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| Sphinx==3.4.3 | ||
| Sphinx==4.5.0 | ||
| sphinxcontrib-napoleon==0.7 | ||
| sphinx-rtd-theme==0.5.1 |
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "db768cda", | ||
| "metadata": { | ||
| "id": "db768cda" | ||
| }, | ||
| "source": [ | ||
| "<td>\n", | ||
| " <a target=\"_blank\" href=\"https://labelbox.com\" ><img src=\"https://labelbox.com/blog/content/images/2021/02/logo-v4.svg\" width=256/></a>\n", | ||
| "</td>" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "cb5611d0", | ||
| "metadata": { | ||
| "id": "cb5611d0" | ||
| }, | ||
| "source": [ | ||
| "<td>\n", | ||
| "<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/develop/examples/basics/data_rows.ipynb\" target=\"_blank\"><img\n", | ||
| "src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"></a>\n", | ||
| "</td>\n", | ||
| "\n", | ||
| "<td>\n", | ||
| "<a href=\"https://github.com/Labelbox/labelbox-python/tree/develop/examples/basics/data_rows.ipynb\" target=\"_blank\"><img\n", | ||
| "src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n", | ||
| "</td>" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "## Batches (*Currently in Public Beta*)" | ||
| ], | ||
| "metadata": { | ||
| "id": "Lup2QNWjaxKg" | ||
| }, | ||
| "id": "Lup2QNWjaxKg" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "* A Batch is collection of datarows picked out of a Data Set.\n", | ||
| "* A Datarow cannot be part of more than one batch in a project.\n", | ||
| "* Batches work for all data types, but there should only be one data type per batch.\n", | ||
| "* Batches may not be shared between projects.\n", | ||
| "* Batches may have Datarows from multiple Datasets.\n", | ||
| "* Datarows can only be attached to a Project as part of a single Batch.\n", | ||
| "* You can set priority for each Batch." | ||
| ], | ||
| "metadata": { | ||
| "id": "KONWmRQkadPf" | ||
| }, | ||
| "id": "KONWmRQkadPf" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "id": "HoW5ypnyzpqb" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "!pip install labelbox[data]" | ||
| ], | ||
| "id": "HoW5ypnyzpqb" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "id": "6-Us9Gj1zpqc" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from labelbox import DataRow, Client\n", | ||
| "import random" | ||
| ], | ||
| "id": "6-Us9Gj1zpqc" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "qQiozm-dzpqd" | ||
| }, | ||
| "source": [ | ||
| "Set the following cell with your data to run this notebook:" | ||
| ], | ||
| "id": "qQiozm-dzpqd" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "id": "84Zna5c0zpqd" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "PROJECT_NAME = \"Batch Queue Demo\" #text project\n", | ||
| "DATASET_NAME = \"Batch Queue Demo Data\"" | ||
| ], | ||
| "id": "84Zna5c0zpqd" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "b0b09aee", | ||
| "metadata": { | ||
| "id": "b0b09aee" | ||
| }, | ||
| "source": [ | ||
| "# API Key and Client\n", | ||
| "Provide a valid api key below in order to properly connect to the Labelbox Client." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "id": "Ge-dfNh-zpqe" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Add your api key\n", | ||
| "API_KEY = None\n", | ||
| "client = Client(api_key=API_KEY)" | ||
| ], | ||
| "id": "Ge-dfNh-zpqe" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "id": "nMVtBYQmzpqe" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "dataset = client.create_dataset(name=DATASET_NAME)\n", | ||
| "\n", | ||
| "uploads = []\n", | ||
| "for i in range(10):\n", | ||
| " uploads.append({\n", | ||
| " 'external_id': i,\n", | ||
