diff --git a/docs/notebooks/serialise-detections-to-csv.ipynb b/docs/notebooks/serialise-detections-to-csv.ipynb
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@@ -0,0 +1,706 @@
+{
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "RFjrV07Spmm2"
+            },
+            "source": [
+                "# Serialise Detections to a CSV File\n",
+                "\n",
+                "---\n",
+                "\n",
+                "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow/supervision/blob/develop/docs/notebooks/detections-to-jsonsink.ipynb)\n",
+                "\n",
+                "This cookbook introduce [sv.CSVSink](https://supervision.roboflow.com/develop/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) tool designed to write captured object detection data to file from video streams/file"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "aFQHoaDLp8R3"
+            },
+            "source": [
+                "Click the `Open in Colab` button to run the cookbook on Google Colab."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {
+                "id": "hzMGlRKlel4p"
+            },
+            "outputs": [],
+            "source": [
+                "!pip install -q inference requests tqdm supervision==0.19.0rc5"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 39,
+            "metadata": {
+                "id": "6vRfXc_Je5Ee"
+            },
+            "outputs": [],
+            "source": [
+                "import supervision as sv\n",
+                "from supervision.assets import download_assets, VideoAssets\n",
+                "from inference import InferencePipeline\n",
+                "from inference.core.interfaces.camera.entities import VideoFrame\n",
+                "import numpy as np\n",
+                "import pandas as pd"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {
+                "id": "urRjZjh2f30v"
+            },
+            "outputs": [],
+            "source": [
+                "SOURCE_VIDEO_PATH = download_assets(VideoAssets.PEOPLE_WALKING)\n",
+                "CONFIDENCE_THRESHOLD = 0.3\n",
+                "IOU_THRESHOLD = 0.7"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "2YyE30JOS4Sf"
+            },
+            "source": [
+                "## Initialize ByteTrack"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 41,
+            "metadata": {
+                "id": "Jpw_TzAsm2oL"
+            },
+            "outputs": [],
+            "source": [
+                "byte_track = sv.ByteTrack()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "IjYwj2vbTLBd"
+            },
+            "source": [
+                "## Initialize CSVSink and open sink"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 42,
+            "metadata": {
+                "id": "-yvv6N1uTKSl"
+            },
+            "outputs": [],
+            "source": [
+                "csv_sink = sv.CSVSink('detections.csv')\n",
+                "csv_sink.open()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "d7IAyIYzmv_v"
+            },
+            "source": [
+                "## Process video to class to track detections and save detections to CSV file"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "-YvmJW5yud1G"
+            },
+            "source": [
+                "All the operations we plan to perform for each frame of our video - detection, tracking, annotation, and write to csv - are encapsulated in a function named `callback`."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 43,
+            "metadata": {
+                "id": "eRQiVkblapCk"
+            },
+            "outputs": [],
+            "source": [
+                "def callback(predictions: dict, frame: VideoFrame) -> np.ndarray:\n",
+                "    detections = sv.Detections.from_inference(predictions)\n",
+                "    detections = byte_track.update_with_detections(detections)\n",
+                "    csv_sink.append(detections, custom_data={'frame_number': frame.frame_id})\n",
+                "    print(f\"Processed Frame ID: {frame.frame_id}\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {
+                "id": "3GRH_QdHgGiC"
+            },
+            "outputs": [],
+            "source": [
+                "#Aliases:\u00a0https://inference.roboflow.com/reference_pages/model_aliases/\n",
+                "\n",
+                "REGISTERED_ALIASES = {\n",
+                "    \"yolov8n-640\": \"coco/3\",\n",
+                "    \"yolov8n-1280\": \"coco/9\",\n",
+                "    \"yolov8m-640\": \"coco/8\",\n",
+                "    \"yolov8x-1280\": \"coco/10\",\n",
+                "}\n",
+                "\n",
+                "def resolve_roboflow_model_alias(model_id: str) -> str:\n",
+                "    return REGISTERED_ALIASES.get(model_id, model_id)\n",
+                "\n",
+                "alias = \"yolov8n-640\"\n",
+                "model_name = resolve_roboflow_model_alias(alias)\n",
+                "\n",
+                "pipeline = InferencePipeline.init(\n",
+                "    model_id=model_name,\n",
+                "    video_reference=SOURCE_VIDEO_PATH,\n",
+                "    on_prediction=callback,\n",
+                "    iou_threshold=IOU_THRESHOLD,\n",
+                "    confidence_threshold=CONFIDENCE_THRESHOLD,\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {
