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gdal2tiles.py
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gdal2tiles.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# ******************************************************************************
# $Id$
#
# Project: Google Summer of Code 2007, 2008 (http://code.google.com/soc/)
# Support: BRGM (http://www.brgm.fr)
# Purpose: Convert a raster into TMS (Tile Map Service) tiles in a directory.
# - generate Google Earth metadata (KML SuperOverlay)
# - generate simple HTML viewer based on Google Maps and OpenLayers
# - support of global tiles (Spherical Mercator) for compatibility
# with interactive web maps a la Google Maps
# Author: Klokan Petr Pridal, klokan at klokan dot cz
# Web: http://www.klokan.cz/projects/gdal2tiles/
# GUI: http://www.maptiler.org/
#
###############################################################################
# Copyright (c) 2008, Klokan Petr Pridal
# Copyright (c) 2010-2013, Even Rouault <even dot rouault at spatialys.com>
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
# ******************************************************************************
from __future__ import print_function, division
import math
from multiprocessing import Pool
from functools import partial
import os
import tempfile
import threading
import shutil
import sys
from uuid import uuid4
from xml.etree import ElementTree
from osgeo import gdal
from osgeo import osr
try:
from PIL import Image
import numpy
import osgeo.gdal_array as gdalarray
numpy_available = True
except ImportError:
# 'antialias' resampling is not available
numpy_available = False
__version__ = "$Id$"
resampling_list = (
'average', 'near', 'bilinear', 'cubic', 'cubicspline', 'lanczos',
'antialias', 'mode', 'max', 'min', 'med', 'q1', 'q3')
profile_list = ('mercator', 'geodetic', 'raster')
webviewer_list = ('all', 'google', 'openlayers', 'leaflet', 'none')
threadLocal = threading.local()
# =============================================================================
# =============================================================================
# =============================================================================
__doc__globalmaptiles = """
globalmaptiles.py
Global Map Tiles as defined in Tile Map Service (TMS) Profiles
==============================================================
Functions necessary for generation of global tiles used on the web.
It contains classes implementing coordinate conversions for:
- GlobalMercator (based on EPSG:3857)
for Google Maps, Yahoo Maps, Bing Maps compatible tiles
- GlobalGeodetic (based on EPSG:4326)
for OpenLayers Base Map and Google Earth compatible tiles
More info at:
http://wiki.osgeo.org/wiki/Tile_Map_Service_Specification
http://wiki.osgeo.org/wiki/WMS_Tiling_Client_Recommendation
http://msdn.microsoft.com/en-us/library/bb259689.aspx
http://code.google.com/apis/maps/documentation/overlays.html#Google_Maps_Coordinates
Created by Klokan Petr Pridal on 2008-07-03.
Google Summer of Code 2008, project GDAL2Tiles for OSGEO.
In case you use this class in your product, translate it to another language
or find it useful for your project please let me know.
My email: klokan at klokan dot cz.
I would like to know where it was used.
Class is available under the open-source GDAL license (www.gdal.org).
"""
MAXZOOMLEVEL = 32
class GlobalMercator(object):
r"""
TMS Global Mercator Profile
---------------------------
Functions necessary for generation of tiles in Spherical Mercator projection,
EPSG:3857.
Such tiles are compatible with Google Maps, Bing Maps, Yahoo Maps,
UK Ordnance Survey OpenSpace API, ...
and you can overlay them on top of base maps of those web mapping applications.
Pixel and tile coordinates are in TMS notation (origin [0,0] in bottom-left).
What coordinate conversions do we need for TMS Global Mercator tiles::
LatLon <-> Meters <-> Pixels <-> Tile
WGS84 coordinates Spherical Mercator Pixels in pyramid Tiles in pyramid
lat/lon XY in meters XY pixels Z zoom XYZ from TMS
EPSG:4326 EPSG:387
.----. --------- -- TMS
/ \ <-> | | <-> /----/ <-> Google
\ / | | /--------/ QuadTree
----- --------- /------------/
KML, public WebMapService Web Clients TileMapService
What is the coordinate extent of Earth in EPSG:3857?
