dataset_splitting.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<a href=\"https://colab.research.google.com/github//pylabel-project/samples/blob/main/dataset_splitting.ipynb\" target=\"_blank\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a> "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cxi8K9mXwl5t"
      },
      "source": [
        "# Splitting Images Datasets with PyLabel\n",
        "This notebook demonstrates how to use the splitting capabilities of PyLabel split an image dataset (with images and annotations) into train, val, and test groups.\n",
        "\n",
        "Splitting image datasets is trickier than splitting a simple table of data because you need to ensure that all of the labels for a particular image stay in the same split as the image (with no leakage) and you have to split the images as well as the annotations. \n",
        "\n",
        "PyLabel has 2 methods for splitting data: \n",
        "1)\t**GroupShuffleSplit**, which uses the GroupShuffleSplit command from sklearn.\n",
        "2)\t**StratifiedGroupShuffleSplit**, which attempts to balance the distribution of classes evenly across the split groups. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "import logging\n",
        "logging.getLogger().setLevel(logging.CRITICAL)\n",
        "!pip install pylabel > /dev/null\n",
        "from pylabel import importer"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Import A Dataset \n",
        "First we will import dateset stored in COCO format. (This is a sample  data set. You can edit this part to point to your dataset.)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2021-12-14 22:18:21--  https://github.com/pylabelalpha/notebook/blob/main/BCCD_coco.zip?raw=true\n",
            "Resolving github.com (github.com)... 192.30.255.113\n",
            "Connecting to github.com (github.com)|192.30.255.113|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://github.com/pylabelalpha/notebook/raw/main/BCCD_coco.zip [following]\n",
            "--2021-12-14 22:18:23--  https://github.com/pylabelalpha/notebook/raw/main/BCCD_coco.zip\n",
            "Reusing existing connection to github.com:443.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://github.com/raw/pylabelalpha/notebook/main/BCCD_coco.zip [following]\n",
            "--2021-12-14 22:18:23--  https://github.com/raw/pylabelalpha/notebook/main/BCCD_coco.zip\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.110.133, 185.199.109.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 7625693 (7.3M) [application/zip]\n",
            "Saving to: ‘data/BCCD_coco.zip’\n",
            "\n",
            "data/BCCD_coco.zip  100%[===================>]   7.27M  1.92MB/s    in 4.8s    \n",
            "\n",
            "2021-12-14 22:18:28 (1.52 MB/s) - ‘data/BCCD_coco.zip’ saved [7625693/7625693]\n",
            "\n"
          ]
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>img_folder</th>\n",
              "      <th>img_filename</th>\n",
              "      <th>img_path</th>\n",
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              "      <th>img_width</th>\n",
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              "      <th>...</th>\n",
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              "      <th>cat_name</th>\n",
              "      <th>cat_supercategory</th>\n",
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              "      <th>0</th>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>13.0</td>\n",
              "      <td>...</td>\n",
              "      <td>11781.0</td>\n",
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              "      <td>None</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>RBC</td>\n",
              "      <td>None</td>\n",
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              "      <th>3</th>\n",
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              "      <td>BloodImage_00315.jpg</td>\n",
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              "      <td>640</td>\n",
              "      <td>480</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>239.0</td>\n",
              "      <td>...</td>\n",
              "      <td>11960.0</td>\n",
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              "      <td>None</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>RBC</td>\n",
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              "      <td>0</td>\n",
              "      <td>542.0</td>\n",
              "      <td>...</td>\n",
              "      <td>10290.0</td>\n",
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              "      <td>None</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "  id img_folder          img_filename img_path  img_id  img_width  img_height  \\\n",
              "0                BloodImage_00315.jpg     None       0        640         480   \n",
              "1                BloodImage_00315.jpg     None       0        640         480   \n",
