Successfully installed MarkupSafe-3.0.2 jinja2-3.1.5 mpmath-1.3.0 networkx-3.4.2 nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nccl-cu12-2.21.5 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.4.127 opencv-python-4.11.0.86 py-cpuinfo-9.0.0 setuptools-75.8.0 sympy-1.13.1 torch-2.5.1 torchvision-0.20.1 triton-3.1.0 ultralytics-8.3.68 ultralytics-thop-2.0.14\n"
+            "Downloading xxhash-3.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.8/194.8 kB\u001b[0m \u001b[31m15.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: xxhash, fsspec, dill, multiprocess, ultralytics-thop, datasets, ultralytics\n",
+            "  Attempting uninstall: fsspec\n",
+            "    Found existing installation: fsspec 2024.10.0\n",
+            "    Uninstalling fsspec-2024.10.0:\n",
+            "      Successfully uninstalled fsspec-2024.10.0\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed datasets-3.2.0 dill-0.3.8 fsspec-2024.9.0 multiprocess-0.70.16 ultralytics-8.3.68 ultralytics-thop-2.0.14 xxhash-3.5.0\n"
           ]
         }
       ],
@@ -184,112 +147,225 @@
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
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+          "height": 402,
           "referenced_widgets": [
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-            "254ed912e97c42e589c81320bdb9c41f",
-            "c3b871e061134a5f9561c8d473a46964",
-            "d8e237beb6114ceeb81d216c2b920570",
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           ]
         },
         "id": "jnJT1oEGVV6d",
-        "outputId": "1c18d27b-310f-4c45-b299-f2839a2922c8"
+        "outputId": "2f509f0a-4f9c-4c05-855f-4caa059f23b6"
       },
       "outputs": [
         {
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "/home/xd/Documents/machine_learning/ML_Notebooks/.venv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-            "  from .autonotebook import tqdm as notebook_tqdm\n",
-            "Generating train split: 100%|██████████| 6176/6176 [00:02<00:00, 2845.51 examples/s]\n",
-            "Generating validation split: 100%|██████████| 1765/1765 [00:00<00:00, 24120.12 examples/s]\n",
-            "Generating test split: 100%|██████████| 882/882 [00:00<00:00, 21573.47 examples/s]\n"
+            "/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
+            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+            "You will be able to reuse this secret in all of your notebooks.\n",
+            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+            "  warnings.warn(\n"
           ]
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "045c5a90a4e44c62bff82074ea0a4206",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "README.md:   0%|          | 0.00/1.88k [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "8a8a814623b1471f8d9b3c49c72592ef",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "license-plate-object-detection.py:   0%|          | 0.00/6.11k [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "f735de1ab77140dbb4c72207b8ebb514",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "0000.parquet:   0%|          | 0.00/168M [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "78ace055e9fb4d4f893f636f81c37c58",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "0000.parquet:   0%|          | 0.00/46.3M [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "9b5bebb7d4d44af4b466e152520f46b0",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "0000.parquet:   0%|          | 0.00/22.6M [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "031ad2790ce14930a576fbb5a70aa6ac",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Generating train split:   0%|          | 0/6176 [00:00<?, ? examples/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "95e2c81b520742bbb26480a87d26daaa",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Generating validation split:   0%|          | 0/1765 [00:00<?, ? examples/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "6e8a5580a981464e842c56ee88fdc29d",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Generating test split:   0%|          | 0/882 [00:00<?, ? examples/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
         }
       ],
       "source": [
@@ -306,7 +382,7 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "haIMLABdXUmZ",
-        "outputId": "f9730faf-6301-4f97-a441-8ef4f97f2f78"
+        "outputId": "b26a0d7c-6b83-4c8f-db80-df9f900f0b2f"
       },
       "outputs": [
         {
@@ -314,7 +390,7 @@
           "output_type": "stream",
           "text": [
             "Creating new Ultralytics Settings v0.0.6 file ✅ \n",
-            "View Ultralytics Settings with 'yolo settings' or at '/home/xd/.config/Ultralytics/settings.json'\n",
+            "View Ultralytics Settings with 'yolo settings' or at '/root/.config/Ultralytics/settings.json'\n",
             "Update Settings with 'yolo settings key=value', i.e. 'yolo settings runs_dir=path/to/dir'. For help see https://docs.ultralytics.com/quickstart/#ultralytics-settings.\n"
           ]
         }
@@ -333,10 +409,10 @@
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 685
+          "height": 425
         },
         "id": "xEqD51f1Xmce",
-        "outputId": "8568a97c-a572-4e2b-c175-89e1c8c56f4a"
+        "outputId": "6382a9b0-ab55-422f-ca8f-b1e52cb18009"
       },
       "outputs": [
         {
@@ -359,8 +435,15 @@
         },
         {
           "data": {
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "summary": "{\n  \"name\": \"df_train\",\n  \"rows\": 6176,\n  \"fields\": [\n    {\n      \"column\": \"image_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1783,\n        \"min\": 0,\n        \"max\": 6175,\n        \"num_unique_values\": 6176,\n        \"samples\": [\n          2669,\n          2934,\n          5218\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"image\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"width\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 80,\n        \"samples\": [\n          300,\n          472,\n          370\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"height\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 205,\n        \"samples\": [\n          342,\n          427,\n          512\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"objects\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+              "type": "dataframe",