[-20037508.342789244, -20037508.342789244, 20037508.342789244, 20037508.342789244]
Constant 20037508.342789244 comes from the circumference of the Earth in meters,
which is 40 thousand kilometers, the coordinate origin is in the middle of extent.
In fact you can calculate the constant as: 2 * math.pi * 6378137 / 2.0
$ echo 180 85 | gdaltransform -s_srs EPSG:4326 -t_srs EPSG:3857
Polar areas with abs(latitude) bigger then 85.05112878 are clipped off.
What are zoom level constants (pixels/meter) for pyramid with EPSG:3857?
whole region is on top of pyramid (zoom=0) covered by 512x512 pixels tile,
every lower zoom level resolution is always divided by two
initialResolution = 20037508.342789244 * 2 / 512 = 156543.03392804062
What is the difference between TMS and Google Maps/QuadTree tile name convention?
The tile raster itself is the same (equal extent, projection, pixel size),
there is just different identification of the same raster tile.
Tiles in TMS are counted from [0,0] in the bottom-left corner, id is XYZ.
Google placed the origin [0,0] to the top-left corner, reference is XYZ.
Microsoft is referencing tiles by a QuadTree name, defined on the website:
http://msdn2.microsoft.com/en-us/library/bb259689.aspx
The lat/lon coordinates are using WGS84 datum, yes?
Yes, all lat/lon we are mentioning should use WGS84 Geodetic Datum.
Well, the web clients like Google Maps are projecting those coordinates by
Spherical Mercator, so in fact lat/lon coordinates on sphere are treated as if
the were on the WGS84 ellipsoid.
From MSDN documentation:
To simplify the calculations, we use the spherical form of projection, not
the ellipsoidal form. Since the projection is used only for map display,
and not for displaying numeric coordinates, we don't need the extra precision
of an ellipsoidal projection. The spherical projection causes approximately
0.33 percent scale distortion in the Y direction, which is not visually
noticeable.
How do I create a raster in EPSG:3857 and convert coordinates with PROJ.4?
You can use standard GIS tools like gdalwarp, cs2cs or gdaltransform.
All of the tools supports -t_srs 'epsg:3857'.
For other GIS programs check the exact definition of the projection:
More info at http://spatialreference.org/ref/user/google-projection/
The same projection is designated as EPSG:3857. WKT definition is in the
official EPSG database.
Proj4 Text:
+proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0
+k=1.0 +units=m +nadgrids=@null +no_defs
Human readable WKT format of EPSG:3857:
PROJCS["Google Maps Global Mercator",
GEOGCS["WGS 84",
DATUM["WGS_1984",
SPHEROID["WGS 84",6378137,298.257223563,
AUTHORITY["EPSG","7030"]],
AUTHORITY["EPSG","6326"]],
PRIMEM["Greenwich",0],
UNIT["degree",0.0174532925199433],
AUTHORITY["EPSG","4326"]],
PROJECTION["Mercator_1SP"],
PARAMETER["central_meridian",0],
PARAMETER["scale_factor",1],
PARAMETER["false_easting",0],
PARAMETER["false_northing",0],
UNIT["metre",1,
AUTHORITY["EPSG","9001"]]]
"""
def __init__(self, tile_size=512):
"Initialize the TMS Global Mercator pyramid"
self.tile_size = tile_size
self.initialResolution = 2 * math.pi * 6378137 / self.tile_size
# 156543.03392804062 for tile_size 512 pixels
self.originShift = 2 * math.pi * 6378137 / 2.0
# 20037508.342789244
def LatLonToMeters(self, lat, lon):
"Converts given lat/lon in WGS84 Datum to XY in Spherical Mercator EPSG:3857"
mx = lon * self.originShift / 180.0
my = math.log(math.tan((90 + lat) * math.pi / 360.0)) / (math.pi / 180.0)
my = my * self.originShift / 180.0
return mx, my
def MetersToLatLon(self, mx, my):
"Converts XY point from Spherical Mercator EPSG:3857 to lat/lon in WGS84 Datum"