              "2                BloodImage_00315.jpg     None       0        640         480   \n",
              "3                BloodImage_00315.jpg     None       0        640         480   \n",
              "4                BloodImage_00315.jpg     None       0        640         480   \n",
              "\n",
              "   img_depth ann_segmented  ann_bbox_xmin  ...  ann_area  ann_segmentation  \\\n",
              "0          3             0          164.0  ...   13699.0              None   \n",
              "1          3             0           15.0  ...   13699.0              None   \n",
              "2          3             0           13.0  ...   11781.0              None   \n",
              "3          3             0          239.0  ...   11960.0              None   \n",
              "4          3             0          542.0  ...   10290.0              None   \n",
              "\n",
              "   ann_iscrowd     ann_pose  ann_truncated  ann_difficult cat_id cat_name  \\\n",
              "0         None  Unspecified              0              0      0      RBC   \n",
              "1         None  Unspecified              0              0      0      RBC   \n",
              "2         None  Unspecified              0              0      0      RBC   \n",
              "3         None  Unspecified              0              0      0      RBC   \n",
              "4         None  Unspecified              1              0      0      RBC   \n",
              "\n",
              "  cat_supercategory split  \n",
              "0              None        \n",
              "1              None        \n",
              "2              None        \n",
              "3              None        \n",
              "4              None        \n",
              "\n",
              "[5 rows x 25 columns]"
            ]
          },
          "execution_count": 2,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import os, zipfile\n",
        "\n",
        "#Download sample  dataset \n",
        "os.makedirs(\"data\", exist_ok=True)\n",
        "!wget \"https://github.com/pylabelalpha/notebook/blob/main/BCCD_coco.zip?raw=true\" -O data/BCCD_coco.zip\n",
        "with zipfile.ZipFile(\"data/BCCD_coco.zip\", 'r') as zip_ref:\n",
        "   zip_ref.extractall(\"data\")\n",
        "\n",
        "#Specify path to the coco.json file\n",
        "path_to_annotations = \"data/BCCD_Dataset.json\"\n",
        "#Specify the path to the images (if they are in a different folder than the annotations)\n",
        "path_to_images = \"\"\n",
        "\n",
        "#Import the dataset into the pylable schema \n",
        "dataset = importer.ImportCoco(path_to_annotations, path_to_images=path_to_images, name=\"BCCD_coco\")\n",
        "dataset.df.head(5)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Analyze annotations\n",
        "Pylabel can calculate basic summary statisticts about the dataset such as the number of files and the classes. \n",
        "The dataset is stored as a pandas frame so the developer can do additional exploratory analysis on the dataset. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5R1rOJVL420b",
        "outputId": "ae94525b-c6d5-4a4f-d56d-7f1bd29a7411"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Number of images: 364\n",
            "Number of classes: 3\n",
            "Classes:['RBC' 'WBC' 'Platelets']\n",
            "Class counts:\n",
            "RBC          4155\n",
            "WBC           372\n",
            "Platelets     361\n",
            "Name: cat_name, dtype: int64\n"
          ]
        }
      ],
      "source": [
        "print(f\"Number of images: {dataset.analyze.num_images}\")\n",
        "print(f\"Number of classes: {dataset.analyze.num_classes}\")\n",
        "print(f\"Classes:{dataset.analyze.classes}\")\n",
        "print(f\"Class counts:\\n{dataset.analyze.class_counts}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Visualize Annotations \n",
        "You can render the bounding boxes for your image to inspect them and confirm that they imported correctly.  "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=640x480 at 0x7FBAA95D2D30>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from IPython.display import Image, display\n",
        "display(dataset.visualize.ShowBoundingBoxes(100))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Split Dataset Using GroupShuffleSplit\n",
        "After running the split commmand the value of the split column will be set to test, train, or val depending on what group the row was split into. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>all</th>\n",
              "      <th>train</th>\n",
              "      <th>test</th>\n",
              "      <th>val</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cat_name</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>RBC</th>\n",
              "      <td>0.850041</td>\n",
              "      <td>0.853001</td>\n",