+              "variable_name": "df_train"
+            },
             "text/html": [
-              "<div>\n",
+              "\n",
+              "  <div id=\"df-b250277b-1fd0-4ee9-b28a-84369bc4b472\" class=\"colab-df-container\">\n",
+              "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
               "        vertical-align: middle;\n",
@@ -428,7 +511,216 @@
               "    </tr>\n",
               "  </tbody>\n",
               "</table>\n",
-              "</div>"
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b250277b-1fd0-4ee9-b28a-84369bc4b472')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-b250277b-1fd0-4ee9-b28a-84369bc4b472 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-b250277b-1fd0-4ee9-b28a-84369bc4b472');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-63930fe7-2b7d-4db3-9aa6-d8efecad41fa\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-63930fe7-2b7d-4db3-9aa6-d8efecad41fa')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-63930fe7-2b7d-4db3-9aa6-d8efecad41fa button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
             ],
             "text/plain": [
               "   image_id                                              image  width  height  \\\n",
@@ -463,7 +755,11 @@
       "cell_type": "code",
       "execution_count": 5,
       "metadata": {
-        "id": "5gxgevPxZU26"
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "5gxgevPxZU26",
+        "outputId": "58a58ccb-985c-4098-ab72-a9ac4b57e566"
       },
       "outputs": [
         {
@@ -477,7 +773,7 @@
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "100%|██████████| 6.25M/6.25M [00:00<00:00, 56.6MB/s]\n"
+            "100%|██████████| 6.25M/6.25M [00:00<00:00, 76.2MB/s]\n"
           ]
         }
       ],
@@ -494,7 +790,7 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "SORMPYhvZb4Z",
-        "outputId": "1fb3982a-7f0f-4ed6-986a-cff7ea88117f"
+        "outputId": "365feb67-da37-4a29-afe1-3155667a1bbe"
       },
       "outputs": [
         {
@@ -513,6198 +809,11 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 8,
+      "execution_count": 7,
       "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "3Hff3i23bPE4",
-        "outputId": "6f2096e1-8598-4af0-8116-134dc231bdcc"
+        "id": "3Hff3i23bPE4"
       },
-      "outputs": [
-        {
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-          "output_type": "stream",
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-      ],
+      "outputs": [],
       "source": [
         "# Output directories\n",
         "image_dir = 'dataset/images/train'\n",
@@ -6746,7 +855,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 14,
+      "execution_count": 8,
       "metadata": {
         "id": "f_J9xp_hpenL"
       },
@@ -6793,22 +902,21 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 15,
+      "execution_count": 11,
       "metadata": {
         "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
+          "base_uri": "https://localhost:8080/"
         },
         "id": "UpfV5l2Dom3t",
-        "outputId": "1450c3fe-04d1-4708-9fe8-ccd22dda3f05"
+        "outputId": "78e0a3c8-34cc-4f92-f31d-62b4b06a132a"
       },
       "outputs": [
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "Ultralytics 8.3.68 🚀 Python-3.12.8 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce 920MX, 2003MiB)\n",
-            "\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=dataset.yaml, epochs=100, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train5, 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/xd/Documents/machine_learning/ML_Notebooks/runs/detect/train5\n",
+            "Ultralytics 8.3.68 🚀 Python-3.11.11 torch-2.5.1+cu121 CUDA:0 (NVIDIA A100-SXM4-40GB, 40514MiB)\n",
+            "\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=dataset.yaml, epochs=75, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train3, 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=runs/detect/train3\n",
             "\n",
             "                   from  n    params  module                                       arguments                     \n",
             "  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]                 \n",
@@ -6837,6 +945,7 @@
             "Model summary: 225 layers, 3,011,043 parameters, 3,011,027 gradients, 8.2 GFLOPs\n",
             "\n",
             "Transferred 355/355 items from pretrained weights\n",
+            "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/detect/train3', view at http://localhost:6006/\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"
@@ -6846,35 +955,36 @@
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /home/xd/Documents/machine_learning/ML_Notebooks/dataset/labels/train.cache... 6176 images, 0 backgrounds, 0 corrupt: 100%|██████████| 6176/6176 [00:00<?, ?it/s]\n",
-            "\u001b[34m\u001b[1mval: \u001b[0mScanning /home/xd/Documents/machine_learning/ML_Notebooks/dataset/labels/val... 1765 images, 0 backgrounds, 0 corrupt: 100%|██████████| 1765/1765 [00:02<00:00, 735.78it/s]"
+            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/dataset/labels/train.cache... 6176 images, 0 backgrounds, 0 corrupt: 100%|██████████| 6176/6176 [00:00<?, ?it/s]"
           ]
         },
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /home/xd/Documents/machine_learning/ML_Notebooks/dataset/labels/val.cache\n"
+            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01, num_output_channels=3, method='weighted_average'), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n"
           ]
         },
         {
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "\n"
+            "\n",
+            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/dataset/labels/val.cache... 1765 images, 0 backgrounds, 0 corrupt: 100%|██████████| 1765/1765 [00:00<?, ?it/s]\n"
           ]
         },
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "Plotting labels to /home/xd/Documents/machine_learning/ML_Notebooks/runs/detect/train5/labels.jpg... \n",
+            "Plotting labels to runs/detect/train3/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=0.002, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n",