lon = (mx / self.originShift) * 180.0
lat = (my / self.originShift) * 180.0
lat = 180 / math.pi * (2 * math.atan(math.exp(lat * math.pi / 180.0)) - math.pi / 2.0)
return lat, lon
def PixelsToMeters(self, px, py, zoom):
"Converts pixel coordinates in given zoom level of pyramid to EPSG:3857"
res = self.Resolution(zoom)
mx = px * res - self.originShift
my = py * res - self.originShift
return mx, my
def MetersToPixels(self, mx, my, zoom):
"Converts EPSG:3857 to pyramid pixel coordinates in given zoom level"
res = self.Resolution(zoom)
px = (mx + self.originShift) / res
py = (my + self.originShift) / res
return px, py
def PixelsToTile(self, px, py):
"Returns a tile covering region in given pixel coordinates"
tx = int(math.ceil(px / float(self.tile_size)) - 1)
ty = int(math.ceil(py / float(self.tile_size)) - 1)
return tx, ty
def PixelsToRaster(self, px, py, zoom):
"Move the origin of pixel coordinates to top-left corner"
mapSize = self.tile_size << zoom
return px, mapSize - py
def MetersToTile(self, mx, my, zoom):
"Returns tile for given mercator coordinates"
px, py = self.MetersToPixels(mx, my, zoom)
return self.PixelsToTile(px, py)
def TileBounds(self, tx, ty, zoom):
"Returns bounds of the given tile in EPSG:3857 coordinates"
minx, miny = self.PixelsToMeters(tx * self.tile_size, ty * self.tile_size, zoom)
maxx, maxy = self.PixelsToMeters((tx + 1) * self.tile_size, (ty + 1) * self.tile_size, zoom)
return (minx, miny, maxx, maxy)
def TileLatLonBounds(self, tx, ty, zoom):
"Returns bounds of the given tile in latitude/longitude using WGS84 datum"
bounds = self.TileBounds(tx, ty, zoom)
minLat, minLon = self.MetersToLatLon(bounds[0], bounds[1])
maxLat, maxLon = self.MetersToLatLon(bounds[2], bounds[3])
return (minLat, minLon, maxLat, maxLon)
def Resolution(self, zoom):
"Resolution (meters/pixel) for given zoom level (measured at Equator)"
# return (2 * math.pi * 6378137) / (self.tile_size * 2**zoom)
return self.initialResolution / (2**zoom)
def ZoomForPixelSize(self, pixelSize):
"Maximal scaledown zoom of the pyramid closest to the pixelSize."
for i in range(MAXZOOMLEVEL):
if pixelSize > self.Resolution(i):
return max(0, i - 1) # We don't want to scale up
return MAXZOOMLEVEL - 1
def GoogleTile(self, tx, ty, zoom):
"Converts TMS tile coordinates to Google Tile coordinates"
# coordinate origin is moved from bottom-left to top-left corner of the extent
return tx, (2**zoom - 1) - ty
def QuadTree(self, tx, ty, zoom):
"Converts TMS tile coordinates to Microsoft QuadTree"
quadKey = ""
ty = (2**zoom - 1) - ty
for i in range(zoom, 0, -1):
digit = 0
mask = 1 << (i - 1)
if (tx & mask) != 0:
digit += 1
if (ty & mask) != 0:
digit += 2
quadKey += str(digit)
return quadKey
class GlobalGeodetic(object):
r"""
TMS Global Geodetic Profile
---------------------------
Functions necessary for generation of global tiles in Plate Carre projection,
EPSG:4326, "unprojected profile".
Such tiles are compatible with Google Earth (as any other EPSG:4326 rasters)
and you can overlay the tiles on top of OpenLayers base map.
Pixel and tile coordinates are in TMS notation (origin [0,0] in bottom-left).
What coordinate conversions do we need for TMS Global Geodetic tiles?
Global Geodetic tiles are using geodetic coordinates (latitude,longitude)
directly as planar coordinates XY (it is also called Unprojected or Plate
Carre). We need only scaling to pixel pyramid and cutting to tiles.
Pyramid has on top level two tiles, so it is not square but rectangle.
Area [-180,-90,180,90] is scaled to 512x512 pixels.
TMS has coordinate origin (for pixels and tiles) in bottom-left corner.
