07 Duke Data.ipynb

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   "source": [
    "# Setup\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "\n",
    "import glob\n",
    "import os\n",
    "import itertools\n",
    "import collections\n",
    "import re\n",
    "import json\n",
    "import requests\n",
    "from shutil import copyfile\n",
    "from pathlib import Path\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "import colour\n",
    "\n",
    "from matplotlib import cm\n",
    "from matplotlib.colors import ListedColormap, LinearSegmentedColormap\n",
    "# https://matplotlib.org/3.1.0/tutorials/colors/colormap-manipulation.html\n",
    "\n",
    "from shapely.geometry import Polygon, Point\n",
    "import geopandas as gpd\n",
    "import pyproj\n",
    "import folium\n",
    "from folium import Rectangle\n",
    "from folium import Polygon as f_Polygon\n",
    "import affine\n",
    "\n",
    "from tqdm import tqdm # Progress bar stuff cos progress bars are good\n",
    "tqdm.pandas() # now can use progress_apply instead of apply\n",
    "\n",
    "import pickle # Pickle stuff, cos pickling is good\n",
    "\n",
    "# Styles\n",
    "pd.set_option('display.float_format', lambda x: '%.2f' % x) # pandas\n",
    "np.set_printoptions(precision=5, suppress=True) # numpy\n",
    "\n",
    "pd.set_option('display.max_columns', 100)\n",
    "pd.set_option('display.max_rows', 100)\n",
    "\n",
    "# seaborn plotting style\n",
    "sns.set(style='ticks', context='poster')\n",
    "\n",
    "import rasterio\n",
    "from rasterio.crs import CRS\n",
    "from rasterio.plot import show\n",
    "from rasterio.warp import transform_bounds\n",
    "from rasterio.features import geometry_mask\n",
    "\n",
    "from shapely.ops import transform\n",
    "from functools import partial\n",
    "import pyproj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_dir = '/home/laurence/projects/raster-vision-fastai-plugin/data/duke_raw_labels/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = gpd.read_file(base_dir + 'SolarArrayPolygons.geojson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>polygon_id</th>\n",
       "      <th>centroid_latitude</th>\n",
       "      <th>centroid_longitude</th>\n",
       "      <th>centroid_latitude_pixels</th>\n",
       "      <th>centroid_longitude_pixels</th>\n",
       "      <th>city</th>\n",
       "      <th>area_pixels</th>\n",
       "      <th>area_meters</th>\n",
       "      <th>image_name</th>\n",
       "      <th>nw_corner_of_image_latitude</th>\n",
       "      <th>nw_corner_of_image_longitude</th>\n",
       "      <th>se_corner_of_image_latitude</th>\n",
       "      <th>se_corner_of_image_longitude</th>\n",
       "      <th>datum</th>\n",
       "      <th>projection_zone</th>\n",
       "      <th>resolution</th>\n",
       "      <th>jaccard_index</th>\n",
       "      <th>polygon_vertices_pixels</th>\n",
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       "      <td>3286.15</td>\n",
       "      <td>Fresno</td>\n",
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       "      <td>36.93</td>\n",
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       "   polygon_id  centroid_latitude  centroid_longitude  \\\n",
       "0           1              36.93             -119.84   \n",
       "\n",
       "   centroid_latitude_pixels  centroid_longitude_pixels    city  area_pixels  \\\n",
       "0                    107.62                    3286.15  Fresno       136.19   \n",
       "\n",
       "   area_meters   image_name  nw_corner_of_image_latitude  \\\n",
       "0      1513.25  11ska460890                        36.93   \n",
       "\n",
       "   nw_corner_of_image_longitude  se_corner_of_image_latitude  \\\n",
       "0                       -119.85                        36.91   \n",
       "\n",
       "   se_corner_of_image_longitude  datum projection_zone  resolution  \\\n",
       "0                       -119.83  NAD83              11        0.30   \n",
       "\n",
       "   jaccard_index                            polygon_vertices_pixels  \\\n",
       "0           0.91  [ [ 3360.495069, 131.631164 ], [ 3249.197710, ...   \n",
       "\n",
       "                                            geometry  \n",
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   "source": [
    "df.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "      <th>geometry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>Fresno</th>\n",
       "      <td>14710</td>\n",
       "      <td>14710</td>\n",
       "      <td>14710</td>\n",
       "      <td>14710</td>\n",
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       "      <td>14710</td>\n",
