#!/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 0.0 0.0 26.775226593018 57.591435321807 -gcp 15060.0 0.0 26.926889419556 57.579288973513 -gcp 15060.0 9744.0 26.912212371826 57.528912008523 -gcp 0.0 9744.0 26.761322021484 57.542549214785 LVVA_F7404_US1_GV1788_002..jpg LVVA_F7404_US1_GV1788_002..vrt

# Add cutline to VRT
gdalwarp -r $GDAL_SAMPLING_WARP -tps -dstalpha -cutline_srs EPSG:4326 \
  -cutline "POLYGON(($(echo -e \"4188.0 4173.05580693816\n4035.0 3950.874811463047\n3636.0 4229.921568627451\n3627.0 4364.974358974359\n3471.0 4602.156862745098\n3186.0 4656.06334841629\n2916.0 4590.016591251886\n2823.0 4472.974358974359\n2745.0 4457.915535444948\n2350.5 4666.508295625943\n2278.5 4701.006033182503\n2169.0 4709.997737556561\n2058.0 4762.530165912519\n1975.5 4737.039969834087\n1768.5 4647.021870286576\n1648.5 4541.966063348416\n1579.5 4551.010558069382\n1570.5 4410.0\n1539.0 4284.75\n1400.25 4245.75\n1321.5 4202.25\n1278.0 4143.75\n1246.5 4072.5\n1257.0 4022.25\n1317.375 3995.626696832579\n1352.25 4004.9898190045246\n1408.5 4080.0\n1430.25 4095.0\n1444.5 4081.5\n1446.75 4060.5\n1408.875 3997.869909502262\n1411.125 3941.6319758672703\n1455.75 3908.248491704374\n1509.75 3910.5\n1560.75 3931.5\n1629.75 4041.75\n1674.75 4077.748491704374\n1758.0 4088.2503770739067\n1788.75 4037.970588235294\n1790.25 3986.225113122172\n1764.0 3935.2228506787333\n1753.5 3879.75\n1768.5 3758.271870286576\n1826.25 3647.25\n1903.5 3612.75\n1956.0 3570.0\n2008.5 3447.75\n2106.0 3336.0\n2168.25 3294.75\n2242.5 3294.0\n2307.75 3309.75\n2340.75 3299.25\n2353.5 3264.0\n2346.75 3235.8763197586723\n2332.5 3211.8891402714935\n2343.375 3160.497737556561\n2350.5 2935.5\n2373.0 2860.5\n2382.0 2823.75\n2388.0 2792.25\n2363.25 2730.0\n2334.0 2658.0\n2254.5 2559.75\n2226.0 2505.75\n2237.25 2439.0\n2294.25 2335.5\n2318.25 2202.0\n2376.0 2142.0\n2418.0 2162.25\n2545.5 2027.25\n2495.25 1914.75\n2453.25 1794.0\n2325.0 1724.25\n2466.75 1598.25\n2544.0 1541.25\n2689.5 1422.0\n2804.25 1284.0\n3006.75 1132.5\n3162.75 1069.5\n3279.75 1008.0\n3313.5 957.0\n3320.25 909.75\n3359.25 900.75\n3431.25 973.5\n3501.75 1000.5\n3551.25 984.75\n3632.25 983.25\n3862.5 1040.25\n3978.75 1200.75\n4052.25 1266.75\n4129.5 1330.5\n4218.75 1359.75\n4320.0 1369.5\n4386.75 1362.0\n4452.0 1326.75\n4527.0 1206.0\n4674.0 1095.0\n4815.75 1004.25\n5018.25 937.5\n5236.5 891.75\n5520.0 894.0\n5796.0 816.0\n5795.25 775.5\n5839.5 741.0\n5918.25 716.25\n5967.0 654.75\n6024.75 608.25\n6063.75 632.25\n6106.5 621.75\n6095.25 555.0\n6102.0 