Rasters are in EPSG:4326 and therefore are compatible with Google Earth.
LatLon <-> Pixels <-> Tiles
WGS84 coordinates Pixels in pyramid Tiles in pyramid
lat/lon XY pixels Z zoom XYZ from TMS
EPSG:4326
.----. ----
/ \ <-> /--------/ <-> TMS
\ / /--------------/
----- /--------------------/
WMS, KML Web Clients, Google Earth TileMapService
"""
def __init__(self, tmscompatible, tile_size=512):
self.tile_size = tile_size
if tmscompatible is not None:
# Defaults the resolution factor to 0.703125 (2 tiles @ level 0)
# Adhers to OSGeo TMS spec
# http://wiki.osgeo.org/wiki/Tile_Map_Service_Specification#global-geodetic
self.resFact = 180.0 / self.tile_size
else:
# Defaults the resolution factor to 1.40625 (1 tile @ level 0)
# Adheres OpenLayers, MapProxy, etc default resolution for WMTS
self.resFact = 360.0 / self.tile_size
def LonLatToPixels(self, lon, lat, zoom):
"Converts lon/lat to pixel coordinates in given zoom of the EPSG:4326 pyramid"
res = self.resFact / 2**zoom
px = (180 + lon) / res
py = (90 + lat) / res
return px, py
def PixelsToTile(self, px, py):
"Returns coordinates of the tile covering region in pixel coordinates"
tx = int(math.ceil(px / float(self.tile_size)) - 1)
ty = int(math.ceil(py / float(self.tile_size)) - 1)
return tx, ty
def LonLatToTile(self, lon, lat, zoom):
"Returns the tile for zoom which covers given lon/lat coordinates"
px, py = self.LonLatToPixels(lon, lat, zoom)
return self.PixelsToTile(px, py)
def Resolution(self, zoom):
"Resolution (arc/pixel) for given zoom level (measured at Equator)"
return self.resFact / 2**zoom
def ZoomForPixelSize(self, pixelSize):
"Maximal scaledown zoom of the pyramid closest to the pixelSize."
for i in range(MAXZOOMLEVEL):
if pixelSize > self.Resolution(i):
return max(0, i - 1) # We don't want to scale up
return MAXZOOMLEVEL - 1
def TileBounds(self, tx, ty, zoom):
"Returns bounds of the given tile"
res = self.resFact / 2**zoom
return (
tx * self.tile_size * res - 180,
ty * self.tile_size * res - 90,
(tx + 1) * self.tile_size * res - 180,
(ty + 1) * self.tile_size * res - 90
)
def TileLatLonBounds(self, tx, ty, zoom):
"Returns bounds of the given tile in the SWNE form"
b = self.TileBounds(tx, ty, zoom)
return (b[1], b[0], b[3], b[2])
class Zoomify(object):
"""
Tiles compatible with the Zoomify viewer
----------------------------------------
"""
def __init__(self, width, height, tile_size=512, tileformat='jpg'):
"""Initialization of the Zoomify tile tree"""
self.tile_size = tile_size
self.tileformat = tileformat
imagesize = (width, height)
tiles = (math.ceil(width / tile_size), math.ceil(height / tile_size))
# Size (in tiles) for each tier of pyramid.
self.tierSizeInTiles = []
self.tierSizeInTiles.append(tiles)
# Image size in pixels for each pyramid tierself
self.tierImageSize = []
self.tierImageSize.append(imagesize)
while (imagesize[0] > tile_size or imagesize[1] > tile_size):
imagesize = (math.floor(imagesize[0] / 2), math.floor(imagesize[1] / 2))
tiles = (math.ceil(imagesize[0] / tile_size), math.ceil(imagesize[1] / tile_size))
self.tierSizeInTiles.append(tiles)
self.tierImageSize.append(imagesize)
self.tierSizeInTiles.reverse()
self.tierImageSize.reverse()
# Depth of the Zoomify pyramid, number of tiers (zoom levels)
self.numberOfTiers = len(self.tierSizeInTiles)
