notebooks/2024_01_26_Create_LabelStudio_Image_Evaluation.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/michaelachmann/social-media-lab/blob/main/notebooks/2024_01_26_Create_LabelStudio_Image_Evaluation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Export to LabelStudio (Images) [![DOI](https://zenodo.org/badge/660157642.svg)](https://zenodo.org/badge/latestdoi/660157642)\n",
        "\n",
        "![Notes on (Computational) Social Media Research Banner](https://raw.githubusercontent.com/michaelachmann/social-media-lab/main/images/banner.png)\n",
        "\n",
        "## Overview\n",
        "\n",
        "This Jupyter notebook is a part of the social-media-lab.net project, which is a work-in-progress textbook on computational social media analysis. The notebook is intended for use in my classes.\n",
        "\n",
        "The **Export to LabelStudio (Images)** Notebook provides an automated workflow to create annotation projects and to automatically import **images**. Images are automatically stored on Google Cloud Buckets.\n",
        "\n",
        "### Project Information\n",
        "\n",
        "- Project Website: [social-media-lab.net](https://social-media-lab.net/)\n",
        "- GitHub Repository: [https://github.com/michaelachmann/social-media-lab](https://github.com/michaelachmann/social-media-lab)\n",
        "\n",
        "## License Information\n",
        "\n",
        "This notebook, along with all other notebooks in the project, is licensed under the following terms:\n",
        "\n",
        "- License: [GNU General Public License version 3.0 (GPL-3.0)](https://www.gnu.org/licenses/gpl-3.0.de.html)\n",
        "- License File: [LICENSE.md](https://github.com/michaelachmann/social-media-lab/blob/main/LICENSE.md)\n",
        "\n",
        "\n",
        "## Citation\n",
        "\n",
        "If you use or reference this notebook in your work, please cite it appropriately. Here is an example of the citation:\n",
        "\n",
        "```\n",
        "Michael Achmann. (2024). michaelachmann/social-media-lab: 2023-01-29 (v0.0.11). Zenodo. https://doi.org/10.5281/zenodo.8199901\n",
        "```"
      ],
      "metadata": {
        "id": "voKy2rVy7PlL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip -q install label-studio-sdk gcloud"
      ],
      "metadata": {
        "id": "J1sLoUSsXzS4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a81dd24b-23cb-4f38-9cdc-ea98d56f6eee"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/454.4 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━\u001b[0m \u001b[32m348.2/454.4 kB\u001b[0m \u001b[31m10.2 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m454.4/454.4 kB\u001b[0m \u001b[31m9.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for gcloud (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title ## Gcloud Setup\n",
        "#@markdown Please specify the file path for the credentials file in order to upload images to google cloud bucket.\n",
        "\n",
        "import json\n",
        "from gcloud import storage\n",
        "from oauth2client.service_account import ServiceAccountCredentials\n",
        "\n",
        "gcloud_credentials_path = '/content/vsma-course-2324-72da2075ad3a.json' #@param {type: \"string\"}\n",
        "gcloud_bucket = 'label-studio-vsma' #@param {type: \"string\"}\n",
        "\n",
        "with open(gcloud_credentials_path, 'rb') as f:\n",
        "  credentials_dict = json.loads(f.read())\n",
        "\n",
        "credentials = ServiceAccountCredentials.from_json_keyfile_dict(\n",
        "    credentials_dict\n",
        ")\n",
        "client = storage.Client(credentials=credentials, project='local-grove-153811')\n",
        "bucket = client.get_bucket(gcloud_bucket)"
      ],
      "metadata": {
        "cellView": "form",
        "id": "x5lmfWEOVdai"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Let's read the dataframe from previous sessions"
      ],
      "metadata": {
        "id": "NBow_A02gg8j"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "i9hkqOpUb8kQ"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "\n",
        "df = pd.read_csv('/content/drive/MyDrive/2024-01-19-AfD-Stories-Exported.csv')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "id": "0-yb8_tRWN1u",
        "outputId": "673caec9-4a2f-4cec-b0f9-1e132190e9e5"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Unnamed: 0.3  Unnamed: 0.2  Unnamed: 0.1  Unnamed: 0  \\\n",
              "0             0             0             0           1   \n",
              "1             1             1             1           2   \n",
              "2             2             2             2           3   \n",
              "3             3             3             3           4   \n",
              "4             4             4             4           5   \n",
              "\n",
              "                               ID      Time of Posting Type of Content  \\\n",
              "0  2125373886060513565_1484534097  2019-09-04 08:05:27           Image   \n",
              "1  2125374701022077222_1484534097  2019-09-04 08:07:04           Image   \n",
              "2  2490851226217175299_1484534097  2021-01-20 14:23:30           Image   \n",
