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‎examples/integrations/yolo/import_yolo_annotations.ipynb

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{
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"nbformat": 4,
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"nbformat_minor": 2,
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"metadata": {},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<td>\n",
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" <a target=\"_blank\" href=\"https://labelbox.com\" ><img src=\"https://labelbox.com/blog/content/images/2021/02/logo-v4.svg\" width=256/></a>\n",
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"<td>",
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" <a target=\"_blank\" href=\"https://labelbox.com\" ><img src=\"https://labelbox.com/blog/content/images/2021/02/logo-v4.svg\" width=256/></a>",
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"</td>\n"
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]
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],
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"cell_type": "markdown"
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<td>\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/tree/develop/examples/integrations/yolo/import_yolo_annotations.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n",
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"</td>"
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]
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],
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"cell_type": "markdown"
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Import YOLOv8 annotations\n",
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"* Setting up our ontology that matches our YOLOv8 annotations\n",
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"* Importing our data rows and attaching our ontology to a project\n",
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"* Running our images through Ultralytics then importing the annotations generated\n"
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]
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],
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"cell_type": "markdown"
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Set up"
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]
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],
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"cell_type": "markdown"
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"source": "%pip install -q --upgrade \"labelbox[data]\"\n%pip install -q --upgrade ultralytics",
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"cell_type": "code",
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"outputs": [],
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"source": [
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"%pip install -q --upgrade \"labelbox[data]\"\n",
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"%pip install -q --upgrade ultralytics"
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]
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"execution_count": null
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"source": "import labelbox as lb\nimport labelbox.types as lb_types\nimport uuid\nimport ultralytics\nfrom ultralytics.engine.model import Model\nfrom ultralytics.engine.results import Results",
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"cell_type": "code",
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"outputs": [],
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"source": [
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"import labelbox as lb\n",
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"import labelbox.types as lb_types\n",
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"import uuid\n",
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"import ultralytics\n",
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"from ultralytics.engine.model import Model\n",
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"from ultralytics.engine.results import Results"
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]
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## API key and client\n",
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"Provide a valid API key below in order to properly connect to the Labelbox client. Please review [Create API key guide](https://docs.labelbox.com/reference/create-api-key) for more information."
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]
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],
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"cell_type": "markdown"
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"source": "API_KEY = None\nclient = lb.Client(api_key=API_KEY)",
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"cell_type": "code",
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"outputs": [],
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"source": [
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"API_KEY = None\n",
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"client = lb.Client(api_key=API_KEY)"
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]
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Example: Import YOLOv8 Annotations\n",
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"\n",
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"The first few steps of this guide will demonstrating a basic workflow of creating data rows and setting up a project. For a quick complete overview of this process visit our [Quick start](https://docs.labelbox.com/reference/quick-start) guide."
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]
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],
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"cell_type": "markdown"
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Importing an image data row\n",
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"\n",
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"We will be using this [image](https://storage.googleapis.com/labelbox-datasets/image_sample_data/2560px-Kitano_Street_Kobe01s5s4110.jpeg) to be annotated with YOLOv8. Which has a lot of objects that can be picked up by YOLOv8. Later in this guide we will go into more detail on the exact annotations."
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]
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],
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"cell_type": "markdown"
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"source": "# create data row\ndata_row = {\n \"row_data\":\n \"https://storage.googleapis.com/labelbox-datasets/image_sample_data/2560px-Kitano_Street_Kobe01s5s4110.jpeg\",\n \"global_key\":\n str(uuid.uuid4()),\n \"media_type\":\n \"IMAGE\",\n}\n\n# create dataset and import data row\ndataset = client.create_dataset(name=\"YOLOv8 Demo Dataset\")\ntask = dataset.create_data_rows([data_row])\ntask.wait_till_done()\n\nprint(f\"Errors: {task.errors}\")",
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"cell_type": "code",
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"outputs": [],
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"source": [
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"# create data row\n",
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"data_row = {\n",
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" \"row_data\":\n",
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" \"https://storage.googleapis.com/labelbox-datasets/image_sample_data/2560px-Kitano_Street_Kobe01s5s4110.jpeg\",\n",
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" \"global_key\":\n",
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" str(uuid.uuid4()),\n",
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" \"media_type\":\n",
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" \"IMAGE\",\n",
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"}\n",
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"\n",
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"# create dataset and import data row\n",
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"dataset = client.create_dataset(name=\"YOLOv8 Demo Dataset\")\n",
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"task = dataset.create_data_rows([data_row])\n",
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"task.wait_till_done()\n",
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"\n",
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"print(f\"Errors: {task.errors}\")"
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]
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Setting up an ontology and a project\n"
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]
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],
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"cell_type": "markdown"
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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]
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}

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