# Number of tiles up to the given tier of pyramid.
self.tileCountUpToTier = []
self.tileCountUpToTier[0] = 0
for i in range(1, self.numberOfTiers + 1):
self.tileCountUpToTier.append(
self.tierSizeInTiles[i - 1][0] * self.tierSizeInTiles[i - 1][1] +
self.tileCountUpToTier[i - 1]
)
def tilefilename(self, x, y, z):
"""Returns filename for tile with given coordinates"""
tileIndex = x + y * self.tierSizeInTiles[z][0] + self.tileCountUpToTier[z]
return os.path.join("TileGroup%.0f" % math.floor(tileIndex / 512),
"%s-%s-%s.%s" % (z, x, y, self.tileformat))
class GDALError(Exception):
pass
def exit_with_error(message, details=""):
# Message printing and exit code kept from the way it worked using the OptionParser (in case
# someone parses the error output)
sys.stderr.write("Usage: gdal2tiles.py [options] input_file [output]\n\n")
sys.stderr.write("gdal2tiles.py: error: %s\n" % message)
if details:
sys.stderr.write("\n\n%s\n" % details)
sys.exit(2)
def generate_kml(tx, ty, tz, tileext, tile_size, tileswne, options, children=None, **args):
"""
Template for the KML. Returns filled string.
"""
if not children:
children = []
args['tx'], args['ty'], args['tz'] = tx, ty, tz
args['tileformat'] = tileext
if 'tile_size' not in args:
args['tile_size'] = tile_size
if 'minlodpixels' not in args:
args['minlodpixels'] = int(args['tile_size'] / 2)
if 'maxlodpixels' not in args:
args['maxlodpixels'] = int(args['tile_size'] * 8)
if children == []:
args['maxlodpixels'] = -1
if tx is None:
tilekml = False
args['title'] = options.title
else:
tilekml = True
args['title'] = "%d/%d/%d.kml" % (tz, tx, ty)
args['south'], args['west'], args['north'], args['east'] = tileswne(tx, ty, tz)
if tx == 0:
args['drawOrder'] = 2 * tz + 1
elif tx is not None:
args['drawOrder'] = 2 * tz
else:
args['drawOrder'] = 0
url = options.url
if not url:
if tilekml:
url = "../../"
else:
url = ""
s = """<?xml version="1.0" encoding="utf-8"?>
<kml xmlns="http://www.opengis.net/kml/2.2">
<Document>
<name>%(title)s</name>
<description></description>
<Style>
<ListStyle id="hideChildren">
<listItemType>checkHideChildren</listItemType>
</ListStyle>
</Style>""" % args
if tilekml:
s += """
<Region>
<LatLonAltBox>
<north>%(north).14f</north>
<south>%(south).14f</south>
<east>%(east).14f</east>
<west>%(west).14f</west>
</LatLonAltBox>
<Lod>
<minLodPixels>%(minlodpixels)d</minLodPixels>
<maxLodPixels>%(maxlodpixels)d</maxLodPixels>
</Lod>
</Region>
<GroundOverlay>
<drawOrder>%(drawOrder)d</drawOrder>
<Icon>
<href>%(ty)d.%(tileformat)s</href>
</Icon>
<LatLonBox>
<north>%(north).14f</north>
<south>%(south).14f</south>
<east>%(east).14f</east>
<west>%(west).14f</west>
</LatLonBox>
</GroundOverlay>
""" % args
for cx, cy, cz in children:
csouth, cwest, cnorth, ceast = tileswne(cx, cy, cz)
s += """
<NetworkLink>
<name>%d/%d/%d.%s</name>
<Region>
<LatLonAltBox>
<north>%.14f</north>
<south>%.14f</south>
<east>%.14f</east>
<west>%.14f</west>
</LatLonAltBox>
<Lod>
<minLodPixels>%d</minLodPixels>
<maxLodPixels>-1</maxLodPixels>
</Lod>
</Region>
<Link>
<href>%s%d/%d/%d.kml</href>
<viewRefreshMode>onRegion</viewRefreshMode>
<viewFormat/>
</Link>
</NetworkLink>
""" % (cz, cx, cy, args['tileformat'], cnorth, csouth, ceast, cwest,
args['minlodpixels'], url, cz, cx, cy)
s += """ </Document>
</kml>
"""
return s
def scale_query_to_tile(dsquery, dstile, tiledriver, options, tilefilename=''):
"""Scales down query dataset to the tile dataset"""
querysize = dsquery.RasterXSize
tile_size = dstile.RasterXSize
tilebands = dstile.RasterCount
if options.resampling == 'average':
# Function: gdal.RegenerateOverview()
for i in range(1, tilebands + 1):
# Black border around NODATA
res = gdal.RegenerateOverview(dsquery.GetRasterBand(i), dstile.GetRasterBand(i),
'average')
if res != 0:
exit_with_error("RegenerateOverview() failed on %s, error %d" % (