+                "id": "bYpA9VxBsOvS"
+            },
+            "outputs": [],
+            "source": [
+                "pipeline.start()\n",
+                "pipeline.join()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 46,
+            "metadata": {
+                "id": "RrewOF02AYta"
+            },
+            "outputs": [],
+            "source": [
+                "# Close CSVSink\n",
+                "csv_sink.close()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "u7Akx7aUsh75"
+            },
+            "source": [
+                "## Visualizate results of detections CSV data with Pandas\n",
+                "\n",
+                "Let's take a look at our resulting data with by using Pandas.\n",
+                "\n",
+                "It will also be created in your current directory with the name detections.csv as well."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 47,
+            "metadata": {
+                "colab": {
+                    "base_uri": "https://localhost:8080/",
+                    "height": 424
+                },
+                "id": "Bu7AZ3QHiAqb",
+                "outputId": "22678389-7be4-4d5e-beb5-2543bdde0b52"
+            },
+            "outputs": [
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+                            "  .colab-df-quickchart {\n",
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+                            "    display: none;\n",
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+                            "    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",
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+                            "  .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",
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+                            "    90% {\n",
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+                            "      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-7b9a62a0-d6a9-45ac-8c4f-0045260ee899 button');\n",
+                            "      quickchartButtonEl.style.display =\n",
+                            "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+                            "    })();\n",
+                            "  </script>\n",
+                            "</div>\n",
+                            "\n",
+                            "  <div id=\"id_c686c1cf-a259-4607-96eb-65ba62bdeb6e\">\n",
+                            "    <style>\n",
+                            "      .colab-df-generate {\n",
+                            "        background-color: #E8F0FE;\n",
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+                            "      }\n",
+                            "\n",
+                            "      .colab-df-generate: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",
+                            "      [theme=dark] .colab-df-generate {\n",
+                            "        background-color: #3B4455;\n",
+                            "        fill: #D2E3FC;\n",
+                            "      }\n",
+                            "\n",
+                            "      [theme=dark] .colab-df-generate: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",
+                            "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+                            "            title=\"Generate code using this dataframe.\"\n",
+                            "            style=\"display:none;\">\n",
+                            "\n",
+                            "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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+                            "  </svg>\n",
+                            "    </button>\n",
+                            "    <script>\n",
+                            "      (() => {\n",
+                            "      const buttonEl =\n",
+                            "        document.querySelector('#id_c686c1cf-a259-4607-96eb-65ba62bdeb6e button.colab-df-generate');\n",
+                            "      buttonEl.style.display =\n",
+                            "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+                            "\n",
+                            "      buttonEl.onclick = () => {\n",
+                            "        google.colab.notebook.generateWithVariable('df');\n",
+                            "      }\n",
+                            "      })();\n",
+                            "    </script>\n",
+                            "  </div>\n",
+                            "\n",
+                            "    </div>\n",
+                            "  </div>\n"
+                        ],
+                        "text/plain": [
+                            "            x_min       y_min       x_max       y_max  class_id  confidence  \\\n",
+                            "0     1460.000000  469.000000  1544.00000   641.00000         0    0.820143   \n",
+                            "1     1447.000000  320.000000  1516.00000   480.00000         0    0.791599   \n",
+                            "2      259.000000  435.000000   326.00000   610.00000         0    0.775027   \n",
+                            "3     1142.000000  950.000000  1245.00000  1080.00000         0    0.768063   \n",
