{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dialect regions from image\n",
    " \n",
    "Use image processing to extract longitude-latitude polygons for four dialect regions illustrated in this image.\n",
    "\n",
    "![dialect regions](../data/dialects.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('..')\n",
    "\n",
    "import folium\n",
    "import json\n",
    "\n",
    "from collections import Counter\n",
    "\n",
    "from math import sqrt, floor\n",
    "import numpy as np\n",
    "from imageio import imread\n",
    "\n",
    "%matplotlib notebook\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from skimage.morphology import binary_closing\n",
    "from skimage.measure import find_contours, label\n",
    "\n",
    "import folium.plugins\n",
    "from folium_jsbutton import JsButton\n",
    "\n",
    "from stimmen.latitude_longitude import reverse_latitude_longitude"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "im = imread('../data/dialects.png')\n",
    "regions =  ['Klaaifrysk', 'Waldfrysk', 'Sudwesthoeksk', 'Noardhoeksk']\n",
    "\n",
    "color_occurence = Counter(map(tuple, im.reshape(-1,3)))\n",
    "colors_sorted_by_occurence = [c for c, _ in sorted(\n",
    "    color_occurence.items(),\n",
    "    key=lambda x: x[1],\n",
    "    reverse=True)\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure out relevant colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pallette_width = floor(sqrt(len(colors_sorted_by_occurence)))\n",
    "pallette = np.array(colors_sorted_by_occurence[:pallette_width**2]).reshape(pallette_width, pallette_width, 3)\n",
    "\n",
    "_, (ax0, ax1) = plt.subplots(1, 2)\n",
    "ax0.imshow(pallette)\n",
    "for x in range(pallette_width):\n",
    "    for y in range(pallette_width):\n",
    "        ax0.text(x-0.5, y+0.5, str(x + y * pallette_width))\n",
    "ax0.set_xticks([]), ax0.set_yticks([])\n",
    "\n",
    "\n",
    "\n",
    "pallette_indices = [3, 4, 7, 8]\n",
    "pallette = [colors_sorted_by_occurence[i] for i in pallette_indices]\n",
    "pallette = np.array(pallette).reshape(1, -1, 3)\n",
    "ax1.imshow(pallette)\n",
    "ax1.set_xticks([]), ax1.set_yticks([])\n",
    "None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Georeference image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bounds = [\n",
    "    [ 53.54634089638824, 6.530699920654293],\n",
    "    [52.60043228879454, 4.684483127594012 ]\n",
    "]\n",
    "\n",
    "m = folium.Map(\n",
    "    location=[(bounds[0][0] + bounds[1][0]) / 2, (bounds[0][1] + bounds[1][1]) / 2],\n",
    "    tiles='stamentoner',\n",
    "    zoom_start=9\n",
    ")\n",
    "\n",
    "overlay = folium.raster_layers.ImageOverlay(\n",
    "    image='../data/dialects.png',\n",
    "    bounds=bounds,\n",
    "    opacity=0.5\n",
    ").add_to(m)\n",
    "\n",
    "overlay_id = overlay._id\n",
    "\n",
    "for number, (corner, direction, operation) in enumerate(\n",
    "    (c, d, o)\n",
    "    for c in ['_northEast', '_southWest'] for d in ['lat', 'lng'] for o in ['-', '+']\n",
    "):\n",
    "    JsButton(title=str(number), function=\"\"\"function(map, item) {{\n",
    "        var overlay = image_overlay_{overlay_id};\n",
    "        var bounds = overlay.getBounds()\n",
    "        bounds.{corner}.{direction} {operation}= 0.001;\n",
    "        overlay.setBounds(bounds);\n",
    "        \n",
    "}}\"\"\".format(overlay_id=overlay_id, corner=corner, direction=direction, operation=operation)).add_to(m)\n",
    "\n",
    "\n",
    "JsButton(title='B', function=\"\"\"function(map, item) {{\n",
    "        var overlay = image_overlay_{overlay_id};\n",
    "        var bounds = overlay.getBounds()\n",
    "        console.log([bounds._northEast.lat, bounds._northEast.lng, bounds._southWest.lat, bounds._southWest.lng])\n",
    "        \n",
    "}}\"\"\".format(overlay_id=overlay_id)).add_to(m)\n",
    "    \n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Find polygons in pixelcoordinates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "axes = plt.subplots(2,2)[1].ravel()\n",
    "contours = []\n",
    "for axis, c in zip(axes, pallette[0]):\n",
    "    bi = (im[:-100] == c[None,None]).min(axis=2)\n",
    "    bi = binary_closing(bi, np.ones((5,5)))\n",
    "    \n",
    "    labels = label(bi, background=False)\n",
    "    \n",
    "    contours.append(find_contours(bi, 0.5))\n",
    "\n",
    "    axis.imshow(bi)\n",
    "    for n, contour in enumerate(contours[-1][:1]):\n",
    "        axis.plot(contour[:, 1], contour[:, 0], linewidth=2)\n",
    "        axis.set_xticks([]); axis.set_yticks([])\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert to longitude-latitudes and write geojson"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(y0, x1), (y1, x0) = bounds\n",
    "\n",
    "scale_x = lambda x: ((x / im.shape[1]) * (x1 - x0) + x0).tolist()\n",
    "scale_y = lambda y: ((y / im.shape[0]) * (y1 - y0) + y0).tolist()\n",
    "\n",
    "contours_scaled = [\n",
    "    list(zip(scale_x(c[0][:, 1]), scale_y(c[0][:, 0])))\n",
    "    for c in contours\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "geojson = {\n",
    "  \"type\": \"FeatureCollection\",\n",
    "  \"features\": [\n",
    "    {\n",
    "      \"type\": \"Feature\",\n",
    "      \"properties\": {'dialect': dialect},\n",
    "      \"geometry\": {\n",
    "        \"type\": \"Polygon\",\n",
    "        \"coordinates\": [list(map(list, contour))]\n",
    "      }\n",
    "    }\n",
    "    for contour, dialect in zip(contours_scaled, regions)\n",
    "  ]\n",
    "}\n",
    "\n",
    "with open('../data/dialect_regions.geojson', 'w') as f:\n",
    "    json.dump(geojson, f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = folium.Map(\n",
    "    location=[(bounds[0][0] + bounds[1][0]) / 2, (bounds[0][1] + bounds[1][1]) / 2],\n",
    "    tiles='stamentoner',\n",
    "    zoom_start=9\n",
    ")\n",
    "\n",
    "for feature in geojson['features']:\n",
    "    folium.Polygon(\n",
    "        reverse_latitude_longitude(feature['geometry']['coordinates']),\n",
    "        color='red',\n",
    "        fill_color='white',\n",
    "        fill_opacity=0,\n",
    "        popup=feature['properties']['dialect']\n",
    "    ).add_to(m)\n",
    "\n",
    "m"
   ]
  }
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