tilefilename, res))
elif options.resampling == 'antialias' and numpy_available:
# Scaling by PIL (Python Imaging Library) - improved Lanczos
array = numpy.zeros((querysize, querysize, tilebands), numpy.uint8)
for i in range(tilebands):
array[:, :, i] = gdalarray.BandReadAsArray(dsquery.GetRasterBand(i + 1),
0, 0, querysize, querysize)
im = Image.fromarray(array, 'RGBA') # Always four bands
im1 = im.resize((tile_size, tile_size), Image.ANTIALIAS)
if os.path.exists(tilefilename):
im0 = Image.open(tilefilename)
im1 = Image.composite(im1, im0, im1)
im1.save(tilefilename, tiledriver)
else:
if options.resampling == 'near':
gdal_resampling = gdal.GRA_NearestNeighbour
elif options.resampling == 'bilinear':
gdal_resampling = gdal.GRA_Bilinear
elif options.resampling == 'cubic':
gdal_resampling = gdal.GRA_Cubic
elif options.resampling == 'cubicspline':
gdal_resampling = gdal.GRA_CubicSpline
elif options.resampling == 'lanczos':
gdal_resampling = gdal.GRA_Lanczos
elif options.resampling == 'mode':
gdal_resampling = gdal.GRA_Mode
elif options.resampling == 'max':
gdal_resampling = gdal.GRA_Max
elif options.resampling == 'min':
gdal_resampling = gdal.GRA_Min
elif options.resampling == 'med':
gdal_resampling = gdal.GRA_Med
elif options.resampling == 'q1':
gdal_resampling = gdal.GRA_Q1
elif options.resampling == 'q3':
gdal_resampling = gdal.GRA_Q3
# Other algorithms are implemented by gdal.ReprojectImage().
dsquery.SetGeoTransform((0.0, tile_size / float(querysize), 0.0, 0.0, 0.0,
tile_size / float(querysize)))
dstile.SetGeoTransform((0.0, 1.0, 0.0, 0.0, 0.0, 1.0))
res = gdal.ReprojectImage(dsquery, dstile, None, None, gdal_resampling)
if res != 0:
exit_with_error("ReprojectImage() failed on %s, error %d" % (tilefilename, res))
def setup_no_data_values(input_dataset, options):
"""
Extract the NODATA values from the dataset or use the passed arguments as override if any
"""
in_nodata = []
if options.srcnodata:
nds = list(map(float, options.srcnodata.split(',')))
if len(nds) < input_dataset.RasterCount:
in_nodata = (nds * input_dataset.RasterCount)[:input_dataset.RasterCount]
else:
in_nodata = nds
else:
for i in range(1, input_dataset.RasterCount + 1):
raster_no_data = input_dataset.GetRasterBand(i).GetNoDataValue()
if raster_no_data is not None:
in_nodata.append(raster_no_data)
if options.verbose:
print("NODATA: %s" % in_nodata)
return in_nodata
def setup_input_srs(input_dataset, options):
"""
Determines and returns the Input Spatial Reference System (SRS) as an osr object and as a
WKT representation
Uses in priority the one passed in the command line arguments. If None, tries to extract them
from the input dataset
"""
input_srs = None
input_srs_wkt = None
if options.s_srs:
input_srs = osr.SpatialReference()
input_srs.SetFromUserInput(options.s_srs)
input_srs_wkt = input_srs.ExportToWkt()
else:
input_srs_wkt = input_dataset.GetProjection()
if not input_srs_wkt and input_dataset.GetGCPCount() != 0:
input_srs_wkt = input_dataset.GetGCPProjection()
if input_srs_wkt:
input_srs = osr.SpatialReference()
input_srs.ImportFromWkt(input_srs_wkt)
input_srs.SetAxisMappingStrategy(osr.OAMS_TRADITIONAL_GIS_ORDER)
return input_srs, input_srs_wkt
def setup_output_srs(input_srs, options):
"""
Setup the desired SRS (based on options)
"""
output_srs = osr.SpatialReference()
output_srs.SetAxisMappingStrategy(osr.OAMS_TRADITIONAL_GIS_ORDER)
if options.profile == 'mercator':
output_srs.ImportFromEPSG(3857)
elif options.profile == 'geodetic':
output_srs.ImportFromEPSG(4326)
else:
output_srs = input_srs
return output_srs
def has_georeference(dataset):
return (dataset.GetGeoTransform() != (0.0, 1.0, 0.0, 0.0, 0.0, 1.0) or
dataset.GetGCPCount() != 0)
def reproject_dataset(from_dataset, from_srs, to_srs, options=None):
"""
Returns the input dataset in the expected "destination" SRS.