+            "\u001b[34m\u001b[1mTensorBoard: \u001b[0mmodel graph visualization added ✅\n",
             "Image sizes 640 train, 640 val\n",
-            "Using 4 dataloader workers\n",
-            "Logging results to \u001b[1m/home/xd/Documents/machine_learning/ML_Notebooks/runs/detect/train5\u001b[0m\n",
-            "Starting training for 100 epochs...\n",
+            "Using 8 dataloader workers\n",
+            "Logging results to \u001b[1mruns/detect/train3\u001b[0m\n",
+            "Starting training for 75 epochs...\n",
             "\n",
             "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
           ]
@@ -6883,165 +993,2290 @@
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "      1/100         2G      1.626      4.397       1.65         30        640:   1%|          | 2/386 [00:54<2:55:25, 27.41s/it]\n"
+            "       1/75      3.87G      1.143      0.681      1.065         31        640: 100%|██████████| 386/386 [00:38<00:00,  9.98it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.89it/s]"
           ]
         },
         {
-          "ename": "OutOfMemoryError",
-          "evalue": "CUDA out of memory. Tried to allocate 34.00 MiB. GPU 0 has a total capacity of 1.96 GiB of which 33.19 MiB is free. Including non-PyTorch memory, this process has 1.91 GiB memory in use. Of the allocated memory 1.79 GiB is allocated by PyTorch, and 65.71 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)",
-          "output_type": "error",
-          "traceback": [
-            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-            "\u001b[0;31mOutOfMemoryError\u001b[0m                          Traceback (most recent call last)",
-            "Cell \u001b[0;32mIn[15], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Train the model using the YAML file\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mdataset.yaml\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mepochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mimgsz\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m640\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m16\u001b[39;49m\u001b[43m)\u001b[49m\n",
-            "File \u001b[0;32m~/Documents/machine_learning/ML_Notebooks/.venv/lib/python3.12/site-packages/ultralytics/engine/model.py:806\u001b[0m, in \u001b[0;36mModel.train\u001b[0;34m(self, trainer, **kwargs)\u001b[0m\n\u001b[1;32m    803\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtrainer\u001b[38;5;241m.\u001b[39mmodel\n\u001b[1;32m    805\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtrainer\u001b[38;5;241m.\u001b[39mhub_session \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msession  \u001b[38;5;66;03m# attach optional HUB session\u001b[39;00m\n\u001b[0;32m--> 806\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrainer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    807\u001b[0m \u001b[38;5;66;03m# Update model and cfg after training\u001b[39;00m\n\u001b[1;32m    808\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m RANK \u001b[38;5;129;01min\u001b[39;00m {\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m0\u001b[39m}:\n",
-            "File \u001b[0;32m~/Documents/machine_learning/ML_Notebooks/.venv/lib/python3.12/site-packages/ultralytics/engine/trainer.py:207\u001b[0m, in \u001b[0;36mBaseTrainer.train\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    204\u001b[0m         ddp_cleanup(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28mstr\u001b[39m(file))\n\u001b[1;32m    206\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 207\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_do_train\u001b[49m\u001b[43m(\u001b[49m\u001b[43mworld_size\u001b[49m\u001b[43m)\u001b[49m\n",
-            "File \u001b[0;32m~/Documents/machine_learning/ML_Notebooks/.venv/lib/python3.12/site-packages/ultralytics/engine/trainer.py:388\u001b[0m, in \u001b[0;36mBaseTrainer._do_train\u001b[0;34m(self, world_size)\u001b[0m\n\u001b[1;32m    383\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtloss \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m    384\u001b[0m         (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtloss \u001b[38;5;241m*\u001b[39m i \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mloss_items) \u001b[38;5;241m/\u001b[39m (i \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtloss \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mloss_items\n\u001b[1;32m    385\u001b[0m     )\n\u001b[1;32m    387\u001b[0m \u001b[38;5;66;03m# Backward\u001b[39;00m\n\u001b[0;32m--> 388\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mscaler\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mscale\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloss\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbackward\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    390\u001b[0m \u001b[38;5;66;03m# Optimize - https://pytorch.org/docs/master/notes/amp_examples.html\u001b[39;00m\n\u001b[1;32m    391\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ni \u001b[38;5;241m-\u001b[39m last_opt_step \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maccumulate:\n",
-            "File \u001b[0;32m~/Documents/machine_learning/ML_Notebooks/.venv/lib/python3.12/site-packages/torch/_tensor.py:581\u001b[0m, in \u001b[0;36mTensor.backward\u001b[0;34m(self, gradient, retain_graph, create_graph, inputs)\u001b[0m\n\u001b[1;32m    571\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m has_torch_function_unary(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m    572\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m handle_torch_function(\n\u001b[1;32m    573\u001b[0m         Tensor\u001b[38;5;241m.\u001b[39mbackward,\n\u001b[1;32m    574\u001b[0m         (\u001b[38;5;28mself\u001b[39m,),\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    579\u001b[0m         inputs\u001b[38;5;241m=\u001b[39minputs,\n\u001b[1;32m    580\u001b[0m     )\n\u001b[0;32m--> 581\u001b[0m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mautograd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbackward\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    582\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgradient\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mretain_graph\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreate_graph\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minputs\u001b[49m\n\u001b[1;32m    583\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