              "3  2600840011884997131_1484534097  2021-06-21 08:31:45           Image   \n",
              "4  2600852794831609459_1484534097  2021-06-21 08:57:09           Image   \n",
              "\n",
              "   video_url  image_url  Username  ...  Is Verified Stickers  \\\n",
              "0        NaN        NaN  afd.bund  ...         True       []   \n",
              "1        NaN        NaN  afd.bund  ...         True       []   \n",
              "2        NaN        NaN  afd.bund  ...         True       []   \n",
              "3        NaN        NaN  afd.bund  ...         True       []   \n",
              "4        NaN        NaN  afd.bund  ...         True       []   \n",
              "\n",
              "                               Accessibility Caption  Attribution URL  \\\n",
              "0  Photo by Alternative für Deutschland on Septem...              NaN   \n",
              "1  Photo by Alternative für Deutschland on Septem...              NaN   \n",
              "2  Photo by Alternative für Deutschland on Januar...              NaN   \n",
              "3  Photo by Alternative für Deutschland on June 2...              NaN   \n",
              "4  Photo by Alternative für Deutschland in Berlin...              NaN   \n",
              "\n",
              "                                          image_path  \\\n",
              "0  /content/media/images/afd.bund/212537388606051...   \n",
              "1  /content/media/images/afd.bund/212537470102207...   \n",
              "2  /content/media/images/afd.bund/249085122621717...   \n",
              "3  /content/media/images/afd.bund/260084001188499...   \n",
              "4  /content/media/images/afd.bund/260085279483160...   \n",
              "\n",
              "                                                 OCR  \\\n",
              "0         FACEBOOK\\nAfD\\nf\\nSwipe up\\nund werde Fan!   \n",
              "1         YOUTUBE\\nAfD\\nSwipe up\\nund abonniere uns!   \n",
              "2            TELEGRAM\\nAfD\\nSwipe up\\nund folge uns!   \n",
              "3                                          Pol\\nBeih   \n",
              "4  BERLIN, GERMANY\\n2160 25.000\\nMON 422 150M\\nA0...   \n",
              "\n",
              "                                           Objects  \\\n",
              "0                                              NaN   \n",
              "1                                              NaN   \n",
              "2                                              NaN   \n",
              "3  3x Person, 1x Chair, 1x Table, 1x Picture frame   \n",
              "4           4x Person, 1x Furniture, 1x Television   \n",
              "\n",
              "                                             caption  \\\n",
              "0  a collage of a picture of a person flying a kite    \n",
              "1                 a poster of a man with a red face    \n",
              "2           a large blue and white photo of a plane    \n",
              "3           a woman sitting at a desk with a laptop    \n",
              "4      a man sitting in front of a screen with a tv    \n",
              "\n",
              "                                      Vertex Caption  \\\n",
              "0  an ad for facebook shows a drawing of a facebo...   \n",
              "1  an advertisement for youtube with a red backgr...   \n",
              "2  an advertisement for telegram with a blue back...   \n",
              "3  two women are sitting at a table talking to ea...   \n",
              "4  a camera is recording a man sitting at a table...   \n",
              "\n",
              "                               Ensemble  \n",
              "0  Digital and Social Media Campaigning  \n",
              "1  Digital and Social Media Campaigning  \n",
              "2  Digital and Social Media Campaigning  \n",
              "3                     Public Engagement  \n",
              "4         Traditional Media Campaigning  \n",
              "\n",
              "[5 rows x 23 columns]"
            ],
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              "      <th></th>\n",
              "      <th>Unnamed: 0.3</th>\n",
              "      <th>Unnamed: 0.2</th>\n",
              "      <th>Unnamed: 0.1</th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>ID</th>\n",
              "      <th>Time of Posting</th>\n",
              "      <th>Type of Content</th>\n",
              "      <th>video_url</th>\n",
              "      <th>image_url</th>\n",
              "      <th>Username</th>\n",
              "      <th>...</th>\n",
              "      <th>Is Verified</th>\n",
              "      <th>Stickers</th>\n",
              "      <th>Accessibility Caption</th>\n",
              "      <th>Attribution URL</th>\n",
              "      <th>image_path</th>\n",
              "      <th>OCR</th>\n",
              "      <th>Objects</th>\n",
              "      <th>caption</th>\n",
              "      <th>Vertex Caption</th>\n",
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              "      <td>2019-09-04 08:05:27</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>afd.bund</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>/content/media/images/afd.bund/212537388606051...</td>\n",