       "      <td>14710</td>\n",
       "      <td>14710</td>\n",
       "      <td>14710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Modesto</th>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
       "      <td>582</td>\n",
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       "      <td>582</td>\n",
       "      <td>582</td>\n",
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       "    <tr>\n",
       "      <th>Oxnard</th>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "      <td>1595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stockton</th>\n",
       "      <td>2546</td>\n",
       "      <td>2546</td>\n",
       "      <td>2546</td>\n",
       "      <td>2546</td>\n",
       "      <td>2546</td>\n",
       "      <td>2546</td>\n",
       "      <td>2546</td>\n",
       "      <td>2546</td>\n",
       "      <td>2546</td>\n",
       "      <td>2546</td>\n",
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       "      <td>2546</td>\n",
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      "text/plain": [
       "          polygon_id  centroid_latitude  centroid_longitude  \\\n",
       "city                                                          \n",
       "Fresno         14710              14710               14710   \n",
       "Modesto          582                582                 582   \n",
       "Oxnard          1595               1595                1595   \n",
       "Stockton        2546               2546                2546   \n",
       "\n",
       "          centroid_latitude_pixels  centroid_longitude_pixels  area_pixels  \\\n",
       "city                                                                         \n",
       "Fresno                       14710                      14710        14710   \n",
       "Modesto                        582                        582          582   \n",
       "Oxnard                        1595                       1595         1595   \n",
       "Stockton                      2546                       2546         2546   \n",
       "\n",
       "          area_meters  image_name  nw_corner_of_image_latitude  \\\n",
       "city                                                             \n",
       "Fresno          14710       14710                        14710   \n",
       "Modesto           582         582                          582   \n",
       "Oxnard           1595        1595                         1595   \n",
       "Stockton         2546        2546                         2546   \n",
       "\n",
       "          nw_corner_of_image_longitude  se_corner_of_image_latitude  \\\n",
       "city                                                                  \n",
       "Fresno                           14710                        14710   \n",
       "Modesto                            582                          582   \n",
       "Oxnard                            1595                         1595   \n",
       "Stockton                          2546                         2546   \n",
       "\n",
       "          se_corner_of_image_longitude  datum  projection_zone  resolution  \\\n",
       "city                                                                         \n",
       "Fresno                           14710  14710            14710       14710   \n",
       "Modesto                            582    582              582         582   \n",
       "Oxnard                            1595   1595             1595        1595   \n",
       "Stockton                          2546   2546             2546        2546   \n",
       "\n",
       "          jaccard_index  polygon_vertices_pixels  geometry  \n",
       "city                                                        \n",
       "Fresno            14710                    14710     14710  \n",
       "Modesto             582                      582       582  \n",
       "Oxnard             1595                     1595      1595  \n",
       "Stockton           2546                     2546      2546  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('city').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
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     "execution_count": 16,
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   ],
   "source": [
    "df.iloc[4].geometry"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Export GeoJson into named label files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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       "      <td>107.62</td>\n",
       "      <td>3286.15</td>\n",