-            "File \u001b[0;32m~/Documents/machine_learning/ML_Notebooks/.venv/lib/python3.12/site-packages/torch/autograd/__init__.py:347\u001b[0m, in \u001b[0;36mbackward\u001b[0;34m(tensors, grad_tensors, retain_graph, create_graph, grad_variables, inputs)\u001b[0m\n\u001b[1;32m    342\u001b[0m     retain_graph \u001b[38;5;241m=\u001b[39m create_graph\n\u001b[1;32m    344\u001b[0m \u001b[38;5;66;03m# The reason we repeat the same comment below is that\u001b[39;00m\n\u001b[1;32m    345\u001b[0m \u001b[38;5;66;03m# some Python versions print out the first line of a multi-line function\u001b[39;00m\n\u001b[1;32m    346\u001b[0m \u001b[38;5;66;03m# calls in the traceback and some print out the last line\u001b[39;00m\n\u001b[0;32m--> 347\u001b[0m \u001b[43m_engine_run_backward\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    348\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtensors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    349\u001b[0m \u001b[43m    \u001b[49m\u001b[43mgrad_tensors_\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    350\u001b[0m \u001b[43m    \u001b[49m\u001b[43mretain_graph\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    351\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcreate_graph\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    352\u001b[0m \u001b[43m    \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    353\u001b[0m \u001b[43m    \u001b[49m\u001b[43mallow_unreachable\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    354\u001b[0m \u001b[43m    \u001b[49m\u001b[43maccumulate_grad\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    355\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
-            "File \u001b[0;32m~/Documents/machine_learning/ML_Notebooks/.venv/lib/python3.12/site-packages/torch/autograd/graph.py:825\u001b[0m, in \u001b[0;36m_engine_run_backward\u001b[0;34m(t_outputs, *args, **kwargs)\u001b[0m\n\u001b[1;32m    823\u001b[0m     unregister_hooks \u001b[38;5;241m=\u001b[39m _register_logging_hooks_on_whole_graph(t_outputs)\n\u001b[1;32m    824\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 825\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mVariable\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_execution_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_backward\u001b[49m\u001b[43m(\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# Calls into the C++ engine to run the backward pass\u001b[39;49;00m\n\u001b[1;32m    826\u001b[0m \u001b[43m        \u001b[49m\u001b[43mt_outputs\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\n\u001b[1;32m    827\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m  \u001b[38;5;66;03m# Calls into the C++ engine to run the backward pass\u001b[39;00m\n\u001b[1;32m    828\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m    829\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m attach_logging_hooks:\n",
-            "\u001b[0;31mOutOfMemoryError\u001b[0m: CUDA out of memory. Tried to allocate 34.00 MiB. GPU 0 has a total capacity of 1.96 GiB of which 33.19 MiB is free. Including non-PyTorch memory, this process has 1.91 GiB memory in use. Of the allocated memory 1.79 GiB is allocated by PyTorch, and 65.71 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.975       0.95      0.975      0.641\n"
           ]
-        }
-      ],
-      "source": [
-        "# Train the model using the YAML file\n",
-        "results = model.train(data=\"dataset.yaml\", epochs=100, imgsz=640, batch=16)"
-      ]
-    }
-  ],
-  "metadata": {
-    "colab": {
-      "authorship_tag": "ABX9TyPgZ3/nPwQl1eSxqGKyKzEu",
-      "include_colab_link": true,
-      "provenance": []
-    },
-    "kernelspec": {
-      "display_name": ".venv",
-      "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",
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-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
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-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
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+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "\n"
+          ]
         },
-        "04b9d680e34c4ff89552b093f68b6e89": {
-          "model_module": "@jupyter-widgets/base",
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-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
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-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
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-            "order": null,
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-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
+          ]
         },
-        "053f3073855549259ec5e3ea7a2c3863": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
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-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
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-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HBoxView",
-            "box_style": "",
-            "children": [
-              "IPY_MODEL_bd39751fd17043ec836dc677d0b34031",
-              "IPY_MODEL_455cf66e4c024f79b8ec35b1705cfa2e",
-              "IPY_MODEL_508574e083e74f7eb2cf14657a8bce47"
-            ],
-            "layout": "IPY_MODEL_1273af0e3b084d0488ce9c34fb25f805"
-          }
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "       2/75      4.01G      1.186     0.6815      1.092         28        640: 100%|██████████| 386/386 [00:36<00:00, 10.45it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.84it/s]"
+          ]
         },
-        "057301b8a5694d14bc3fcb71d0c29eaf": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.913      0.932      0.962      0.649\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": [
+            "       3/75      4.01G      1.206     0.6668      1.097         31        640: 100%|██████████| 386/386 [00:35<00:00, 10.85it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.00it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.955      0.952      0.979      0.668\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": [