              "      <td>FACEBOOK\\nAfD\\nf\\nSwipe up\\nund werde Fan!</td>\n",
              "      <td>NaN</td>\n",
              "      <td>a collage of a picture of a person flying a kite</td>\n",
              "      <td>an ad for facebook shows a drawing of a facebo...</td>\n",
              "      <td>Digital and Social Media Campaigning</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>2125374701022077222_1484534097</td>\n",
              "      <td>2019-09-04 08:07:04</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>/content/media/images/afd.bund/212537470102207...</td>\n",
              "      <td>YOUTUBE\\nAfD\\nSwipe up\\nund abonniere uns!</td>\n",
              "      <td>NaN</td>\n",
              "      <td>a poster of a man with a red face</td>\n",
              "      <td>an advertisement for youtube with a red backgr...</td>\n",
              "      <td>Digital and Social Media Campaigning</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>2490851226217175299_1484534097</td>\n",
              "      <td>2021-01-20 14:23:30</td>\n",
              "      <td>Image</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>afd.bund</td>\n",
              "      <td>...</td>\n",
              "      <td>True</td>\n",
              "      <td>[]</td>\n",
              "      <td>Photo by Alternative für Deutschland on Januar...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>/content/media/images/afd.bund/249085122621717...</td>\n",
              "      <td>TELEGRAM\\nAfD\\nSwipe up\\nund folge uns!</td>\n",
              "      <td>NaN</td>\n",
              "      <td>a large blue and white photo of a plane</td>\n",
              "      <td>an advertisement for telegram with a blue back...</td>\n",
              "      <td>Digital and Social Media Campaigning</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>2600840011884997131_1484534097</td>\n",
              "      <td>2021-06-21 08:31:45</td>\n",
              "      <td>Image</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>afd.bund</td>\n",
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              "      <td>True</td>\n",
              "      <td>[]</td>\n",
              "      <td>Photo by Alternative für Deutschland on June 2...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>/content/media/images/afd.bund/260084001188499...</td>\n",
              "      <td>Pol\\nBeih</td>\n",
              "      <td>3x Person, 1x Chair, 1x Table, 1x Picture frame</td>\n",
              "      <td>a woman sitting at a desk with a laptop</td>\n",
              "      <td>two women are sitting at a table talking to ea...</td>\n",
              "      <td>Public Engagement</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>2600852794831609459_1484534097</td>\n",
              "      <td>2021-06-21 08:57:09</td>\n",
              "      <td>Image</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>afd.bund</td>\n",
              "      <td>...</td>\n",
              "      <td>True</td>\n",
              "      <td>[]</td>\n",
              "      <td>Photo by Alternative für Deutschland in Berlin...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>/content/media/images/afd.bund/260085279483160...</td>\n",
              "      <td>BERLIN, GERMANY\\n2160 25.000\\nMON 422 150M\\nA0...</td>\n",
              "      <td>4x Person, 1x Furniture, 1x Television</td>\n",
              "      <td>a man sitting in front of a screen with a tv</td>\n",
              "      <td>a camera is recording a man sitting at a table...</td>\n",
              "      <td>Traditional Media Campaigning</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 23 columns</p>\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
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              "\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
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              "    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",
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              "    20% {\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    60% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
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              "  }\n",
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              "\n",
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              "    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",
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              "    (() => {\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "And let's unzip the images"
      ],
      "metadata": {
        "id": "odjm4eiGWJB7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip /content/drive/MyDrive/2024-01-19-AfD-Stories-Exported.zip"
      ],
      "metadata": {
        "id": "O8tOTxu3WKby"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Upload files to Cloud Bucket\n",
        "\n",
        "We're using the naming convention `{cloud-bucket}/{username}/{id}.jpg`. The naming convention is important, as we will use it later on to map the manual and computational annotations into one dataframe. (See *Identifier* in the text annotation project)."