              "      <td>0.838446</td>\n",
              "      <td>0.852761</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WBC</th>\n",
              "      <td>0.076105</td>\n",
              "      <td>0.071282</td>\n",
              "      <td>0.080777</td>\n",
              "      <td>0.085890</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Platelets</th>\n",
              "      <td>0.073854</td>\n",
              "      <td>0.075716</td>\n",
              "      <td>0.080777</td>\n",
              "      <td>0.061350</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                all     train      test       val\n",
              "cat_name                                         \n",
              "RBC        0.850041  0.853001  0.838446  0.852761\n",
              "WBC        0.076105  0.071282  0.080777  0.085890\n",
              "Platelets  0.073854  0.075716  0.080777  0.061350"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset.splitter.GroupShuffleSplit(train_pct=.6, val_pct=.2, test_pct=.2)\n",
        "dataset.analyze.ShowClassSplits()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Split Dataset Using StratifiedGroupShuffleSplit\n",
        "Note that the distribution of classes should be more balanced. Increasing the batch_size will improve performance, but may make the distribution less balanced. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>all</th>\n",
              "      <th>train</th>\n",
              "      <th>test</th>\n",
              "      <th>val</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cat_name</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>RBC</th>\n",
              "      <td>0.850041</td>\n",
              "      <td>0.850303</td>\n",
              "      <td>0.849287</td>\n",
              "      <td>0.85000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WBC</th>\n",
              "      <td>0.076105</td>\n",
              "      <td>0.075523</td>\n",
              "      <td>0.076375</td>\n",
              "      <td>0.07766</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Platelets</th>\n",
              "      <td>0.073854</td>\n",
              "      <td>0.074174</td>\n",
              "      <td>0.074338</td>\n",
              "      <td>0.07234</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                all     train      test      val\n",
              "cat_name                                        \n",
              "RBC        0.850041  0.850303  0.849287  0.85000\n",
              "WBC        0.076105  0.075523  0.076375  0.07766\n",
              "Platelets  0.073854  0.074174  0.074338  0.07234"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset.splitter.StratifiedGroupShuffleSplit(train_pct=.6, val_pct=.2, test_pct=.2, batch_size=1)\n",
        "dataset.analyze.ShowClassSplits()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Export Split Dataset\n",
        "PyLabel can export the dataset into train, test, val groups and even even create a YAML file for YOLOv5 datasets, "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['model_training/dataset.yaml',\n",
              " 'model_training/labels/train/BloodImage_00198.txt',\n",
              " 'model_training/labels/train/BloodImage_00245.txt',\n",
              " 'model_training/labels/train/BloodImage_00389.txt',\n",
              " 'model_training/labels/train/BloodImage_00016.txt',\n",
              " 'model_training/labels/train/BloodImage_00169.txt',\n",
              " 'model_training/labels/train/BloodImage_00101.txt',\n",
              " 'model_training/labels/train/BloodImage_00288.txt',\n",
              " 'model_training/labels/train/BloodImage_00023.txt',\n",
              " 'model_training/labels/train/BloodImage_00405.txt',\n",
              " 'model_training/labels/train/BloodImage_00294.txt',\n",
              " 'model_training/labels/train/BloodImage_00047.txt',\n",
              " 'model_training/labels/train/BloodImage_00403.txt',\n",
              " 'model_training/labels/train/BloodImage_00325.txt',\n",
              " 'model_training/labels/train/BloodImage_00388.txt',\n",
              " 'model_training/labels/train/BloodImage_00029.txt',\n",
              " 'model_training/labels/train/BloodImage_00000.txt',\n",
              " 'model_training/labels/train/BloodImage_00259.txt',\n",
              " 'model_training/labels/train/BloodImage_00180.txt',\n",
              " 'model_training/labels/train/BloodImage_00222.txt',\n",
              " 'model_training/labels/train/BloodImage_00273.txt',\n",
              " 'model_training/labels/train/BloodImage_00095.txt',\n",
              " 'model_training/labels/train/BloodImage_00056.txt',\n",
              " 'model_training/labels/train/BloodImage_00013.txt',\n",
              " 'model_training/labels/train/BloodImage_00335.txt',\n",
              " 'model_training/labels/train/BloodImage_00142.txt',\n",
              " 'model_training/labels/train/BloodImage_00001.txt',\n",