+            "       4/75      4.01G      1.196     0.6361      1.095         32        640: 100%|██████████| 386/386 [00:35<00:00, 11.01it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.12it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.974      0.959      0.981      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": [
+            "       5/75      4.01G      1.189     0.6285      1.099         30        640: 100%|██████████| 386/386 [00:34<00:00, 11.05it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.06it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.971      0.954      0.981       0.68\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": [
+            "       6/75      4.01G      1.161     0.6001      1.081         25        640: 100%|██████████| 386/386 [00:35<00:00, 11.03it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.05it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.974      0.969      0.989      0.689\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": [
+            "       7/75      4.01G      1.145     0.5798      1.073         24        640: 100%|██████████| 386/386 [00:35<00:00, 10.88it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.14it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.974      0.967      0.989      0.691\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": [
+            "       8/75      4.01G      1.147     0.5732      1.073         32        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.95it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.968      0.967      0.987      0.689\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": [
+            "       9/75      4.01G      1.126     0.5606      1.068         24        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.09it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.975      0.961      0.983      0.694\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": [
+            "      10/75      4.01G      1.119     0.5514      1.062         28        640: 100%|██████████| 386/386 [00:34<00:00, 11.05it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.71it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.972      0.955      0.985      0.697\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": [
+            "      11/75      4.01G      1.124     0.5437      1.063         29        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.03it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.973      0.967      0.988       0.69\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": [
+            "      12/75      4.01G      1.124     0.5377      1.062         28        640: 100%|██████████| 386/386 [00:35<00:00, 10.92it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.90it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.968      0.985      0.702\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": [
+            "      13/75      4.01G      1.112     0.5336      1.061         42        640: 100%|██████████| 386/386 [00:35<00:00, 10.96it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.969      0.972      0.988      0.692\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": [
+            "      14/75      4.01G      1.109     0.5251      1.051         27        640: 100%|██████████| 386/386 [00:34<00:00, 11.10it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.81it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.979      0.968      0.987       0.71\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": [
+            "      15/75      4.01G      1.109     0.5195      1.056         34        640: 100%|██████████| 386/386 [00:34<00:00, 11.09it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.32it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.977      0.969      0.988      0.717\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": [
+            "      16/75      4.01G      1.099     0.5134      1.055         28        640: 100%|██████████| 386/386 [00:34<00:00, 11.05it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.05it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.982      0.967      0.988      0.705\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": [
+            "      17/75      4.01G      1.095     0.5061      1.055         31        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.03it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.975      0.973      0.989       0.71\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": [
+            "      18/75      4.01G      1.092     0.5071      1.053         30        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.84it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.979      0.966      0.985      0.707\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": [
+            "      19/75      4.01G      1.081     0.5001      1.048         31        640: 100%|██████████| 386/386 [00:35<00:00, 10.80it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.17it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.973       0.98      0.987      0.701\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": [
+            "      20/75      4.01G      1.073     0.4922      1.045         27        640: 100%|██████████| 386/386 [00:34<00:00, 11.08it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.84it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.982       0.97      0.988      0.709\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": [
+            "      21/75      4.01G      1.084     0.4985      1.047         23        640: 100%|██████████| 386/386 [00:35<00:00, 10.95it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.09it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.977      0.968       0.99       0.72\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": [
+            "      22/75      4.01G      1.064     0.4892      1.037         33        640: 100%|██████████| 386/386 [00:35<00:00, 10.94it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.87it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.972      0.973       0.99      0.704\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": [