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       "      <td>36.93</td>\n",
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       "      <td>45.98</td>\n",
       "      <td>3286.35</td>\n",
       "      <td>Fresno</td>\n",
       "      <td>155.51</td>\n",
       "      <td>1727.91</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>36.93</td>\n",
       "      <td>-119.84</td>\n",
       "      <td>22.28</td>\n",
       "      <td>3303.47</td>\n",
       "      <td>Fresno</td>\n",
       "      <td>111.80</td>\n",
       "      <td>1242.18</td>\n",
       "      <td>11ska460890</td>\n",
       "      <td>36.93</td>\n",
       "      <td>-119.85</td>\n",
       "      <td>36.91</td>\n",
       "      <td>-119.83</td>\n",
       "      <td>NAD83</td>\n",
       "      <td>11</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.94</td>\n",
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       "      <td>POLYGON ((-119.8403195438845 36.92647659525593...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>36.92</td>\n",
       "      <td>-119.84</td>\n",
       "      <td>2048.36</td>\n",
       "      <td>2547.37</td>\n",
       "      <td>Fresno</td>\n",
       "      <td>62.00</td>\n",
       "      <td>688.93</td>\n",
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       "      <td>-119.85</td>\n",
       "      <td>36.91</td>\n",
       "      <td>-119.83</td>\n",
       "      <td>NAD83</td>\n",
       "      <td>11</td>\n",
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       "      <td>0.84</td>\n",
       "      <td>[ [ 2571.591716, 2068.049310 ], [ 2571.021266,...</td>\n",
       "      <td>POLYGON ((-119.842763429036 36.92095723433444,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>36.92</td>\n",
       "      <td>-119.84</td>\n",
       "      <td>2060.01</td>\n",
       "      <td>2529.50</td>\n",
       "      <td>Fresno</td>\n",
       "      <td>95.48</td>\n",
       "      <td>1060.89</td>\n",
       "      <td>11ska460890</td>\n",
       "      <td>36.93</td>\n",
       "      <td>-119.85</td>\n",
       "      <td>36.91</td>\n",
       "      <td>-119.83</td>\n",
       "      <td>NAD83</td>\n",
       "      <td>11</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.89</td>\n",
       "      <td>[ [ 2563.781065, 2091.398422 ], [ 2504.416174,...</td>\n",
       "      <td>POLYGON ((-119.8427873725915 36.92089353657303...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>36.92</td>\n",
       "      <td>-119.84</td>\n",
       "      <td>2058.96</td>\n",
       "      <td>2501.53</td>\n",
       "      <td>Fresno</td>\n",
       "      <td>95.07</td>\n",
       "      <td>1056.37</td>\n",
       "      <td>11ska460890</td>\n",
       "      <td>36.93</td>\n",
       "      <td>-119.85</td>\n",
       "      <td>36.91</td>\n",
       "      <td>-119.83</td>\n",
       "      <td>NAD83</td>\n",
       "      <td>11</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.88</td>\n",
       "      <td>[ [ 2536.550000, 2090.250000 ], [ 2508.358568,...</td>\n",
       "      <td>POLYGON ((-119.842879104718 36.92089444496381,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>36.92</td>\n",
       "      <td>-119.84</td>\n",
       "      <td>2059.19</td>\n",
       "      <td>2474.75</td>\n",
       "      <td>Fresno</td>\n",
       "      <td>96.09</td>\n",
       "      <td>1067.70</td>\n",
       "      <td>11ska460890</td>\n",
       "      <td>36.93</td>\n",
       "      <td>-119.85</td>\n",
       "      <td>36.91</td>\n",
       "      <td>-119.83</td>\n",
       "      <td>NAD83</td>\n",
       "      <td>11</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.93</td>\n",
       "      <td>[ [ 2508.437870, 2090.662722 ], [ 2508.012693,...</td>\n",
       "      <td>POLYGON ((-119.8429736450205 36.92089106555471...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   polygon_id  centroid_latitude  centroid_longitude  \\\n",
       "0           1              36.93             -119.84   \n",
       "1           2              36.93             -119.84   \n",
       "2           3              36.93             -119.84   \n",
       "3           4              36.92             -119.84   \n",
       "4           5              36.92             -119.84   \n",
       "5           6              36.92             -119.84   \n",
       "6           7              36.92             -119.84   \n",
       "\n",
       "   centroid_latitude_pixels  centroid_longitude_pixels    city  area_pixels  \\\n",
       "0                    107.62                    3286.15  Fresno       136.19   \n",
       "1                     45.98                    3286.35  Fresno       155.51   \n",
