#!/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 1527.4043977055449 2362.9131038312053 27 57.25 -gcp 20530.71797323136 2371.8814547473626 27.5 57.25 -gcp 20590.913001912046 19926.32148806219 27.5 57 -gcp 1464.3365200764817 19933.877290394226 27 57 LAT075_092_Balvi_1932_400dpi.jpg LAT075_092_Balvi_1932_400dpi.vrt

# Add cutline to VRT
gdalwarp -r $GDAL_SAMPLING_WARP -tps -dstalpha -cutline_srs EPSG:4326 \
  -cutline "POLYGON(($(echo -e "1527.4043977055449 2362.9131038312053\n20530.71797323136 2371.8814547473626\n20590.913001912046 19926.32148806219\n1464.3365200764817 19933.877290394226" | \
  gdaltransform -tps -output_xy LAT075_092_Balvi_1932_400dpi.vrt | \
  awk 'NR==1{first=$0} {printf "%s %s,", $1,$2} END{print " " first}')))" \
  LAT075_092_Balvi_1932_400dpi.vrt LAT075_092_Balvi_1932_400dpi.cut.vrt

# Generate tiles
gdal2tiles.py -r $GDAL_SAMPLING_TILE --xyz -z $GDAL_TILE_ZOOMS -x --processes=$GDAL_TILE_PROCESSES LAT075_092_Balvi_1932_400dpi.cut.vrt LAT075_092_Balvi_1932_400dpi.xyz