+            "      23/75      4.01G      1.078     0.4916      1.041         34        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.24it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.979      0.971       0.99      0.725\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": [
+            "      24/75      4.01G      1.062     0.4822      1.037         27        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.81it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.977      0.973      0.989      0.719\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": [
+            "      25/75      4.01G       1.07     0.4853      1.041         43        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.15it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.975      0.976       0.99       0.72\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": [
+            "      26/75      4.01G      1.061     0.4755      1.032         36        640: 100%|██████████| 386/386 [00:35<00:00, 10.96it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.92it/s]\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.975      0.978      0.991      0.727\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "      27/75      4.01G      1.059     0.4759      1.038         29        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.04it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.981      0.974      0.991      0.726\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": [
+            "      28/75      4.01G      1.058     0.4687      1.036         22        640: 100%|██████████| 386/386 [00:35<00:00, 10.97it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.977      0.973      0.988      0.718\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": [
+            "      29/75      4.01G      1.055     0.4652      1.032         26        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.982      0.974       0.99      0.725\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": [
+            "      30/75      4.01G       1.05      0.462      1.034         28        640: 100%|██████████| 386/386 [00:35<00:00, 10.80it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.89it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.984      0.976      0.992      0.725\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": [
+            "      31/75      4.01G      1.038     0.4587      1.033         22        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.00it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.974      0.981       0.99      0.721\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": [
+            "      32/75      4.01G      1.043     0.4582       1.03         28        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.11it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.977      0.973      0.991      0.722\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": [
+            "      33/75      4.01G      1.041     0.4539      1.022         30        640: 100%|██████████| 386/386 [00:35<00:00, 10.99it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.98it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.977      0.979      0.992      0.731\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": [
+            "      34/75      4.01G      1.044     0.4597      1.026         25        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.20it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.978      0.976      0.992      0.729\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": [
+            "      35/75      4.01G      1.028     0.4473      1.025         35        640: 100%|██████████| 386/386 [00:35<00:00, 11.01it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.98it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.982      0.976      0.993       0.73\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": [
+            "      36/75      4.01G      1.034     0.4504      1.028         30        640: 100%|██████████| 386/386 [00:35<00:00, 10.86it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.11it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.975      0.989      0.725\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": [
+            "      37/75      4.01G      1.024     0.4418      1.024         27        640: 100%|██████████| 386/386 [00:35<00:00, 10.94it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.80it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.972      0.991      0.727\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": [
+            "      38/75      4.01G      1.018     0.4412      1.017         35        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.06it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.979      0.976      0.992      0.724\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": [
+            "      39/75      4.01G      1.031     0.4443      1.025         33        640: 100%|██████████| 386/386 [00:35<00:00, 10.90it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.73it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.977      0.977      0.991      0.728\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": [
+            "      40/75      4.01G      1.026     0.4408      1.026         27        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.22it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.976      0.977      0.991       0.73\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": [
+            "      41/75      4.01G       1.01     0.4325      1.016         38        640: 100%|██████████| 386/386 [00:35<00:00, 10.92it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.88it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.979      0.977      0.991      0.734\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": [
+            "      42/75      4.01G      1.014     0.4312      1.016         27        640: 100%|██████████| 386/386 [00:35<00:00, 10.83it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.984       0.97       0.99      0.737\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": [
+            "      43/75      4.01G      1.015     0.4328      1.018         26        640: 100%|██████████| 386/386 [00:34<00:00, 11.09it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.79it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.984      0.973      0.991      0.737\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": [