       "2                     22.28                    3303.47  Fresno       111.80   \n",
       "3                   2048.36                    2547.37  Fresno        62.00   \n",
       "4                   2060.01                    2529.50  Fresno        95.48   \n",
       "5                   2058.96                    2501.53  Fresno        95.07   \n",
       "6                   2059.19                    2474.75  Fresno        96.09   \n",
       "\n",
       "   area_meters   image_name  nw_corner_of_image_latitude  \\\n",
       "0      1513.25  11ska460890                        36.93   \n",
       "1      1727.91  11ska460890                        36.93   \n",
       "2      1242.18  11ska460890                        36.93   \n",
       "3       688.93  11ska460890                        36.93   \n",
       "4      1060.89  11ska460890                        36.93   \n",
       "5      1056.37  11ska460890                        36.93   \n",
       "6      1067.70  11ska460890                        36.93   \n",
       "\n",
       "   nw_corner_of_image_longitude  se_corner_of_image_latitude  \\\n",
       "0                       -119.85                        36.91   \n",
       "1                       -119.85                        36.91   \n",
       "2                       -119.85                        36.91   \n",
       "3                       -119.85                        36.91   \n",
       "4                       -119.85                        36.91   \n",
       "5                       -119.85                        36.91   \n",
       "6                       -119.85                        36.91   \n",
       "\n",
       "   se_corner_of_image_longitude  datum projection_zone  resolution  \\\n",
       "0                       -119.83  NAD83              11        0.30   \n",
       "1                       -119.83  NAD83              11        0.30   \n",
       "2                       -119.83  NAD83              11        0.30   \n",
       "3                       -119.83  NAD83              11        0.30   \n",
       "4                       -119.83  NAD83              11        0.30   \n",
       "5                       -119.83  NAD83              11        0.30   \n",
       "6                       -119.83  NAD83              11        0.30   \n",
       "\n",
       "   jaccard_index                            polygon_vertices_pixels  \\\n",
       "0           0.91  [ [ 3360.495069, 131.631164 ], [ 3249.197710, ...   \n",
       "1           0.83  [ [ 3361.153846, 69.615385 ], [ 3217.615385, 1...   \n",
       "2           0.94  [ [ 3358.015726, 48.136863 ], [ 3358.050000, 4...   \n",
       "3           0.84  [ [ 2571.591716, 2068.049310 ], [ 2571.021266,...   \n",
       "4           0.89  [ [ 2563.781065, 2091.398422 ], [ 2504.416174,...   \n",
       "5           0.88  [ [ 2536.550000, 2090.250000 ], [ 2508.358568,...   \n",
       "6           0.93  [ [ 2508.437870, 2090.662722 ], [ 2508.012693,...   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((-119.8403028528537 36.92625126752494...  \n",
       "1  POLYGON ((-119.8403068380159 36.92641883215844...  \n",
       "2  POLYGON ((-119.8403195438845 36.92647659525593...  \n",
       "3  POLYGON ((-119.842763429036 36.92095723433444,...  \n",
       "4  POLYGON ((-119.8427873725915 36.92089353657303...  \n",
       "5  POLYGON ((-119.842879104718 36.92089444496381,...  \n",
       "6  POLYGON ((-119.8429736450205 36.92089106555471...  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['image_name']=='11ska460890']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "for name in df['image_name'].unique():\n",
    "    df[df['image_name'] == name].to_file(f\"/home/laurence/projects/raster-vision-fastai-plugin/data/duke_labels/{name}.geojson\", driver='GeoJSON')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get list of IDs\n",
    "lab_dir = '/home/laurence/projects/raster-vision-fastai-plugin/data/duke_labels/*.geojson'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "names = [os.path.basename(x).replace('.geojson', '') for x in glob.glob(lab_dir)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'11ska385710'"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "label_uri = '/home/laurence/projects/raster-vision-fastai-plugin/data/duke_labels/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/laurence/projects/raster-vision-fastai-plugin/data/duke_labels/*.geojson'"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.path.join(label_uri, '*.geojson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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