+                            "4      665.000000  649.000000   744.00000   851.00000         0    0.762994   \n",
+                            "...           ...         ...         ...         ...       ...         ...   \n",
+                            "7917  1854.766600  259.925570  1914.51900   442.58704         0    0.715024   \n",
+                            "7918   391.996430  470.574280   460.88147   632.92770         0    0.506561   \n",
+                            "7919    74.250565  700.197940   173.04185   893.15936         0    0.477815   \n",
+                            "7920  1012.475770  170.831770  1058.31270   297.39798         0    0.565866   \n",
+                            "7921  1012.560800   60.415718  1052.00890   175.33592         0    0.406130   \n",
+                            "\n",
+                            "      tracker_id  frame_number  \n",
+                            "0            180             1  \n",
+                            "1            181             1  \n",
+                            "2            182             1  \n",
+                            "3            183             1  \n",
+                            "4            184             1  \n",
+                            "...          ...           ...  \n",
+                            "7917         322           341  \n",
+                            "7918         318           341  \n",
+                            "7919         306           341  \n",
+                            "7920         283           341  \n",
+                            "7921         320           341  \n",
+                            "\n",
+                            "[7922 rows x 8 columns]"
+                        ]
+                    },
+                    "execution_count": 47,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "df = pd.read_csv('detections.csv')\n",
+                "df"
+            ]
+        }
+    ],
+    "metadata": {
+        "colab": {
+            "provenance": []
+        },
+        "kernelspec": {
+            "display_name": "Python 3",
+            "name": "python3"
+        },
+        "language_info": {
+            "name": "python"
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 0
+}
diff --git a/docs/notebooks/serialise-detections-to-json.ipynb b/docs/notebooks/serialise-detections-to-json.ipynb
new file mode 100644
index 00000000..59e3c4d7
--- /dev/null
+++ b/docs/notebooks/serialise-detections-to-json.ipynb
@@ -0,0 +1,708 @@
+{
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "RFjrV07Spmm2"
+            },
+            "source": [
+                "# Serialise Detections to a JSON File\n",
+                "\n",
+                "---\n",
+                "\n",
+                "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow/supervision/blob/develop/docs/notebooks/detections-to-jsonsink.ipynb)\n",
+                "\n",
+                "This cookbook introduce [sv.JSONSink](https://supervision.roboflow.com/develop/detection/tools/save_detections/#supervision.detection.tools.json_sink.JSONSink) tool designed to write captured object detection data to file from video streams/file"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "aFQHoaDLp8R3"
+            },
+            "source": [
+                "Click the `Open in Colab` button to run the cookbook on Google Colab."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {
+                "id": "hzMGlRKlel4p"
+            },
+            "outputs": [],
+            "source": [
+                "!pip install -q inference requests tqdm  supervision==0.19.0rc6"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {
+                "id": "6vRfXc_Je5Ee"
+            },
+            "outputs": [],
+            "source": [
+                "import supervision as sv\n",
+                "from supervision.assets import download_assets, VideoAssets\n",
+                "from inference import InferencePipeline\n",
+                "from inference.core.interfaces.camera.entities import VideoFrame\n",
+                "import numpy as np\n",
+                "import pandas as pd"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {
+                "id": "urRjZjh2f30v"
+            },
+            "outputs": [],
+            "source": [
+                "SOURCE_VIDEO_PATH = download_assets(VideoAssets.PEOPLE_WALKING)\n",
+                "CONFIDENCE_THRESHOLD = 0.3\n",
+                "IOU_THRESHOLD = 0.7"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "2YyE30JOS4Sf"
+            },
+            "source": [
+                "## Initialize ByteTrack"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 20,
+            "metadata": {
+                "id": "Jpw_TzAsm2oL"
+            },
+            "outputs": [],
+            "source": [
+                "byte_track = sv.ByteTrack()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "IjYwj2vbTLBd"
+            },
+            "source": [
+                "## Initialize JsonSink"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 21,
+            "metadata": {
+                "id": "-yvv6N1uTKSl"
+            },
+            "outputs": [],
+            "source": [
+                "json_sink = sv.JSONSink('detections.json')\n",
+                "json_sink.open()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "d7IAyIYzmv_v"
