PollenClassification.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "77c893c9",
   "metadata": {},
   "source": [
    "This notebook is adapted from the \"how-to-use-scivision\" notebook in the repository https://github.com/scivision-gallery/scivision_examples to be used in the Turing REG/RDS Connections Workshop.\n",
    "The purpose is to use the pollen dataset and pretrained model that will have been added to the Scivision catalog."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5812ba7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scivision import default_catalog, load_pretrained_model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb7bdd44",
   "metadata": {},
   "source": [
    "Construct a dataframe containing the contents of the models catalog:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3961a3ac",
   "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>name</th>\n",
       "      <th>description</th>\n",
       "      <th>tasks</th>\n",
       "      <th>url</th>\n",
       "      <th>pkg_url</th>\n",
       "      <th>format</th>\n",
       "      <th>pretrained</th>\n",
       "      <th>labels_required</th>\n",
       "      <th>institution</th>\n",
       "      <th>tags</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>model-000</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.object_detection, TaskEnum.segmentat...</td>\n",
       "      <td>https://github.com/stardist/stardist</td>\n",
       "      <td>git+https://github.com/stardist/stardist.git@main</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>(epfl,)</td>\n",
       "      <td>(2D, 3D, optical-microscopy, xray, microtomogr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>model-001</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.segmentation, TaskEnum.thresholding,...</td>\n",
       "      <td>https://github.com/danforthcenter/plantcv</td>\n",
       "      <td>git+https://github.com/danforthcenter/plantcv@...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>(danforthcenter,)</td>\n",
       "      <td>(2D, hyperspectral, multispectral, near-infrar...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>model-002</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.segmentation,)</td>\n",
       "      <td>https://github.com/MarniTausen/Greenotyper</td>\n",
       "      <td>git+https://github.com/MarniTausen/Greenotyper...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>(MarniTausen,)</td>\n",
       "      <td>(2D, multispectral, plant-phenotyping, climate...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>model-003</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.segmentation,)</td>\n",
       "      <td>https://github.com/alan-turing-institute/cv-al...</td>\n",
       "      <td>git+https://github.com/alan-turing-institute/c...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>(alan-turing-institute,)</td>\n",
       "      <td>(dummy,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>scivision-test-plugin</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.object_detection,)</td>\n",
       "      <td>https://github.com/alan-turing-institute/scivi...</td>\n",
       "      <td>git+https://github.com/alan-turing-institute/s...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(alan-turing-institute,)</td>\n",
       "      <td>(dummy,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mapreader-plant</td>\n",
       "      <td>automated detection of plant patches in images...</td>\n",
       "      <td>(TaskEnum.classificiation, TaskEnum.object_det...</td>\n",
       "      <td>https://github.com/alan-turing-institute/mapre...</td>\n",
       "      <td>git+https://github.com/alan-turing-institute/m...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(alan-turing-institute,)</td>\n",
       "      <td>(2D, plant, phenotype, rgb, biology, agriculture)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>resnet50-plankton</td>\n",
       "      <td>automated classification of plankton images co...</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>https://github.com/nbarlowATI/plankton-cefas-s...</td>\n",
       "      <td>git+https://github.com/nbarlowATI/plankton-cef...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(alan-turing-institute, cefas, plankton-analyt...</td>\n",
       "      <td>(2D, plankton, ecology, environmental-science)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>vedge-detector</td>\n",
       "      <td>automated detection of coastal vegetation edge...</td>\n",
       "      <td>(TaskEnum.segmentation,)</td>\n",
       "      <td>https://github.com/MartinSJRogers/VEdge_Detect...</td>\n",
       "      <td>git+https://github.com/MartinSJRogers/VEdge_De...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(cambridge-university, birkbeck-university)</td>\n",
       "      <td>(2D, satellite, remote-sensing, ecology, envir...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>image-classifiers</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>https://github.com/alan-turing-institute/scivi...</td>\n",
       "      <td>git+https://github.com/alan-turing-institute/s...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(alan-turing-institute,)</td>\n",
       "      <td>(classification, 2D, image)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>huggingface-classifiers</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>https://github.com/alan-turing-institute/scivi...</td>\n",
       "      <td>git+https://github.com/alan-turing-institute/s...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(alan-turing-institute, huggingface)</td>\n",
       "      <td>(classification, 2D, image)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>huggingface-segmentation</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.segmentation,)</td>\n",
       "      <td>https://github.com/alan-turing-institute/scivi...</td>\n",