              " 'model_training/labels/train/BloodImage_00145.txt',\n",
              " 'model_training/labels/train/BloodImage_00296.txt',\n",
              " 'model_training/labels/train/BloodImage_00011.txt',\n",
              " 'model_training/labels/train/BloodImage_00064.txt',\n",
              " 'model_training/labels/train/BloodImage_00402.txt',\n",
              " 'model_training/labels/train/BloodImage_00112.txt',\n",
              " 'model_training/labels/train/BloodImage_00289.txt',\n",
              " 'model_training/labels/train/BloodImage_00397.txt',\n",
              " 'model_training/labels/train/BloodImage_00043.txt',\n",
              " 'model_training/labels/train/BloodImage_00014.txt',\n",
              " 'model_training/labels/train/BloodImage_00279.txt',\n",
              " 'model_training/labels/train/BloodImage_00048.txt',\n",
              " 'model_training/labels/train/BloodImage_00361.txt',\n",
              " 'model_training/labels/train/BloodImage_00018.txt',\n",
              " 'model_training/labels/train/BloodImage_00269.txt',\n",
              " 'model_training/labels/train/BloodImage_00220.txt',\n",
              " 'model_training/labels/train/BloodImage_00278.txt',\n",
              " 'model_training/labels/train/BloodImage_00002.txt',\n",
              " 'model_training/labels/train/BloodImage_00277.txt',\n",
              " 'model_training/labels/train/BloodImage_00059.txt',\n",
              " 'model_training/labels/train/BloodImage_00031.txt',\n",
              " 'model_training/labels/train/BloodImage_00308.txt',\n",
              " 'model_training/labels/train/BloodImage_00124.txt',\n",
              " 'model_training/labels/train/BloodImage_00301.txt',\n",
              " 'model_training/labels/train/BloodImage_00117.txt',\n",
              " 'model_training/labels/train/BloodImage_00345.txt',\n",
              " 'model_training/labels/train/BloodImage_00244.txt',\n",
              " 'model_training/labels/train/BloodImage_00046.txt',\n",
              " 'model_training/labels/train/BloodImage_00167.txt',\n",
              " 'model_training/labels/train/BloodImage_00368.txt',\n",
              " 'model_training/labels/train/BloodImage_00387.txt',\n",
              " 'model_training/labels/train/BloodImage_00068.txt',\n",
              " 'model_training/labels/train/BloodImage_00332.txt',\n",
              " 'model_training/labels/train/BloodImage_00097.txt',\n",
              " 'model_training/labels/train/BloodImage_00125.txt',\n",
              " 'model_training/labels/train/BloodImage_00109.txt',\n",
              " 'model_training/labels/train/BloodImage_00045.txt',\n",
              " 'model_training/labels/train/BloodImage_00201.txt',\n",
              " 'model_training/labels/train/BloodImage_00248.txt',\n",
              " 'model_training/labels/train/BloodImage_00081.txt',\n",
              " 'model_training/labels/train/BloodImage_00237.txt',\n",
              " 'model_training/labels/train/BloodImage_00028.txt',\n",
              " 'model_training/labels/train/BloodImage_00395.txt',\n",
              " 'model_training/labels/train/BloodImage_00211.txt',\n",
              " 'model_training/labels/train/BloodImage_00260.txt',\n",
              " 'model_training/labels/train/BloodImage_00226.txt',\n",
              " 'model_training/labels/train/BloodImage_00083.txt',\n",
              " 'model_training/labels/train/BloodImage_00393.txt',\n",
              " 'model_training/labels/train/BloodImage_00352.txt',\n",
              " 'model_training/labels/train/BloodImage_00022.txt',\n",
              " 'model_training/labels/train/BloodImage_00228.txt',\n",
              " 'model_training/labels/train/BloodImage_00054.txt',\n",
              " 'model_training/labels/train/BloodImage_00203.txt',\n",
              " 'model_training/labels/train/BloodImage_00184.txt',\n",
              " 'model_training/labels/train/BloodImage_00026.txt',\n",
              " 'model_training/labels/train/BloodImage_00410.txt',\n",
              " 'model_training/labels/train/BloodImage_00075.txt',\n",
              " 'model_training/labels/train/BloodImage_00282.txt',\n",
              " 'model_training/labels/train/BloodImage_00034.txt',\n",
              " 'model_training/labels/train/BloodImage_00340.txt',\n",
              " 'model_training/labels/train/BloodImage_00314.txt',\n",
              " 'model_training/labels/train/BloodImage_00317.txt',\n",
              " 'model_training/labels/train/BloodImage_00367.txt',\n",
              " 'model_training/labels/train/BloodImage_00037.txt',\n",
              " 'model_training/labels/train/BloodImage_00137.txt',\n",
              " 'model_training/labels/train/BloodImage_00249.txt',\n",
              " 'model_training/labels/train/BloodImage_00291.txt',\n",
              " 'model_training/labels/train/BloodImage_00346.txt',\n",
              " 'model_training/labels/train/BloodImage_00140.txt',\n",
              " 'model_training/labels/train/BloodImage_00218.txt',\n",
