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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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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"execution_count": null
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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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},
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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."
"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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"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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"cell_type": "markdown"
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{
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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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