510.0\n6271.5 504.75\n6267.0 612.0\n6156.75 676.5\n6157.5 724.5\n6213.75 768.0\n6256.5 830.25\n6268.5 904.5\n6229.5 935.25\n6222.0 963.75\n6218.25 1003.5\n6327.0 1127.25\n6486.75 1218.0\n6571.5 1491.0\n6644.25 1574.25\n6615.0 1779.75\n6618.0 1904.25\n6571.5 1964.25\n6228.0 2127.0\n6226.5 2206.5\n6239.25 2303.25\n6240.0 2402.25\n6237.0 2573.25\n6264.0 2689.5\n6480.75 3000.0\n6519.75 2999.25\n6677.25 2854.5\n6765.0 2833.5\n6849.0 2829.0\n7316.25 3088.5\n8154.0 3024.0\n8739.0 3315.0\n8757.0 3549.0\n8880.0 4020.0\n8787.0 4452.0\n8716.5 4609.5\n8640.0 4728.0\n8580.0 4785.0\n8583.0 4860.0\n8520.0 4924.5\n8370.0 4975.5\n8247.0 5107.5\n8049.0 5173.5\n7986.0 5323.5\n7893.0 5443.5\n7854.0 5566.5\n7810.5 5626.5\n7771.5 5773.5\n7594.5 5896.5\n7560.0 5959.5\n7596.0 6060.0\n7671.0 6159.0\n7669.5 6325.5\n7614.0 6492.0\n7596.0 6829.5\n7683.0 6975.0\n7659.0 7099.5\n7644.0 7194.0\n7667.25 7272.0\n7713.0 7331.25\n7584.0 7535.625\n7550.25 7551.75\n7503.75 7537.5\n7473.75 7600.5\n7425.75 7637.25\n7424.25 7666.5\n7406.25 7696.5\n7371.75 7724.25\n7335.0 7770.0\n7253.25 7773.0\n7192.5 7792.5\n7167.75 7794.75\n7156.5 7815.0\n7169.25 7857.75\n7134.0 7899.0\n7140.0 7928.25\n7134.75 7964.25\n7092.0 7984.5\n7074.0 8012.25\n7068.0 8038.5\n7031.25 8063.25\n6916.5 8093.25\n6840.0 8130.75\n6782.25 8183.25\n6750.0 8206.5\n6721.5 8217.0\n6687.75 8271.75\n6627.75 8309.25\n6601.5 8314.5\n6572.25 8344.5\n6500.25 8348.25\n6460.5 8380.5\n6417.75 8379.0\n6354.75 8421.75\n6313.5 8422.5\n6286.5 8479.5\n6243.0 8470.5\n6206.25 8517.0\n6144.0 8520.75\n6106.5 8562.0\n6060.0 8551.5\n6020.25 8577.75\n5966.25 8632.5\n5905.5 8642.25\n5872.5 8606.25\n5859.0 8559.75\n5801.25 8532.75\n5694.0 8521.5\n5610.0 8460.0\n4945.5 8212.5\n5134.5 7371.0\n4803.0 6570.0\n4845.0 5535.75\n5058.75 5439.0\n5101.5 5351.25\n5136.75 5291.25\n5136.75 5215.5\n5203.5 5169.0\n5207.25 5136.0\n5195.25 5101.5\n5107.5 5013.0\n5136.0 4951.5\n5168.25 4921.5\n5203.5 4851.0\n5252.25 4836.75\n5307.0 4845.75\n5331.0 4831.5\n5346.75 4807.5\n5356.5 4725.75\n5262.75 4581.75\n5091.0 4482.0\n5046.75 4473.75\n5001.75 4526.25\n4949.25 4563.75\n4875.0 4565.25\" | \
  gdaltransform -tps -output_xy LVVA_F7404_US1_GV1788_002..vrt | \
  awk 'NR==1{first=$0} {printf "%s %s,", $1,$2} END{print " " first}'))))" \
  LVVA_F7404_US1_GV1788_002..vrt LVVA_F7404_US1_GV1788_002..cut.vrt

# Generate tiles
gdal2tiles.py -r $GDAL_SAMPLING_TILE --xyz -z $GDAL_TILE_ZOOMS -x --processes=$GDAL_TILE_PROCESSES LVVA_F7404_US1_GV1788_002..cut.vrt LVVA_F7404_US1_GV1788_002..xyz