{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "import pyrosm\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import shapely\n",
    "import pyproj\n",
    "\n",
    "import src.data.mapillary as mapi\n",
    "import src.data.osm as osmd\n",
    "#from src.data.mapillary import download_mapillary_image_by_key, download_mapillary_object_detection_by_key\n",
    "#from src.data.osm import add_mapillary_key_to_network\n",
    "from ipyleaflet import Map, Marker, Icon, Polyline, FullScreenControl\n",
    "from importlib import reload\n",
    "from tqdm.notebook import tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "input_filepath = \"../data/raw/berlin-latest.osm.pbf\"\n",
    "min_quality_score = 4\n",
    "output_dir = Path(\"../data/processed/out\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Code (see make_dataset.py)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "osm = pyrosm.OSM(input_filepath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "network = osm.get_network(\n",
    "    network_type=\"cycling\",\n",
    "    extra_attributes=[\"surface\", \"smoothness\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "network = network.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Filter relevant columns\n",
    "network = network[[\"id\", \"geometry\", \"surface\", \"smoothness\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Filter only records where both surface and smoothness is set\n",
    "network = network[(~network[\"surface\"].isna()) & (~network[\"smoothness\"].isna())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Request URL: https://a.mapillary.com/v3/images?client_id=TmxURHBKRFFFRTc1dWZscGpLWW5VUDo1ZjYyYmFjYjY5MTA3MDNk&bbox=13.526105139690427,52.4891476086417,13.5277082950903,52.49031200789549&per_page=500&sort_by=key&min_quality_score=4\n",
      "DONE\n",
      "Total images: 42\n"
     ]
    }
   ],
   "source": [
    "# Get Mapillary keys for each street\n",
    "street_mapillary_df = osmd.add_mapillary_key_to_network(network.head(1), \n",
    "                                                        street_buffer=5,\n",
    "                                                        shorten_street_by=30,\n",
    "                                                        min_quality_score=min_quality_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "                                            geometry         id  \\\n",
       "2  MULTILINESTRING ((13.52783 52.49043, 13.52639 ...  4045220.0   \n",
       "2  MULTILINESTRING ((13.52783 52.49043, 13.52639 ...  4045220.0   \n",
       "2  MULTILINESTRING ((13.52783 52.49043, 13.52639 ...  4045220.0   \n",
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       "2  MULTILINESTRING ((13.52783 52.49043, 13.52639 ...  4045220.0   \n",
       "\n",
       "                      img_coords           mapillary_key smoothness surface  \n",
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      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "street_mapillary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Create output dir\n",
    "Path(f\"{output_dir}\").mkdir(parents=True, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Create sub dirs\n",
    "image_dir = output_dir/ \"images\"\n",
    "object_detection_dir = output_dir / \"object_detections\"\n",
    "\n",
    "image_dir.mkdir(exist_ok=True)\n",
    "object_detection_dir.mkdir(exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Export street_mapillary_df as data.csv\n",
    "csv_filepath = output_dir / \"data.csv\"\n",
    "street_mapillary_df.to_csv(csv_filepath, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d187651267504f2ba241822deebb1d7e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "../data/processed/out/images/pL2n6QmeQSa0mVlTyoLilw.jpg already exists. Skipping Download.\n"
     ]
    }
   ],
   "source": [
    "# Download images and object detections\n",
    "for _, row in tqdm(street_mapillary_df.iterrows(), total=len(street_mapillary_df)):\n",
    "    mapi.download_mapillary_image_by_key(row[\"mapillary_key\"], download_dir=image_dir)\n",
    "    #download_mapillary_object_detection_by_key(row[\"mapillary_key\"],\n",
    "                                               #download_dir=object_detection_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2ab0d508bef340e996b9b077d7ba4ce9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[52.4896728, 13.5268612], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Display a map with the streets and images\n",
    "\n",
    "map_center = street_mapillary_df.iloc[0].img_coords\n",
    "map_center = [map_center.y, map_center.x]\n",
    "\n",
    "street_id_added = list()  # list with added streets to avoid adding them multiple times\n",
    "m = Map(zoom=16, center=map_center, max_zoom=22, scroll_wheel_zoom=True)\n",
    "for _, row in street_mapillary_df.iterrows():\n",
    "    img_path = Path(output_dir) / \"images\" / (row.mapillary_key + \".jpg\")\n",
    "    assert img_path.is_file(), img_path\n",
    "    icon = Icon(icon_url=str(img_path), \n",
    "                icon_size=[177, 100])\n",
    "    marker_center = [row.img_coords.y, row.img_coords.x]\n",
    "    marker = Marker(location=marker_center, draggable=False, icon=icon)\n",
    "    m.add_layer(marker)\n",
    "    \n",
    "    if row.id not in street_id_added:\n",
    "        street_id_added.append(row.id)\n",
    "        line_shapely = row.geometry\n",
    "        line_map_locactions = list()\n",
    "\n",
    "        for single_line in line_shapely.geoms:\n",
    "            line_map_locactions.extend([reversed(p) for p in single_line.coords])\n",
    "        \n",
    "        line = Polyline(\n",
    "            locations=line_map_locactions,\n",
    "            color=\"green\" ,\n",
    "            fill=False\n",
    "        )\n",
    "        m.add_layer(line)\n",
    "        \n",
    "m.add_control(FullScreenControl())       \n",
    "m"
   ]
  }
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