              " 'model_training/labels/train/BloodImage_00008.txt',\n",
              " 'model_training/labels/train/BloodImage_00209.txt',\n",
              " 'model_training/labels/train/BloodImage_00171.txt',\n",
              " 'model_training/labels/train/BloodImage_00391.txt',\n",
              " 'model_training/labels/train/BloodImage_00036.txt',\n",
              " 'model_training/labels/train/BloodImage_00407.txt',\n",
              " 'model_training/labels/train/BloodImage_00039.txt',\n",
              " 'model_training/labels/train/BloodImage_00309.txt',\n",
              " 'model_training/labels/train/BloodImage_00009.txt',\n",
              " 'model_training/labels/train/BloodImage_00312.txt',\n",
              " 'model_training/labels/train/BloodImage_00404.txt',\n",
              " 'model_training/labels/train/BloodImage_00065.txt',\n",
              " 'model_training/labels/train/BloodImage_00349.txt',\n",
              " 'model_training/labels/train/BloodImage_00353.txt',\n",
              " 'model_training/labels/train/BloodImage_00223.txt',\n",
              " 'model_training/labels/train/BloodImage_00381.txt',\n",
              " 'model_training/labels/train/BloodImage_00017.txt',\n",
              " 'model_training/labels/train/BloodImage_00371.txt',\n",
              " 'model_training/labels/train/BloodImage_00370.txt',\n",
              " 'model_training/labels/train/BloodImage_00052.txt',\n",
              " 'model_training/labels/train/BloodImage_00136.txt',\n",
              " 'model_training/labels/train/BloodImage_00383.txt',\n",
              " 'model_training/labels/train/BloodImage_00384.txt',\n",
              " 'model_training/labels/train/BloodImage_00409.txt',\n",
              " 'model_training/labels/train/BloodImage_00019.txt',\n",
              " 'model_training/labels/train/BloodImage_00392.txt',\n",
              " 'model_training/labels/train/BloodImage_00172.txt',\n",
              " 'model_training/labels/train/BloodImage_00348.txt',\n",
              " 'model_training/labels/train/BloodImage_00007.txt',\n",
              " 'model_training/labels/train/BloodImage_00044.txt',\n",
              " 'model_training/labels/train/BloodImage_00337.txt',\n",
              " 'model_training/labels/train/BloodImage_00356.txt',\n",
              " 'model_training/labels/train/BloodImage_00357.txt',\n",
              " 'model_training/labels/train/BloodImage_00006.txt',\n",
              " 'model_training/labels/train/BloodImage_00178.txt',\n",
              " 'model_training/labels/train/BloodImage_00010.txt',\n",
              " 'model_training/labels/train/BloodImage_00111.txt',\n",
              " 'model_training/labels/train/BloodImage_00135.txt',\n",
              " 'model_training/labels/train/BloodImage_00272.txt',\n",
              " 'model_training/labels/train/BloodImage_00398.txt',\n",
              " 'model_training/labels/train/BloodImage_00290.txt',\n",
              " 'model_training/labels/train/BloodImage_00227.txt',\n",
              " 'model_training/labels/train/BloodImage_00020.txt',\n",
              " 'model_training/labels/train/BloodImage_00239.txt',\n",
              " 'model_training/labels/train/BloodImage_00177.txt',\n",
              " 'model_training/labels/train/BloodImage_00236.txt',\n",
              " 'model_training/labels/train/BloodImage_00086.txt',\n",
              " 'model_training/labels/train/BloodImage_00302.txt',\n",
              " 'model_training/labels/train/BloodImage_00156.txt',\n",
              " 'model_training/labels/train/BloodImage_00110.txt',\n",
              " 'model_training/labels/train/BloodImage_00164.txt',\n",
              " 'model_training/labels/train/BloodImage_00050.txt',\n",
              " 'model_training/labels/train/BloodImage_00032.txt',\n",
              " 'model_training/labels/train/BloodImage_00193.txt',\n",
              " 'model_training/labels/train/BloodImage_00336.txt',\n",
              " 'model_training/labels/train/BloodImage_00257.txt',\n",
              " 'model_training/labels/train/BloodImage_00078.txt',\n",
              " 'model_training/labels/train/BloodImage_00374.txt',\n",
              " 'model_training/labels/train/BloodImage_00347.txt',\n",
              " 'model_training/labels/train/BloodImage_00024.txt',\n",
              " 'model_training/labels/train/BloodImage_00324.txt',\n",
              " 'model_training/labels/train/BloodImage_00320.txt',\n",
              " 'model_training/labels/train/BloodImage_00281.txt',\n",
              " 'model_training/labels/train/BloodImage_00379.txt',\n",
              " 'model_training/labels/train/BloodImage_00305.txt',\n",
              " 'model_training/labels/train/BloodImage_00343.txt',\n",
              " 'model_training/labels/train/BloodImage_00087.txt',\n",
              " 'model_training/labels/train/BloodImage_00217.txt',\n",
              " 'model_training/labels/train/BloodImage_00359.txt',\n",