+            },
+            "source": [
+                "## Process video to class to track detections and save detections to json file"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "-YvmJW5yud1G"
+            },
+            "source": [
+                "All the operations we plan to perform for each frame of our video - detection, tracking, annotation, and write to json - are encapsulated in a function named `callback`."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 22,
+            "metadata": {
+                "id": "eRQiVkblapCk"
+            },
+            "outputs": [],
+            "source": [
+                "def callback(predictions: dict, frame: VideoFrame) -> np.ndarray:\n",
+                "    detections = sv.Detections.from_inference(predictions)\n",
+                "    detections = byte_track.update_with_detections(detections)\n",
+                "    json_sink.append(detections, custom_data={'frame_number': frame.frame_id})\n",
+                "    print(f\"Processed Frame ID: {frame.frame_id}\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 23,
+            "metadata": {
+                "id": "3GRH_QdHgGiC"
+            },
+            "outputs": [],
+            "source": [
+                "#Aliases:\u00a0https://inference.roboflow.com/reference_pages/model_aliases/\n",
+                "\n",
+                "REGISTERED_ALIASES = {\n",
+                "    \"yolov8n-640\": \"coco/3\",\n",
+                "    \"yolov8n-1280\": \"coco/9\",\n",
+                "    \"yolov8m-640\": \"coco/8\",\n",
+                "    \"yolov8x-1280\": \"coco/10\",\n",
+                "}\n",
+                "\n",
+                "def resolve_roboflow_model_alias(model_id: str) -> str:\n",
+                "    return REGISTERED_ALIASES.get(model_id, model_id)\n",
+                "\n",
+                "alias = \"yolov8n-640\"\n",
+                "model_name = resolve_roboflow_model_alias(alias)\n",
+                "\n",
+                "pipeline = InferencePipeline.init(\n",
+                "    model_id=model_name,\n",
+                "    video_reference=SOURCE_VIDEO_PATH,\n",
+                "    on_prediction=callback,\n",
+                "    iou_threshold=IOU_THRESHOLD,\n",
+                "    confidence_threshold=CONFIDENCE_THRESHOLD,\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {
+                "id": "bYpA9VxBsOvS"
+            },
+            "outputs": [],
+            "source": [
+                "pipeline.start()\n",
+                "pipeline.join()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {
+                "id": "KXbZt-FNVnrS"
+            },
+            "outputs": [],
+            "source": [
+                "# Close JSONSink\n",
+                "json_sink.write_and_close()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {
+                "id": "u7Akx7aUsh75"
+            },
+            "source": [
+                "## Visualizate results of detections json data with Pandas\n",
+                "\n",
+                "Let's take a look at our resulting data with by using Pandas.\n",
+                "\n",
+                "It will also be created in your current directory with the name detections.json as well."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 14,
+            "metadata": {
+                "colab": {
+                    "base_uri": "https://localhost:8080/",
+                    "height": 424
+                },
+                "id": "Bu7AZ3QHiAqb",
+                "outputId": "f6dab963-6ac2-4055-b79b-893c100301e7"
+            },
+            "outputs": [
+                {
+                    "data": {
+                        "application/vnd.google.colaboratory.intrinsic+json": {
+                            "summary": "{\n  \"name\": \"df\",\n  \"rows\": 15829,\n  \"fields\": [\n    {\n      \"column\": \"x_min\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 526.8739960472874,\n        \"min\": -12.64497184753418,\n        \"max\": 1898.829345703125,\n        \"num_unique_values\": 11137,\n        \"samples\": [\n          1591.7908935546875,\n          1337.453125,\n          701.3184814453125\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"y_min\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 284.9995089434701,\n        \"min\": -0.33771914243698103,\n        \"max\": 1028.637451171875,\n        \"num_unique_values\": 9618,\n        \"samples\": [\n          47.191009521484375,\n          23.033039093017578,\n          44.03553009033203\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"x_max\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 527.3199046060209,\n        \"min\": 23.571643829345703,\n        \"max\": 1933.473388671875,\n        \"num_unique_values\": 11122,\n        \"samples\": [\n          746.7100219726562,\n          1432.0216064453125,\n          1901.59716796875\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"y_max\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 302.62132272340716,\n        \"min\": 79.22730255126953,\n        \"max\": 1083.3433837890625,\n        \"num_unique_values\": 9538,\n        \"samples\": [\n          301.63653564453125,\n          1079.0537109375,\n          152.47158813476562\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"class_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 