| " 'row_data': 'https://picsum.photos/200/300'\n", | ||
| " })\n", | ||
| "dataset.create_data_rows(uploads)" | ||
| ], | ||
| "id": "nMVtBYQmzpqe" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "# Ensure project is in batch mode:" | ||
| ], | ||
| "metadata": { | ||
| "id": "61CvCD3C7qv6" | ||
| }, | ||
| "id": "61CvCD3C7qv6" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "project = client.create_project(name=PROJECT_NAME)\n", | ||
| "project.update(queue_mode=project.QueueMode.Batch)" | ||
| ], | ||
| "metadata": { | ||
| "id": "tqtT4q31787T" | ||
| }, | ||
| "id": "tqtT4q31787T", | ||
| "execution_count": null, | ||
| "outputs": [] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "# Collect Datarow id's:" | ||
| ], | ||
| "metadata": { | ||
| "id": "Xti9AoZWELrq" | ||
| }, | ||
| "id": "Xti9AoZWELrq" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "### Select All Data Rows from dataset." | ||
| ], | ||
| "metadata": { | ||
| "id": "9JVLsXdevywS" | ||
| }, | ||
| "id": "9JVLsXdevywS" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "data_rows = [dr.uid for dr in list(dataset.export_data_rows())]" | ||
| ], | ||
| "metadata": { | ||
| "id": "U4C1ZyJ2EgTS" | ||
| }, | ||
| "id": "U4C1ZyJ2EgTS", | ||
| "execution_count": null, | ||
| "outputs": [] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "### Randomly sample\n", | ||
| "\n", | ||
| "Rather than selecting all of the data we sample 5 data rows at random" | ||
| ], | ||
| "metadata": { | ||
| "id": "B0UqO_O1V8ei" | ||
| }, | ||
| "id": "B0UqO_O1V8ei" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "sample = random.sample(data_rows, 5)" | ||
| ], | ||
| "metadata": { | ||
| "id": "WJAXBf1bV-td" | ||
| }, | ||
| "id": "WJAXBf1bV-td", | ||
| "execution_count": null, | ||
| "outputs": [] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "# Batch Manipulation" | ||
| ], | ||
| "metadata": { | ||
| "id": "UPdaTqkgYyvt" | ||
| }, | ||
| "id": "UPdaTqkgYyvt" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "### Create a Batch:" | ||
| ], | ||
| "metadata": { | ||
| "id": "Al-K1lBBEjtb" | ||
| }, | ||
| "id": "Al-K1lBBEjtb" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "batch = project.create_batch(\n", | ||
| " \"first batch\", # Each batch in a project must have a unique name\n", | ||
| " sample, # A list of data rows or data row ids\n", | ||
| " 5 # priority between 1(Highest) - 5(lowest)\n", | ||
| ")" | ||
| ], | ||
| "metadata": { | ||
| "id": "resH3xqeErVv" | ||
| }, | ||
| "id": "resH3xqeErVv", | ||
| "execution_count": null, | ||
| "outputs": [] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "# number of data rows in the batch\n", | ||
| "batch.size" | ||
| ], | ||
| "metadata": { | ||
| "id": "gFio7ONOWYdJ" | ||
| }, | ||
| "id": "gFio7ONOWYdJ", | ||
| "execution_count": null, | ||
| "outputs": [] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "8Cj64Isxzpqe" | ||
| }, | ||
| "source": [ | ||
| "### List DataRows in a Batch (Not supported yet)\n", | ||
| "Note: You can view your batch through in the Data Row table of the project" | ||
| ], | ||
| "id": "8Cj64Isxzpqe" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "rU7iddSQzpqg" | ||
| }, | ||
| "source": [ | ||
| "### Remove queued data rows by batch (Not supported yet)\n", | ||
| "Note: You can do this through the batch management pane on the data rows tab of the project" | ||
| ], | ||
| "id": "rU7iddSQzpqg" | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.8.5" | ||
| }, | ||
| "colab": { | ||
| "name": "Batches.ipynb", | ||
| "provenance": [], | ||
| "collapsed_sections": [] | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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