              " 'model_training/labels/train/BloodImage_00079.txt',\n",
              " 'model_training/labels/train/BloodImage_00261.txt',\n",
              " 'model_training/labels/train/BloodImage_00354.txt',\n",
              " 'model_training/labels/train/BloodImage_00033.txt',\n",
              " 'model_training/labels/train/BloodImage_00120.txt',\n",
              " 'model_training/labels/train/BloodImage_00268.txt',\n",
              " 'model_training/labels/train/BloodImage_00161.txt',\n",
              " 'model_training/labels/train/BloodImage_00189.txt',\n",
              " 'model_training/labels/train/BloodImage_00331.txt',\n",
              " 'model_training/labels/train/BloodImage_00263.txt',\n",
              " 'model_training/labels/train/BloodImage_00114.txt',\n",
              " 'model_training/labels/train/BloodImage_00005.txt',\n",
              " 'model_training/labels/train/BloodImage_00191.txt',\n",
              " 'model_training/labels/train/BloodImage_00386.txt',\n",
              " 'model_training/labels/train/BloodImage_00040.txt',\n",
              " 'model_training/labels/train/BloodImage_00376.txt',\n",
              " 'model_training/labels/train/BloodImage_00338.txt',\n",
              " 'model_training/labels/train/BloodImage_00207.txt',\n",
              " 'model_training/labels/train/BloodImage_00067.txt',\n",
              " 'model_training/labels/train/BloodImage_00323.txt',\n",
              " 'model_training/labels/train/BloodImage_00162.txt',\n",
              " 'model_training/labels/train/BloodImage_00148.txt',\n",
              " 'model_training/labels/train/BloodImage_00159.txt',\n",
              " 'model_training/labels/train/BloodImage_00150.txt',\n",
              " 'model_training/labels/train/BloodImage_00042.txt',\n",
              " 'model_training/labels/train/BloodImage_00254.txt',\n",
              " 'model_training/labels/train/BloodImage_00342.txt',\n",
              " 'model_training/labels/train/BloodImage_00175.txt',\n",
              " 'model_training/labels/train/BloodImage_00252.txt',\n",
              " 'model_training/labels/train/BloodImage_00270.txt',\n",
              " 'model_training/labels/train/BloodImage_00066.txt',\n",
              " 'model_training/labels/train/BloodImage_00292.txt',\n",
              " 'model_training/labels/train/BloodImage_00322.txt',\n",
              " 'model_training/labels/train/BloodImage_00139.txt',\n",
              " 'model_training/labels/train/BloodImage_00071.txt',\n",
              " 'model_training/labels/train/BloodImage_00267.txt',\n",
              " 'model_training/labels/train/BloodImage_00240.txt',\n",
              " 'model_training/labels/train/BloodImage_00251.txt',\n",
              " 'model_training/labels/train/BloodImage_00126.txt',\n",
              " 'model_training/labels/train/BloodImage_00113.txt',\n",
              " 'model_training/labels/train/BloodImage_00297.txt',\n",
              " 'model_training/labels/train/BloodImage_00299.txt',\n",
              " 'model_training/labels/train/BloodImage_00310.txt',\n",
              " 'model_training/labels/train/BloodImage_00258.txt',\n",
              " 'model_training/labels/train/BloodImage_00130.txt',\n",
              " 'model_training/labels/train/BloodImage_00055.txt',\n",
              " 'model_training/labels/train/BloodImage_00224.txt',\n",
              " 'model_training/labels/train/BloodImage_00134.txt',\n",
              " 'model_training/labels/train/BloodImage_00147.txt',\n",
              " 'model_training/labels/train/BloodImage_00235.txt',\n",
              " 'model_training/labels/train/BloodImage_00350.txt',\n",
              " 'model_training/labels/train/BloodImage_00152.txt',\n",
              " 'model_training/labels/train/BloodImage_00303.txt',\n",
              " 'model_training/labels/test/BloodImage_00365.txt',\n",
              " 'model_training/labels/test/BloodImage_00364.txt',\n",
              " 'model_training/labels/test/BloodImage_00098.txt',\n",
              " 'model_training/labels/test/BloodImage_00100.txt',\n",
              " 'model_training/labels/test/BloodImage_00076.txt',\n",
              " 'model_training/labels/test/BloodImage_00072.txt',\n",
              " 'model_training/labels/test/BloodImage_00396.txt',\n",
              " 'model_training/labels/test/BloodImage_00104.txt',\n",
              " 'model_training/labels/test/BloodImage_00366.txt',\n",
              " 'model_training/labels/test/BloodImage_00166.txt',\n",
              " 'model_training/labels/test/BloodImage_00212.txt',\n",
              " 'model_training/labels/test/BloodImage_00069.txt',\n",
              " 'model_training/labels/test/BloodImage_00174.txt',\n",
              " 'model_training/labels/test/BloodImage_00341.txt',\n",
              " 'model_training/labels/test/BloodImage_00195.txt',\n",
              " 'model_training/labels/test/BloodImage_00074.txt',\n",
              " 'model_training/labels/test/BloodImage_00003.txt',\n",
              " 'model_training/labels/test/BloodImage_00216.txt',\n",