+            "      44/75      4.01G      1.009     0.4306      1.018         26        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.19it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.982      0.976      0.992      0.734\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": [
+            "      45/75      4.01G      1.009     0.4255      1.012         26        640: 100%|██████████| 386/386 [00:34<00:00, 11.07it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.99it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.975      0.991      0.737\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": [
+            "      46/75      4.01G      1.005     0.4262      1.013         32        640: 100%|██████████| 386/386 [00:34<00:00, 11.03it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.09it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.977      0.991      0.734\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": [
+            "      47/75      4.01G      1.001     0.4223      1.011         30        640: 100%|██████████| 386/386 [00:34<00:00, 11.04it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.93it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.982      0.978      0.991      0.744\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": [
+            "      48/75      4.01G          1     0.4205      1.007         30        640: 100%|██████████| 386/386 [00:35<00:00, 10.82it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.20it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.978      0.978      0.991      0.731\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": [
+            "      49/75      4.01G     0.9894     0.4139      1.004         28        640: 100%|██████████| 386/386 [00:34<00:00, 11.08it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.95it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.984      0.977      0.991      0.737\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": [
+            "      50/75      4.01G     0.9881     0.4116       1.01         29        640: 100%|██████████| 386/386 [00:34<00:00, 11.03it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.12it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.973      0.991      0.736\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": [
+            "      51/75      4.01G     0.9787     0.4083      1.007         32        640: 100%|██████████| 386/386 [00:35<00:00, 10.93it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.18it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.984      0.972      0.991      0.742\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": [
+            "      52/75      4.01G     0.9848     0.4058      1.008         36        640: 100%|██████████| 386/386 [00:34<00:00, 11.05it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.97it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.979      0.993      0.739\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": [
+            "      53/75      4.01G     0.9799     0.4047      1.004         32        640: 100%|██████████| 386/386 [00:35<00:00, 10.99it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.13it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.987      0.978      0.991      0.735\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": [
+            "      54/75      4.01G     0.9871      0.405      1.007         37        640: 100%|██████████| 386/386 [00:35<00:00, 10.79it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.94it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.987      0.976      0.992       0.74\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": [
+            "      55/75      4.01G     0.9756     0.4016      1.001         27        640: 100%|██████████| 386/386 [00:34<00:00, 11.08it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.02it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.978      0.992      0.736\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": [
+            "      56/75      4.01G     0.9782     0.4004          1         22        640: 100%|██████████| 386/386 [00:35<00:00, 10.99it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.97it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.985      0.978      0.992      0.741\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": [
+            "      57/75      4.01G     0.9762     0.4005     0.9995         40        640: 100%|██████████| 386/386 [00:34<00:00, 11.06it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.10it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.988      0.977      0.993      0.739\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": [
+            "      58/75      4.01G     0.9765     0.3915     0.9991         39        640: 100%|██████████| 386/386 [00:34<00:00, 11.07it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.96it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.986      0.977      0.992       0.74\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": [
+            "      59/75      4.01G     0.9694     0.3908      0.998         31        640: 100%|██████████| 386/386 [00:35<00:00, 10.99it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.19it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.984      0.978      0.992      0.739\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": [
+            "      60/75      4.01G     0.9543     0.3885     0.9944         36        640: 100%|██████████| 386/386 [00:35<00:00, 10.87it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.94it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.982      0.982      0.992      0.743\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": [
+            "      61/75      4.01G     0.9681     0.3927     0.9933         28        640: 100%|██████████| 386/386 [00:35<00:00, 11.01it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.978      0.992      0.741\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": [
+            "      62/75      4.01G     0.9578     0.3859     0.9942         26        640: 100%|██████████| 386/386 [00:35<00:00, 10.90it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.94it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.985       0.98      0.992       0.74\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": [