       "      <td>git+https://github.com/alan-turing-institute/s...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(alan-turing-institute, huggingface)</td>\n",
       "      <td>()</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>huggingface-object-detection</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.object_detection,)</td>\n",
       "      <td>https://github.com/alan-turing-institute/scivi...</td>\n",
       "      <td>git+https://github.com/alan-turing-institute/s...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(alan-turing-institute, huggingface)</td>\n",
       "      <td>()</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>detectreeRGB-forest</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.object_detection, TaskEnum.segmentat...</td>\n",
       "      <td>https://github.com/shmh40/detectreeRGB-treecro...</td>\n",
       "      <td>git+https://github.com/shmh40/detectreeRGB-tre...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(cambridge-university,)</td>\n",
       "      <td>(2D, satellite, remote-sensing, ecology, envir...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>bee-species</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>https://github.com/nbarlowATI/honeybee_species...</td>\n",
       "      <td>git+https://github.com/nbarlowATI/honeybee_spe...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(Alan Turing Institute,)</td>\n",
       "      <td>(bee, honeybee)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>flower-species</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>https://github.com/nbarlowATI/flower_classific...</td>\n",
       "      <td>git+https://github.com/nbarlowATI/flower_class...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(Alan Turing Institute,)</td>\n",
       "      <td>(flower, biology)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>butterfly-species</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>https://github.com/nbarlowATI/butterfly_classi...</td>\n",
       "      <td>git+https://github.com/nbarlowATI/butterfly_cl...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(Alan Turing Institute,)</td>\n",
       "      <td>(butterfly, insect, biology)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>pollen-types</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>https://github.com/nbarlowATI/pollen_classific...</td>\n",
       "      <td>git+https://github.com/nbarlowATI/pollen_class...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>(Alan Turing Institute,)</td>\n",
       "      <td>(pollen, plant, biology)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            name  \\\n",
       "0                      model-000   \n",
       "1                      model-001   \n",
       "2                      model-002   \n",
       "3                      model-003   \n",
       "4          scivision-test-plugin   \n",
       "5                mapreader-plant   \n",
       "6              resnet50-plankton   \n",
       "7                 vedge-detector   \n",
       "8              image-classifiers   \n",
       "9        huggingface-classifiers   \n",
       "10      huggingface-segmentation   \n",
       "11  huggingface-object-detection   \n",
       "12           detectreeRGB-forest   \n",
       "13                   bee-species   \n",
       "14                flower-species   \n",
       "15             butterfly-species   \n",
       "16                  pollen-types   \n",
       "\n",
       "                                          description  \\\n",
       "0                                                None   \n",
       "1                                                None   \n",
       "2                                                None   \n",
       "3                                                None   \n",
       "4                                                None   \n",
       "5   automated detection of plant patches in images...   \n",
       "6   automated classification of plankton images co...   \n",
       "7   automated detection of coastal vegetation edge...   \n",
       "8                                                None   \n",
       "9                                                None   \n",
       "10                                               None   \n",
       "11                                               None   \n",
       "12                                               None   \n",
       "13                                               None   \n",
       "14                                               None   \n",
       "15                                               None   \n",
       "16                                               None   \n",
       "\n",
       "                                                tasks  \\\n",
       "0   (TaskEnum.object_detection, TaskEnum.segmentat...   \n",
       "1   (TaskEnum.segmentation, TaskEnum.thresholding,...   \n",
       "2                            (TaskEnum.segmentation,)   \n",
       "3                            (TaskEnum.segmentation,)   \n",
       "4                        (TaskEnum.object_detection,)   \n",
       "5   (TaskEnum.classificiation, TaskEnum.object_det...   \n",
       "6                         (TaskEnum.classificiation,)   \n",
       "7                            (TaskEnum.segmentation,)   \n",
       "8                         (TaskEnum.classificiation,)   \n",
       "9                         (TaskEnum.classificiation,)   \n",
       "10                           (TaskEnum.segmentation,)   \n",
       "11                       (TaskEnum.object_detection,)   \n",
       "12  (TaskEnum.object_detection, TaskEnum.segmentat...   \n",
       "13                        (TaskEnum.classificiation,)   \n",
       "14                        (TaskEnum.classificiation,)   \n",
