NumpyTile.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import mercantile\n",
    "from io import BytesIO\n",
    "import numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "titiler_endpoint = \"https://api.cogeo.xyz\"  # Devseed temporary endpoint\n",
    "url = \"https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.get(f\"{titiler_endpoint}/cog/tilejson.json?url={url}\").json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'tilejson': '2.2.0', 'name': '105001001F1B5B00.tif', 'version': '1.0.0', 'scheme': 'xyz', 'tiles': ['https://api.cogeo.xyz/cog/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?url=https%3A%2F%2Fopendata.digitalglobe.com%2Fevents%2Fmauritius-oil-spill%2Fpost-event%2F2020-08-12%2F105001001F1B5B00%2F105001001F1B5B00.tif'], 'minzoom': 10, 'maxzoom': 18, 'bounds': [57.664053823239804, -20.55473177712791, 57.84021477996238, -20.25261582755764], 'center': [57.75213430160109, -20.403673802342773, 10]}\n"
     ]
    }
   ],
   "source": [
    "print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "tiles = list(mercantile.tiles(*r[\"bounds\"], r[\"minzoom\"] + 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "tile = tiles[0]\n",
    "r = requests.get(f\"{titiler_endpoint}/cog/tiles/{tile.z}/{tile.x}/{tile.y}.npy?url={url}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "arr = numpy.load(BytesIO(r.content))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "tile, mask = arr[0:-1], arr[-1]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}