0,\n        \"max\": 28,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          14,\n          26,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"confidence\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.1214256650003242,\n        \"min\": 0.40000790357589705,\n        \"max\": 0.90840470790863,\n        \"num_unique_values\": 7916,\n        \"samples\": [\n          0.59814703464508,\n          0.737265467643737,\n          0.576151430606842\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"tracker_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 75,\n        \"min\": 1,\n        \"max\": 279,\n        \"num_unique_values\": 164,\n        \"samples\": [\n          226,\n          185,\n          211\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"frame_number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 96,\n        \"min\": 1,\n        \"max\": 341,\n        \"num_unique_values\": 341,\n        \"samples\": [\n          323,\n          117,\n          114\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+                            "type": "dataframe",
+                            "variable_name": "df"
+                        },
+                        "text/html": [
+                            "\n",
+                            "  <div id=\"df-5ea81b5e-9bc4-4c00-9694-67672a5d5bdb\" class=\"colab-df-container\">\n",
+                            "    <div>\n",
+                            "<style scoped>\n",
+                            "    .dataframe tbody tr th:only-of-type {\n",
+                            "        vertical-align: middle;\n",
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+                            "    .dataframe thead th {\n",
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+                            "</style>\n",
+                            "<table border=\"1\" class=\"dataframe\">\n",
+                            "  <thead>\n",
+                            "    <tr style=\"text-align: right;\">\n",
+                            "      <th></th>\n",
+                            "      <th>x_min</th>\n",
+                            "      <th>y_min</th>\n",
+                            "      <th>x_max</th>\n",
+                            "      <th>y_max</th>\n",
+                            "      <th>class_id</th>\n",
+                            "      <th>confidence</th>\n",
+                            "      <th>tracker_id</th>\n",
+                            "      <th>frame_number</th>\n",
+                            "    </tr>\n",
+                            "  </thead>\n",
+                            "  <tbody>\n",
+                            "    <tr>\n",
+                            "      <th>0</th>\n",
+                            "      <td>1460.000000</td>\n",
+                            "      <td>469.000000</td>\n",
+                            "      <td>1544.000000</td>\n",
+                            "      <td>641.000000</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.820143</td>\n",
+                            "      <td>1</td>\n",
+                            "      <td>1</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>1</th>\n",
+                            "      <td>1447.000000</td>\n",
+                            "      <td>320.000000</td>\n",
+                            "      <td>1516.000000</td>\n",
+                            "      <td>480.000000</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.791599</td>\n",
+                            "      <td>2</td>\n",
+                            "      <td>1</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>2</th>\n",
+                            "      <td>259.000000</td>\n",
+                            "      <td>435.000000</td>\n",
+                            "      <td>326.000000</td>\n",
+                            "      <td>610.000000</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.775027</td>\n",
+                            "      <td>3</td>\n",
+                            "      <td>1</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>3</th>\n",
+                            "      <td>1142.000000</td>\n",
+                            "      <td>950.000000</td>\n",
+                            "      <td>1245.000000</td>\n",
+                            "      <td>1080.000000</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.768064</td>\n",
+                            "      <td>4</td>\n",
+                            "      <td>1</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>4</th>\n",
+                            "      <td>665.000000</td>\n",
+                            "      <td>649.000000</td>\n",
+                            "      <td>744.000000</td>\n",
+                            "      <td>851.000000</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.762994</td>\n",
+                            "      <td>5</td>\n",
+                            "      <td>1</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>...</th>\n",
+                            "      <td>...</td>\n",
+                            "      <td>...</td>\n",
+                            "      <td>...</td>\n",
+                            "      <td>...</td>\n",
+                            "      <td>...</td>\n",