       "15                        (TaskEnum.classificiation,)   \n",
       "16                        (TaskEnum.classificiation,)   \n",
       "\n",
       "                                                  url  \\\n",
       "0                https://github.com/stardist/stardist   \n",
       "1           https://github.com/danforthcenter/plantcv   \n",
       "2          https://github.com/MarniTausen/Greenotyper   \n",
       "3   https://github.com/alan-turing-institute/cv-al...   \n",
       "4   https://github.com/alan-turing-institute/scivi...   \n",
       "5   https://github.com/alan-turing-institute/mapre...   \n",
       "6   https://github.com/nbarlowATI/plankton-cefas-s...   \n",
       "7   https://github.com/MartinSJRogers/VEdge_Detect...   \n",
       "8   https://github.com/alan-turing-institute/scivi...   \n",
       "9   https://github.com/alan-turing-institute/scivi...   \n",
       "10  https://github.com/alan-turing-institute/scivi...   \n",
       "11  https://github.com/alan-turing-institute/scivi...   \n",
       "12  https://github.com/shmh40/detectreeRGB-treecro...   \n",
       "13  https://github.com/nbarlowATI/honeybee_species...   \n",
       "14  https://github.com/nbarlowATI/flower_classific...   \n",
       "15  https://github.com/nbarlowATI/butterfly_classi...   \n",
       "16  https://github.com/nbarlowATI/pollen_classific...   \n",
       "\n",
       "                                              pkg_url format  pretrained  \\\n",
       "0   git+https://github.com/stardist/stardist.git@main  image        True   \n",
       "1   git+https://github.com/danforthcenter/plantcv@...  image        True   \n",
       "2   git+https://github.com/MarniTausen/Greenotyper...  image        True   \n",
       "3   git+https://github.com/alan-turing-institute/c...  image        True   \n",
       "4   git+https://github.com/alan-turing-institute/s...  image        True   \n",
       "5   git+https://github.com/alan-turing-institute/m...  image        True   \n",
       "6   git+https://github.com/nbarlowATI/plankton-cef...  image        True   \n",
       "7   git+https://github.com/MartinSJRogers/VEdge_De...  image        True   \n",
       "8   git+https://github.com/alan-turing-institute/s...  image        True   \n",
       "9   git+https://github.com/alan-turing-institute/s...  image        True   \n",
       "10  git+https://github.com/alan-turing-institute/s...  image        True   \n",
       "11  git+https://github.com/alan-turing-institute/s...  image        True   \n",
       "12  git+https://github.com/shmh40/detectreeRGB-tre...  image        True   \n",
       "13  git+https://github.com/nbarlowATI/honeybee_spe...  image        True   \n",
       "14  git+https://github.com/nbarlowATI/flower_class...  image        True   \n",
       "15  git+https://github.com/nbarlowATI/butterfly_cl...  image        True   \n",
       "16  git+https://github.com/nbarlowATI/pollen_class...  image        True   \n",
       "\n",
       "    labels_required                                        institution  \\\n",
       "0              True                                            (epfl,)   \n",
       "1              True                                  (danforthcenter,)   \n",
       "2              True                                     (MarniTausen,)   \n",
       "3              True                           (alan-turing-institute,)   \n",
       "4             False                           (alan-turing-institute,)   \n",
       "5             False                           (alan-turing-institute,)   \n",
       "6             False  (alan-turing-institute, cefas, plankton-analyt...   \n",
       "7             False        (cambridge-university, birkbeck-university)   \n",
       "8             False                           (alan-turing-institute,)   \n",
       "9             False               (alan-turing-institute, huggingface)   \n",
       "10            False               (alan-turing-institute, huggingface)   \n",
       "11            False               (alan-turing-institute, huggingface)   \n",
       "12            False                            (cambridge-university,)   \n",
       "13            False                           (Alan Turing Institute,)   \n",
       "14            False                           (Alan Turing Institute,)   \n",
       "15            False                           (Alan Turing Institute,)   \n",
       "16            False                           (Alan Turing Institute,)   \n",
       "\n",
       "                                                 tags  \n",
       "0   (2D, 3D, optical-microscopy, xray, microtomogr...  \n",
       "1   (2D, hyperspectral, multispectral, near-infrar...  \n",
       "2   (2D, multispectral, plant-phenotyping, climate...  \n",
       "3                                            (dummy,)  \n",
       "4                                            (dummy,)  \n",
       "5   (2D, plant, phenotype, rgb, biology, agriculture)  \n",
       "6      (2D, plankton, ecology, environmental-science)  \n",
       "7   (2D, satellite, remote-sensing, ecology, envir...  \n",
       "8                         (classification, 2D, image)  \n",
       "9                         (classification, 2D, image)  \n",
       "10                                                 ()  \n",
       "11                                                 ()  \n",
       "12  (2D, satellite, remote-sensing, ecology, envir...  \n",
       "13                                    (bee, honeybee)  \n",
       "14                                  (flower, biology)  \n",
       "15                       (butterfly, insect, biology)  \n",
       "16                           (pollen, plant, biology)  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "models_catalog = default_catalog.models.to_dataframe()\n",
    "models_catalog"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2800056f",