+            "      63/75      4.01G     0.9556      0.383     0.9948         23        640: 100%|██████████| 386/386 [00:35<00:00, 11.01it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.16it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.985       0.98      0.992      0.743\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": [
+            "      64/75      4.01G     0.9538     0.3849      0.994         36        640: 100%|██████████| 386/386 [00:35<00:00, 11.02it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.91it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.986      0.978      0.992      0.743\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": [
+            "      65/75      4.01G     0.9475     0.3823     0.9894         35        640: 100%|██████████| 386/386 [00:35<00:00, 10.98it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.09it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.983      0.978      0.992      0.739\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Closing dataloader mosaic\n",
+            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01, num_output_channels=3, method='weighted_average'), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n",
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "      66/75      4.01G     0.9412     0.3463      1.002         16        640: 100%|██████████| 386/386 [00:35<00:00, 10.83it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.94it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.985      0.978      0.991      0.737\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": [
+            "      67/75      4.01G     0.9393     0.3446      1.005         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.16it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.07it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.986      0.976      0.991       0.74\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": [
+            "      68/75      4.01G      0.933     0.3398      1.001         16        640: 100%|██████���███| 386/386 [00:34<00:00, 11.25it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.02it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.984       0.98      0.991      0.743\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": [
+            "      69/75      4.01G     0.9288     0.3388     0.9981         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.24it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.99it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.988      0.976      0.992      0.741\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": [
+            "      70/75      4.01G     0.9258     0.3363     0.9976         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.24it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.12it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.987      0.977      0.992      0.742\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": [
+            "      71/75      4.01G     0.9173     0.3323     0.9919         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.24it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.98it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.989      0.974      0.991      0.743\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": [
+            "      72/75      4.01G     0.9119     0.3303     0.9896         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.06it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.04it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765      0.991      0.972      0.992      0.743\n"
+          ]
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+          "text": [
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "      73/75      4.01G     0.9126     0.3291     0.9877         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.20it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.99it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765       0.99      0.974      0.992      0.744\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": [
+            "      74/75      4.01G     0.9078     0.3285     0.9853         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.16it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.14it/s]"
+          ]
+        },
+        {
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+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765       0.99      0.974      0.992      0.744\n"
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+        },
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+          "text": [
+            "\n",
+            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "      75/75      4.01G     0.9056     0.3249     0.9883         16        640: 100%|██████████| 386/386 [00:34<00:00, 11.22it/s]\n",
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  9.08it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765       0.99      0.972      0.991      0.744\n"
+          ]
+        },
+        {
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+          "output_type": "stream",
+          "text": [
+            "\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\n",
+            "75 epochs completed in 0.876 hours.\n",
+            "Optimizer stripped from runs/detect/train3/weights/last.pt, 6.2MB\n",
+            "Optimizer stripped from runs/detect/train3/weights/best.pt, 6.2MB\n",
+            "\n",
+            "Validating runs/detect/train3/weights/best.pt...\n",
+            "Ultralytics 8.3.68 🚀 Python-3.11.11 torch-2.5.1+cu121 CUDA:0 (NVIDIA A100-SXM4-40GB, 40514MiB)\n",
+            "Model summary (fused): 168 layers, 3,005,843 parameters, 0 gradients, 8.1 GFLOPs\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 56/56 [00:06<00:00,  8.10it/s]\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "                   all       1765       1765       0.99      0.974      0.993      0.744\n",
+            "Speed: 0.1ms preprocess, 0.4ms inference, 0.0ms loss, 0.8ms postprocess per image\n",
+            "Results saved to \u001b[1mruns/detect/train3\u001b[0m\n"
+          ]
+        }
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