              " 'model_training/labels/test/BloodImage_00099.txt',\n",
              " 'model_training/labels/test/BloodImage_00070.txt',\n",
              " 'model_training/labels/test/BloodImage_00355.txt',\n",
              " 'model_training/labels/test/BloodImage_00202.txt',\n",
              " 'model_training/labels/test/BloodImage_00255.txt',\n",
              " 'model_training/labels/test/BloodImage_00221.txt',\n",
              " 'model_training/labels/test/BloodImage_00208.txt',\n",
              " 'model_training/labels/test/BloodImage_00041.txt',\n",
              " 'model_training/labels/test/BloodImage_00182.txt',\n",
              " 'model_training/labels/test/BloodImage_00057.txt',\n",
              " 'model_training/labels/test/BloodImage_00049.txt',\n",
              " 'model_training/labels/test/BloodImage_00093.txt',\n",
              " 'model_training/labels/test/BloodImage_00058.txt',\n",
              " 'model_training/labels/test/BloodImage_00038.txt',\n",
              " 'model_training/labels/test/BloodImage_00160.txt',\n",
              " 'model_training/labels/test/BloodImage_00232.txt',\n",
              " 'model_training/labels/test/BloodImage_00276.txt',\n",
              " 'model_training/labels/test/BloodImage_00234.txt',\n",
              " 'model_training/labels/test/BloodImage_00183.txt',\n",
              " 'model_training/labels/test/BloodImage_00230.txt',\n",
              " 'model_training/labels/test/BloodImage_00210.txt',\n",
              " 'model_training/labels/test/BloodImage_00168.txt',\n",
              " 'model_training/labels/test/BloodImage_00108.txt',\n",
              " 'model_training/labels/test/BloodImage_00144.txt',\n",
              " 'model_training/labels/test/BloodImage_00351.txt',\n",
              " 'model_training/labels/test/BloodImage_00333.txt',\n",
              " 'model_training/labels/test/BloodImage_00192.txt',\n",
              " 'model_training/labels/test/BloodImage_00103.txt',\n",
              " 'model_training/labels/test/BloodImage_00246.txt',\n",
              " 'model_training/labels/test/BloodImage_00176.txt',\n",
              " 'model_training/labels/test/BloodImage_00265.txt',\n",
              " 'model_training/labels/test/BloodImage_00053.txt',\n",
              " 'model_training/labels/test/BloodImage_00215.txt',\n",
              " 'model_training/labels/test/BloodImage_00219.txt',\n",
              " 'model_training/labels/test/BloodImage_00362.txt',\n",
              " 'model_training/labels/test/BloodImage_00408.txt',\n",
              " 'model_training/labels/test/BloodImage_00196.txt',\n",
              " 'model_training/labels/test/BloodImage_00157.txt',\n",
              " 'model_training/labels/test/BloodImage_00275.txt',\n",
              " 'model_training/labels/test/BloodImage_00089.txt',\n",
              " 'model_training/labels/test/BloodImage_00106.txt',\n",
              " 'model_training/labels/test/BloodImage_00400.txt',\n",
              " 'model_training/labels/test/BloodImage_00179.txt',\n",
              " 'model_training/labels/test/BloodImage_00187.txt',\n",
              " 'model_training/labels/test/BloodImage_00344.txt',\n",
              " 'model_training/labels/test/BloodImage_00132.txt',\n",
              " 'model_training/labels/test/BloodImage_00326.txt',\n",
              " 'model_training/labels/test/BloodImage_00090.txt',\n",
              " 'model_training/labels/test/BloodImage_00304.txt',\n",
              " 'model_training/labels/test/BloodImage_00158.txt',\n",
              " 'model_training/labels/test/BloodImage_00165.txt',\n",
              " 'model_training/labels/test/BloodImage_00163.txt',\n",
              " 'model_training/labels/test/BloodImage_00375.txt',\n",
              " 'model_training/labels/test/BloodImage_00298.txt',\n",
              " 'model_training/labels/test/BloodImage_00327.txt',\n",
              " 'model_training/labels/val/BloodImage_00266.txt',\n",
              " 'model_training/labels/val/BloodImage_00012.txt',\n",
              " 'model_training/labels/val/BloodImage_00115.txt',\n",
              " 'model_training/labels/val/BloodImage_00092.txt',\n",
              " 'model_training/labels/val/BloodImage_00088.txt',\n",
              " 'model_training/labels/val/BloodImage_00243.txt',\n",
              " 'model_training/labels/val/BloodImage_00073.txt',\n",
              " 'model_training/labels/val/BloodImage_00283.txt',\n",
              " 'model_training/labels/val/BloodImage_00077.txt',\n",
              " 'model_training/labels/val/BloodImage_00378.txt',\n",
              " 'model_training/labels/val/BloodImage_00385.txt',\n",
              " 'model_training/labels/val/BloodImage_00262.txt',\n",
              " 'model_training/labels/val/BloodImage_00313.txt',\n",
              " 'model_training/labels/val/BloodImage_00094.txt',\n",
              " 'model_training/labels/val/BloodImage_00229.txt',\n",
              " 'model_training/labels/val/BloodImage_00334.txt',\n",
