#!/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 403.6969831410825 667.7493051695386 21 57.5 -gcp 14695.437444543035 717.3285158421345 21.5 57.5 -gcp 14744.335181898847 13857.92843246248 21.5 57.25 -gcp 319.50865128660155 13816.679266259032 21 57.25 Lat075_002_Libciems_ca1930.jpg Lat075_002_Libciems_ca1930.vrt

# Add cutline to VRT
gdalwarp -r $GDAL_SAMPLING_WARP -tps -dstalpha -cutline_srs EPSG:4326 \
  -cutline "POLYGON(($(echo -e \"401.2493345164153 666.7495831017231\n315.0878438331854 13814.955808782657\n14743.378216503994 13857.769594219011\n14695.569210292813 710.988326848249\" | \
  gdaltransform -tps -output_xy Lat075_002_Libciems_ca1930.vrt | \
  awk 'NR==1{first=$0} {printf "%s %s,", $1,$2} END{print " " first}'))))" \
  Lat075_002_Libciems_ca1930.vrt Lat075_002_Libciems_ca1930.cut.vrt

# Generate tiles
gdal2tiles.py -r $GDAL_SAMPLING_TILE --xyz -z $GDAL_TILE_ZOOMS -x --processes=$GDAL_TILE_PROCESSES Lat075_002_Libciems_ca1930.cut.vrt Lat075_002_Libciems_ca1930.xyz