      ],
      "metadata": {
        "id": "5_Y1fcN9WVLn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Image\"] =  df.apply(lambda row: \"gs://{}/{}/{}.jpg\".format(gcloud_bucket, row['Username'], row['ID']), axis=1)"
      ],
      "metadata": {
        "id": "kt4YCvMOZAhv"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from tqdm.notebook import tqdm\n",
        "\n",
        "df[\"Image\"] = \"gs://{}/{}/{}.jpg\".format(gcloud_bucket, df['Username'], df['ID'])\n",
        "\n",
        "uploaded_count = 0\n",
        "skipped_count = 0\n",
        "\n",
        "# Use tqdm for progress bar\n",
        "for row in tqdm(df.itertuples(), total=len(df), desc=\"Uploading Images\"):\n",
        "    filename = \"{}/{}.jpg\".format(row.Username, row.ID)\n",
        "    source_filename = row.image_path\n",
        "    blob = bucket.blob(filename)\n",
        "\n",
        "    if not blob.exists(client):\n",
        "        try:\n",
        "            blob.upload_from_filename(source_filename)\n",
        "            uploaded_count += 1\n",
        "        except FileNotFoundError:\n",
        "            print(f\"Uploading {source_filename} failed: Missing File\")\n",
        "    else:\n",
        "        skipped_count += 1\n",
        "\n",
        "print()\n",
        "print(f\"Uploaded {uploaded_count} images successfully, skipped {skipped_count} existing files.\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 223,
          "referenced_widgets": [
            "7d4bfe0e8b0c40b69c701ee4b4f1bffb",
            "28333a2033254e4e8f71f81a674003e9",
            "1b967cc3b1904d8b9698a6b08f24b488",
            "c0e1274c16b74061b2441286890255fb",
            "73bbc1abedb44f6e880d49dac13e5102",
            "6d4eab2924de44babf37cdaff20b9051",
            "9d20a49908ac4ce183a2124e437bcaf1",
            "6574cc570cf24127998befb452ed38ae",
            "88391ba3126c4f619de3e560f13597c2",
            "95374b20ea824cb2bb06a82855ec2fbf",
            "f5e94238277b43119253eeb6b2a61aeb"
          ]
        },
        "id": "rVUyFbyAWXF2",
        "outputId": "003ccb57-bdf3-4ba3-d819-eeade5877a1f"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Uploading Images:   0%|          | 0/180 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7d4bfe0e8b0c40b69c701ee4b4f1bffb"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Uploading /content/media/images/afd.bund/2632909594311219564_1484534097.jpg failed: Missing File\n",
            "Uploading /content/media/images/afd.bund/2637169242765597715_1484534097.jpg failed: Missing File\n",
            "Uploading /content/media/images/afd.bund/2637310044636651340_1484534097.jpg failed: Missing File\n",
            "Uploading /content/media/images/afd.bund/2640856259194124126_1484534097.jpg failed: Missing File\n",
            "Uploading /content/media/images/afd.bund/2643802824089930195_1484534097.jpg failed: Missing File\n",
            "Uploading /content/media/images/afd.bund/2653863205891438589_1484534097.jpg failed: Missing File\n",
            "Uploading /content/media/images/afd.bund/2664113842957989541_1484534097.jpg failed: Missing File\n",
            "Uploading /content/media/images/afd.bund/2671444844831156334_1484534097.jpg failed: Missing File\n",
            "\n",
            "Uploaded 1 images successfully, skipped 171 existing files.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title ## LabelStudio Setup\n",
        "#@markdown Please specify the the URL and API-Key for you LabelStudio Instance.\n",
        "import json\n",
        "from google.colab import userdata\n",
        "\n",
        "labelstudio_key_name = \"label2-key\" #@param {type: \"string\"}\n",
        "labelstudio_key = userdata.get(labelstudio_key_name)\n",
        "labelstudio_url = \"https://label2.digitalhumanities.io\" #@param {type: \"string\"}"
      ],
      "metadata": {
        "cellView": "form",
        "id": "71Cj4_19X3AV"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Export to LabelStudio"
      ],
      "metadata": {
        "id": "YhkLOWLnYQlI"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Create LabelStudio Interface\n",
        "Before creating the LabelStudio project you will need to define your labelling interface. Once the project is set up you will only be able to edit the interface in LabelStudio."