              " 'model_training/labels/val/BloodImage_00030.txt',\n",
              " 'model_training/labels/val/BloodImage_00293.txt',\n",
              " 'model_training/labels/val/BloodImage_00360.txt',\n",
              " 'model_training/labels/val/BloodImage_00204.txt',\n",
              " 'model_training/labels/val/BloodImage_00231.txt',\n",
              " 'model_training/labels/val/BloodImage_00149.txt',\n",
              " 'model_training/labels/val/BloodImage_00082.txt',\n",
              " 'model_training/labels/val/BloodImage_00377.txt',\n",
              " 'model_training/labels/val/BloodImage_00247.txt',\n",
              " 'model_training/labels/val/BloodImage_00214.txt',\n",
              " 'model_training/labels/val/BloodImage_00295.txt',\n",
              " 'model_training/labels/val/BloodImage_00190.txt',\n",
              " 'model_training/labels/val/BloodImage_00015.txt',\n",
              " 'model_training/labels/val/BloodImage_00197.txt',\n",
              " 'model_training/labels/val/BloodImage_00264.txt',\n",
              " 'model_training/labels/val/BloodImage_00285.txt',\n",
              " 'model_training/labels/val/BloodImage_00256.txt',\n",
              " 'model_training/labels/val/BloodImage_00390.txt',\n",
              " 'model_training/labels/val/BloodImage_00062.txt',\n",
              " 'model_training/labels/val/BloodImage_00133.txt',\n",
              " 'model_training/labels/val/BloodImage_00319.txt',\n",
              " 'model_training/labels/val/BloodImage_00318.txt',\n",
              " 'model_training/labels/val/BloodImage_00369.txt',\n",
              " 'model_training/labels/val/BloodImage_00170.txt',\n",
              " 'model_training/labels/val/BloodImage_00311.txt',\n",
              " 'model_training/labels/val/BloodImage_00307.txt',\n",
              " 'model_training/labels/val/BloodImage_00004.txt',\n",
              " 'model_training/labels/val/BloodImage_00250.txt',\n",
              " 'model_training/labels/val/BloodImage_00242.txt',\n",
              " 'model_training/labels/val/BloodImage_00035.txt',\n",
              " 'model_training/labels/val/BloodImage_00063.txt',\n",
              " 'model_training/labels/val/BloodImage_00271.txt',\n",
              " 'model_training/labels/val/BloodImage_00141.txt',\n",
              " 'model_training/labels/val/BloodImage_00315.txt',\n",
              " 'model_training/labels/val/BloodImage_00339.txt',\n",
              " 'model_training/labels/val/BloodImage_00107.txt',\n",
              " 'model_training/labels/val/BloodImage_00200.txt',\n",
              " 'model_training/labels/val/BloodImage_00199.txt',\n",
              " 'model_training/labels/val/BloodImage_00225.txt',\n",
              " 'model_training/labels/val/BloodImage_00233.txt',\n",
              " 'model_training/labels/val/BloodImage_00253.txt',\n",
              " 'model_training/labels/val/BloodImage_00300.txt',\n",
              " 'model_training/labels/val/BloodImage_00021.txt',\n",
              " 'model_training/labels/val/BloodImage_00241.txt',\n",
              " 'model_training/labels/val/BloodImage_00372.txt',\n",
              " 'model_training/labels/val/BloodImage_00123.txt',\n",
              " 'model_training/labels/val/BloodImage_00382.txt',\n",
              " 'model_training/labels/val/BloodImage_00205.txt',\n",
              " 'model_training/labels/val/BloodImage_00206.txt',\n",
              " 'model_training/labels/val/BloodImage_00284.txt',\n",
              " 'model_training/labels/val/BloodImage_00143.txt',\n",
              " 'model_training/labels/val/BloodImage_00287.txt',\n",
              " 'model_training/labels/val/BloodImage_00154.txt',\n",
              " 'model_training/labels/val/BloodImage_00274.txt',\n",
              " 'model_training/labels/val/BloodImage_00091.txt',\n",
              " 'model_training/labels/val/BloodImage_00127.txt',\n",
              " 'model_training/labels/val/BloodImage_00330.txt']"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset.export.ExportToYoloV5(output_path='model_training/labels',yaml_file='dataset.yaml', copy_images=True, use_splits=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "names:\n",
            "- RBC\n",
            "- Platelets\n",
            "- WBC\n",
            "nc: 3\n",
            "path: ..\n",
            "test: model_training/images/test\n",
            "train: model_training/images/train\n",
            "val: model_training/images/val\n"
          ]
        }
      ],
      "source": [
        "!cat 'model_training/dataset.yaml'"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "import2.ipynb",
      "provenance": []
    },
    "interpreter": {
      "hash": "de5e368ab5494158da905fb8b1c2e4fef8844fbfaace7cceca0beab983df3a80"
    },
    "kernelspec": {
      "display_name": "Python 3.8.5 64-bit ('penv': venv)",
      "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"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}