+                            "      <td>...</td>\n",
+                            "      <td>...</td>\n",
+                            "      <td>...</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>15824</th>\n",
+                            "      <td>1854.766602</td>\n",
+                            "      <td>259.925568</td>\n",
+                            "      <td>1914.519043</td>\n",
+                            "      <td>442.587036</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.715025</td>\n",
+                            "      <td>278</td>\n",
+                            "      <td>341</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>15825</th>\n",
+                            "      <td>391.996429</td>\n",
+                            "      <td>470.574280</td>\n",
+                            "      <td>460.881470</td>\n",
+                            "      <td>632.927673</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.506562</td>\n",
+                            "      <td>274</td>\n",
+                            "      <td>341</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>15826</th>\n",
+                            "      <td>74.250565</td>\n",
+                            "      <td>700.197937</td>\n",
+                            "      <td>173.041855</td>\n",
+                            "      <td>893.159363</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.477815</td>\n",
+                            "      <td>262</td>\n",
+                            "      <td>341</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>15827</th>\n",
+                            "      <td>1012.475769</td>\n",
+                            "      <td>170.831772</td>\n",
+                            "      <td>1058.312744</td>\n",
+                            "      <td>297.397980</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.565866</td>\n",
+                            "      <td>239</td>\n",
+                            "      <td>341</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>15828</th>\n",
+                            "      <td>1012.560791</td>\n",
+                            "      <td>60.415718</td>\n",
+                            "      <td>1052.008911</td>\n",
+                            "      <td>175.335922</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>0.406129</td>\n",
+                            "      <td>276</td>\n",
+                            "      <td>341</td>\n",
+                            "    </tr>\n",
+                            "  </tbody>\n",
+                            "</table>\n",
+                            "<p>15829 rows \u00d7 8 columns</p>\n",
+                            "</div>\n",
+                            "    <div class=\"colab-df-buttons\">\n",
+                            "\n",
+                            "  <div class=\"colab-df-container\">\n",
+                            "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5ea81b5e-9bc4-4c00-9694-67672a5d5bdb')\"\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",
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+                            "  </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",
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+                            "      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-5ea81b5e-9bc4-4c00-9694-67672a5d5bdb 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-5ea81b5e-9bc4-4c00-9694-67672a5d5bdb');\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-78d2c252-82f9-4a1a-8fb9-de6d207bdec2\">\n",
+                            "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-78d2c252-82f9-4a1a-8fb9-de6d207bdec2')\"\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",
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+                            "    </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-78d2c252-82f9-4a1a-8fb9-de6d207bdec2 button');\n",
+                            "      quickchartButtonEl.style.display =\n",
+                            "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+                            "    })();\n",
+                            "  </script>\n",
+                            "</div>\n",
+                            "\n",
+                            "  <div id=\"id_2459ce93-06af-4ff7-93a6-0af6715837a2\">\n",
+                            "    <style>\n",
+                            "      .colab-df-generate {\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-generate: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",
+                            "      [theme=dark] .colab-df-generate {\n",
+                            "        background-color: #3B4455;\n",
+                            "        fill: #D2E3FC;\n",
+                            "      }\n",
+                            "\n",
+                            "      [theme=dark] .colab-df-generate: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",
+                            "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+                            "            title=\"Generate code using this dataframe.\"\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",
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+                            "  </svg>\n",