      ],
      "metadata": {
        "id": "NyWtV-3PDxn3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "interface = \"\"\"\n",
        "<View style=\"display:flex;\">\n",
        "  <View style=\"flex:33%\">\n",
        "    <Image name=\"Image\" value=\"$Image\"/>\n",
        "  </View>\n",
        "  <View style=\"flex:66%\">\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "kVhp0vEGE4an"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title ### Codes\n",
        "#@markdown Do you want add codes (Classification) to the images? Please name your coding instance and add options. <br/> **By running this cell multiple times you're able to add multiple variables (not recommended)**\n",
        "\n",
        "coding_name = \"Sentiment\" #@param {type:\"string\"}\n",
        "coding_values = \"Positive,Neutral,Negative\" #@param {type:\"string\"}\n",
        "coding_choice = \"single\" #@param [\"single\", \"multiple\"]\n",
        "\n",
        "coding_interface = '<Header value=\"{}\" /><Choices name=\"{}\" choice=\"{}\" toName=\"Image\">'.format(coding_name, coding_name,coding_choice)\n",
        "\n",
        "for value in coding_values.split(\",\"):\n",
        "  value = value.strip()\n",
        "  coding_interface += '<Choice value=\"{}\" />'.format(value)\n",
        "\n",
        "coding_interface += \"</Choices>\"\n",
        "\n",
        "interface += coding_interface\n",
        "\n",
        "print(\"Added {}\".format(coding_name))"
      ],
      "metadata": {
        "id": "iYYcR7nnIaj7",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7bd1e76c-12c3-4d7f-a842-6e2156f941ee"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Added Sentiment\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Don't forget to run the next line! It closes the interface XML!**"
      ],
      "metadata": {
        "id": "KJPxxRGZQvwe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "interface += \"\"\"\n",
        "        </View>\n",
        "    </View>\n",
        "    \"\"\""
      ],
      "metadata": {
        "id": "I1B_JTpMUbjy"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title ## Create LabelStudio Project\n",
        "#@markdown In this step we will create a LabelStudio project and configure cloud storage and the interface.\n",
        "#@markdown The `Image` column should contain the exact location of the image in form of a Cloud Bucket URL: `gs://cloud-bucket/filename`.\n",
        "from label_studio_sdk import Client\n",
        "import contextlib\n",
        "import io\n",
        "\n",
        "project_name = \"vSMA Image Test 1\"  #@param {type: \"string\"}\n",
        "identifier_column = \"ID\"  #@param {type: \"string\"}\n",
        "#@markdown Percentage for drawing a sample to annotate, e.g. 30%\n",
        "sample_percentage = 30  #@param {type: \"number\", min:0, max:100}\n",
        "#@markdown Number of project copies. **Start testing with 1!**\n",
        "num_copies = 1  #@param {type: \"number\", min:0, max:3}\n",
        "\n",
        "sample_size = round(len(df) * (sample_percentage / 100))\n",
        "\n",
        "ls = Client(url=labelstudio_url, api_key=labelstudio_key)\n",
        "\n",
        "\n",
        "# Import all tasks\n",
        "df_tasks = df[[identifier_column, 'Image']]\n",
        "df_tasks = df_tasks.sample(sample_size)\n",
        "df_tasks = df_tasks.fillna(\"\")\n",
        "\n",
        "for i in range(0, num_copies):\n",
        "  project_name = f\"{project_name} #{i}\"\n",
        "  # Create the project\n",
        "  project = ls.start_project(\n",
        "      title=project_name,\n",
        "      label_config=interface,\n",
        "      sampling=\"Uniform sampling\"\n",
        "  )\n",
        "  # Configure Cloud Storage (in order to be able to view the images)\n",
        "  project.connect_google_import_storage(bucket=gcloud_bucket, google_application_credentials=json.dumps(credentials_dict))\n",
        "\n",
        "\n",
        "  with contextlib.redirect_stdout(io.StringIO()):\n",
        "    project.import_tasks(\n",
        "          df_tasks.to_dict('records')\n",
        "        )\n",
        "\n",
        "  print(f\"All done, created project #{i}! Visit {labelstudio_url}/projects/{project.id}/ and get started labelling!\")\n",
        "\n"
      ],
      "metadata": {
        "id": "Uyvam3dH7uB5",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}