#!/bin/bash

GDAL_TILE_PROCESSES=16
GDAL_TILE_ZOOMS=8-14
GDAL_SAMPLING_WARP=cubic
GDAL_SAMPLING_TILE=antialias

# Create virtual dataset with coordinates
gdal_translate -of VRT -a_srs EPSG:4326 -outsize 300% 300% -gcp 1122.0 3329.2016397998887 26.337216666666666 57 -gcp 30717.0 3216.1500833796554 26.337216666666666 56.25 -gcp 30498.0 36961.91106170094 24.837216666666666 56.25 -gcp 990.0 36374.36131183991 24.837216666666666 57 Latvijas_top.kartes_Jaunjelgavas_un_Jekabpils_aprinkis_6828_A1_L37_2_02.JPG Latvijas_top.kartes_Jaunjelgavas_un_Jekabpils_aprinkis_6828_A1_L37_2_02.vrt

# Add cutline to VRT
gdalwarp -r $GDAL_SAMPLING_WARP -tps -dstalpha -cutline_srs EPSG:4326 \
  -cutline "POLYGON(($(echo -e "1140.0 19732.434130072263\n1120.5 3326.9949972206787\n15915.0 3239.983324068927\n30717.0 3213.0\n30706.5 20083.499166203444\n30501.0 36958.49749861034\n15754.5 36638.98499166203\n990.0 36374.99833240689" | \
  gdaltransform -tps -output_xy Latvijas_top.kartes_Jaunjelgavas_un_Jekabpils_aprinkis_6828_A1_L37_2_02.vrt | \
  awk 'NR==1{first=$0} {printf "%s %s,", $1,$2} END{print " " first}')))" \
  Latvijas_top.kartes_Jaunjelgavas_un_Jekabpils_aprinkis_6828_A1_L37_2_02.vrt Latvijas_top.kartes_Jaunjelgavas_un_Jekabpils_aprinkis_6828_A1_L37_2_02.cut.vrt

# Generate tiles
gdal2tiles.py -r $GDAL_SAMPLING_TILE --xyz -z $GDAL_TILE_ZOOMS -x --processes=$GDAL_TILE_PROCESSES Latvijas_top.kartes_Jaunjelgavas_un_Jekabpils_aprinkis_6828_A1_L37_2_02.cut.vrt Latvijas_top.kartes_Jaunjelgavas_un_Jekabpils_aprinkis_6828_A1_L37_2_02.xyz