+                            "    </button>\n",
+                            "    <script>\n",
+                            "      (() => {\n",
+                            "      const buttonEl =\n",
+                            "        document.querySelector('#id_2459ce93-06af-4ff7-93a6-0af6715837a2 button.colab-df-generate');\n",
+                            "      buttonEl.style.display =\n",
+                            "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+                            "\n",
+                            "      buttonEl.onclick = () => {\n",
+                            "        google.colab.notebook.generateWithVariable('df');\n",
+                            "      }\n",
+                            "      })();\n",
+                            "    </script>\n",
+                            "  </div>\n",
+                            "\n",
+                            "    </div>\n",
+                            "  </div>\n"
+                        ],
+                        "text/plain": [
+                            "             x_min       y_min        x_max        y_max  class_id  \\\n",
+                            "0      1460.000000  469.000000  1544.000000   641.000000         0   \n",
+                            "1      1447.000000  320.000000  1516.000000   480.000000         0   \n",
+                            "2       259.000000  435.000000   326.000000   610.000000         0   \n",
+                            "3      1142.000000  950.000000  1245.000000  1080.000000         0   \n",
+                            "4       665.000000  649.000000   744.000000   851.000000         0   \n",
+                            "...            ...         ...          ...          ...       ...   \n",
+                            "15824  1854.766602  259.925568  1914.519043   442.587036         0   \n",
+                            "15825   391.996429  470.574280   460.881470   632.927673         0   \n",
+                            "15826    74.250565  700.197937   173.041855   893.159363         0   \n",
+                            "15827  1012.475769  170.831772  1058.312744   297.397980         0   \n",
+                            "15828  1012.560791   60.415718  1052.008911   175.335922         0   \n",
+                            "\n",
+                            "       confidence  tracker_id  frame_number  \n",
+                            "0        0.820143           1             1  \n",
+                            "1        0.791599           2             1  \n",
+                            "2        0.775027           3             1  \n",
+                            "3        0.768064           4             1  \n",
+                            "4        0.762994           5             1  \n",
+                            "...           ...         ...           ...  \n",
+                            "15824    0.715025         278           341  \n",
+                            "15825    0.506562         274           341  \n",
+                            "15826    0.477815         262           341  \n",
+                            "15827    0.565866         239           341  \n",
+                            "15828    0.406129         276           341  \n",
+                            "\n",
+                            "[15829 rows x 8 columns]"
+                        ]
+                    },
+                    "execution_count": 14,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "df = pd.read_json('detections.json')\n",
+                "df"
+            ]
+        }
+    ],
+    "metadata": {
+        "accelerator": "GPU",
+        "colab": {
+            "gpuType": "T4",
+            "provenance": []
+        },
+        "kernelspec": {
+            "display_name": "Python 3",
+            "name": "python3"
+        },
+        "language_info": {
+            "name": "python"
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 0
+}
diff --git a/docs/theme/cookbooks.html b/docs/theme/cookbooks.html
index fe01a568..8a182064 100644
--- a/docs/theme/cookbooks.html
+++ b/docs/theme/cookbooks.html
@@ -18,6 +18,9 @@
       <p class="card repo-card" data-url="/develop/notebooks/annotate-video-with-detections" data-name="Annotate Video with Detections" data-labels="INFERENCE,YOLOV8" data-version="v0.18.0" data-author="nickherrig"></p>
       <p class="card repo-card" data-url="/develop/notebooks/object-tracking" data-name="Object Tracking"  data-labels="TRACKING, ANNOTATOR" data-version="v0.18.0" data-author="nickherrig"></p>
       <p class="card repo-card" data-url="/develop/notebooks/evaluating-alignment-of-text-to-image-diffusion-models" data-name="Evaluating Alignment of Text-to-image Diffusion Models"  data-labels="ANNOTATORS,YOLO WORLD" data-version="v0.19.0rc5" data-author="iamhatesz"></p>
+      <p class="card repo-card" data-url="/develop/notebooks/serialise-detections-to-csv" data-name="Serialise Detections to a CSV File"  data-labels="DETECTIONS,CSV SINK,INFERENCE" data-version="v0.19.0rc5" data-author="onuralpszr"></p>
+      <p class="card repo-card" data-url="/develop/notebooks/serialise-detections-to-json" data-name="Serialise Detections to a JSON File"  data-labels="DETECTIONS,JSON SINK,INFERENCE" data-version="v0.19.0rc6" data-author="onuralpszr"></p>
+
     </div>
   </div>
 </section>