   "metadata": {},
   "source": [
    "Our newly-added \"pollen-types\" model is there as the last entry.  We can use the \"url\" column, specifying the Github repo that contains the model, to load the model itself: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bf26a010",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Inspecting model entry and its metadata in the default catalog\n",
    "model_repo = models_catalog[models_catalog.name == \"pollen-types\"].url.item()\n",
    "model = load_pretrained_model(model_repo, allow_install=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72d75a8a",
   "metadata": {},
   "source": [
    "Now we will search the catalog again for data sources that are compatible with our model.   By \"compatible\", we mean that the dataset is suitable for the \"tasks\" that the model can perform."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "43322db2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>description</th>\n",
       "      <th>tasks</th>\n",
       "      <th>domains</th>\n",
       "      <th>url</th>\n",
       "      <th>format</th>\n",
       "      <th>labels_provided</th>\n",
       "      <th>institution</th>\n",
       "      <th>tags</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>data-002</td>\n",
       "      <td>None</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>(oceanography,)</td>\n",
       "      <td>https://github.com/scotthosking/intake-plankto...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>(CEFAS,)</td>\n",
       "      <td>(help-needed, 2D)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>data-003</td>\n",
       "      <td>Koala</td>\n",
       "      <td>(TaskEnum.object_detection, TaskEnum.classific...</td>\n",
       "      <td>(computer-vision,)</td>\n",
       "      <td>https://github.com/alan-turing-institute/scivi...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>(Wikipedia by Erik Veland,)</td>\n",
       "      <td>(demo,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>data-004</td>\n",
       "      <td>Sample dataset of Plankton required to demonst...</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>(computer-vision,)</td>\n",
       "      <td>https://raw.githubusercontent.com/alan-turing-...</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>(Centre for Environment, Fisheries and Aquacul...</td>\n",
       "      <td>(2D, plankton, ecology, environmental-science)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>data-005</td>\n",
       "      <td>Sample dataset of satellite imagery required t...</td>\n",
       "      <td>(TaskEnum.classificiation, TaskEnum.segmentation)</td>\n",
       "      <td>(computer-vision, earth-observation, ecology)</td>\n",
       "      <td>https://github.com/MartinSJRogers/VEdge_Detect...</td>\n",
       "      <td>image</td>\n",
       "      <td>False</td>\n",
       "      <td>(Cambridge University,)</td>\n",
       "      <td>(2D, satellite, remote-sensing, ecology, envir...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>data-007</td>\n",
       "      <td>A labelled dataset of honeybee images, from Ka...</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>(nature, insects, bee-keeping)</td>\n",
       "      <td>https://github.com/nbarlowATI/honeybee_data_repo</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>(alan-turing-institute,)</td>\n",
       "      <td>(bees, biology, classification)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>data-008</td>\n",
       "      <td>A labelled dataset of flower images, from Kaggle</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>(nature, flowers, biology)</td>\n",
       "      <td>https://github.com/nbarlowATI/flowers_data_repo</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>(alan-turing-institute,)</td>\n",
       "      <td>(flowers, biology, classification)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>data-009</td>\n",
       "      <td>A labelled dataset of butterfly images, from K...</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>(nature, butterflies, biology)</td>\n",
       "      <td>https://github.com/nbarlowATI/butterfly_data_repo</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>(alan-turing-institute,)</td>\n",
       "      <td>(butterflies, biology, classification)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>data-010</td>\n",
       "      <td>A labelled dataset of pollen grain images, fro...</td>\n",
       "      <td>(TaskEnum.classificiation,)</td>\n",
       "      <td>(nature, pollen, biology)</td>\n",
       "      <td>https://github.com/nbarlowATI/pollen_data_repo</td>\n",
       "      <td>image</td>\n",
       "      <td>True</td>\n",
       "      <td>(alan-turing-institute,)</td>\n",
       "      <td>(pollen, biology, classification)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name                                        description  \\\n",
       "2   data-002                                               None   \n",
       "3   data-003                                              Koala   \n",
       "4   data-004  Sample dataset of Plankton required to demonst...   \n",
       "5   data-005  Sample dataset of satellite imagery required t...   \n",
       "7   data-007  A labelled dataset of honeybee images, from Ka...   \n",
       "8   data-008   A labelled dataset of flower images, from Kaggle   \n",
       "9   data-009  A labelled dataset of butterfly images, from K...   \n",
       "10  data-010  A labelled dataset of pollen grain images, fro...   \n",
       "\n",
       "                                                tasks  \\\n",
       "2                         (TaskEnum.classificiation,)   \n",
       "3   (TaskEnum.object_detection, TaskEnum.classific...   \n",
       "4                         (TaskEnum.classificiation,)   \n",
       "5   (TaskEnum.classificiation, TaskEnum.segmentation)   \n",
       "7                         (TaskEnum.classificiation,)   \n",
       "8                         (TaskEnum.classificiation,)   \n",
       "9                         (TaskEnum.classificiation,)   \n",
       "10                        (TaskEnum.classificiation,)   \n",
       "\n",
       "                                          domains  \\\n",
       "2                                 (oceanography,)   \n",
       "3                              (computer-vision,)   \n",
       "4                              (computer-vision,)   \n",
       "5   (computer-vision, earth-observation, ecology)   \n",
       "7                  (nature, insects, bee-keeping)   \n",
       "8                      (nature, flowers, biology)   \n",
       "9                  (nature, butterflies, biology)   \n",
       "10                      (nature, pollen, biology)   \n",
       "\n",
       "                                                  url format  labels_provided  \\\n",
       "2   https://github.com/scotthosking/intake-plankto...  image             True   \n",
       "3   https://github.com/alan-turing-institute/scivi...  image             True   \n",
       "4   https://raw.githubusercontent.com/alan-turing-...  image             True   \n",
       "5   https://github.com/MartinSJRogers/VEdge_Detect...  image            False   \n",
       "7    https://github.com/nbarlowATI/honeybee_data_repo  image             True   \n",
       "8     https://github.com/nbarlowATI/flowers_data_repo  image             True   \n",
       "9   https://github.com/nbarlowATI/butterfly_data_repo  image             True   \n",
       "10     https://github.com/nbarlowATI/pollen_data_repo  image             True   \n",
       "\n",
       "                                          institution  \\\n",
       "2                                            (CEFAS,)   \n",
       "3                         (Wikipedia by Erik Veland,)   \n",
       "4   (Centre for Environment, Fisheries and Aquacul...   \n",
       "5                             (Cambridge University,)   \n",
       "7                            (alan-turing-institute,)   \n",
       "8                            (alan-turing-institute,)   \n",
       "9                            (alan-turing-institute,)   \n",
       "10                           (alan-turing-institute,)   \n",
       "\n",
       "                                                 tags  \n",
       "2                                   (help-needed, 2D)  \n",
       "3                                             (demo,)  \n",
       "4      (2D, plankton, ecology, environmental-science)  \n",
       "5   (2D, satellite, remote-sensing, ecology, envir...  \n",
       "7                     (bees, biology, classification)  \n",
       "8                  (flowers, biology, classification)  \n",
       "9              (butterflies, biology, classification)  \n",
       "10                  (pollen, biology, classification)  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compatible_datasources = default_catalog.compatible_datasources(\"pollen-types\").to_dataframe()\n",
    "compatible_datasources"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44378db0",
   "metadata": {},
   "source": [
    "Happily, our newly-added pollen dataset is there.  We can use the \"url\" column to load the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d0eae24b",
   "metadata": {},
   "outputs": [],
   "source": [
    "target_datasource = compatible_datasources.loc[compatible_datasources['name'] == 'data-010']\n",
    "data_url = target_datasource['url'].item()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8b425cb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/yaml": "data:\n  args:\n    path: https://raw.githubusercontent.com/nbarlowATI/pollen_data_repo/main/.scivision/data.yml\n  description: ''\n  driver: intake.catalog.local.YAMLFileCatalog\n  metadata: {}\n",
      "text/plain": [
       "data:\n",
       "  args:\n",
       "    path: https://raw.githubusercontent.com/nbarlowATI/pollen_data_repo/main/.scivision/data.yml\n",
       "  description: ''\n",
       "  driver: intake.catalog.local.YAMLFileCatalog\n",
       "  metadata: {}\n"
      ]
     },
     "metadata": {
      "application/json": {
       "root": "data"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scivision import load_dataset\n",
    "data_config = load_dataset(data_url)\n",
    "data_config"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9428cd4",
   "metadata": {},
   "source": [
    "Now, using Intake and Dask, we get the images themselves in a form that we can iterate over."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "96327b1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "images = data_config.pollen().to_dask()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ece4b0e",
   "metadata": {},
   "source": [
    "We can take a look at an example image using matplotlib's imshow function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "302bc3d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x2a27f24f0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.imshow(images[4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ad437fe",
   "metadata": {},
   "source": [
    "And finally, we can run our model on this image, to see what category it predicts for it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8280a76e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 1s 715ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'anadenanthera: 95.73%'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict(images[4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2ddff67",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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",
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