If the dataset is already in the correct SRS, returns it unmodified
"""
if not from_srs or not to_srs:
raise GDALError("from and to SRS must be defined to reproject the dataset")
if (from_srs.ExportToProj4() != to_srs.ExportToProj4()) or (from_dataset.GetGCPCount() != 0):
to_dataset = gdal.AutoCreateWarpedVRT(from_dataset,
from_srs.ExportToWkt(), to_srs.ExportToWkt())
if options and options.verbose:
print("Warping of the raster by AutoCreateWarpedVRT (result saved into 'tiles.vrt')")
to_dataset.GetDriver().CreateCopy("tiles.vrt", to_dataset)
return to_dataset
else:
return from_dataset
def add_gdal_warp_options_to_string(vrt_string, warp_options):
if not warp_options:
return vrt_string
vrt_root = ElementTree.fromstring(vrt_string)
options = vrt_root.find("GDALWarpOptions")
if options is None:
return vrt_string
for key, value in warp_options.items():
tb = ElementTree.TreeBuilder()
tb.start("Option", {"name": key})
tb.data(value)
tb.end("Option")
elem = tb.close()
options.insert(0, elem)
return ElementTree.tostring(vrt_root).decode()
def update_no_data_values(warped_vrt_dataset, nodata_values, options=None):
"""
Takes an array of NODATA values and forces them on the WarpedVRT file dataset passed
"""
# TODO: gbataille - Seems that I forgot tests there
assert nodata_values != []
vrt_string = warped_vrt_dataset.GetMetadata("xml:VRT")[0]
vrt_string = add_gdal_warp_options_to_string(
vrt_string, {"INIT_DEST": "NO_DATA", "UNIFIED_SRC_NODATA": "YES"})
# TODO: gbataille - check the need for this replacement. Seems to work without
# # replace BandMapping tag for NODATA bands....
# for i in range(len(nodata_values)):
# s = s.replace(
# '<BandMapping src="%i" dst="%i"/>' % ((i+1), (i+1)),
# """
# <BandMapping src="%i" dst="%i">
# <SrcNoDataReal>%i</SrcNoDataReal>
# <SrcNoDataImag>0</SrcNoDataImag>
# <DstNoDataReal>%i</DstNoDataReal>
# <DstNoDataImag>0</DstNoDataImag>
# </BandMapping>
# """ % ((i+1), (i+1), nodata_values[i], nodata_values[i]))
corrected_dataset = gdal.Open(vrt_string)
# set NODATA_VALUE metadata
corrected_dataset.SetMetadataItem(
'NODATA_VALUES', ' '.join([str(i) for i in nodata_values]))
if options and options.verbose:
print("Modified warping result saved into 'tiles1.vrt'")
with open("tiles1.vrt", "w") as f:
f.write(corrected_dataset.GetMetadata("xml:VRT")[0])
return corrected_dataset
def add_alpha_band_to_string_vrt(vrt_string):
# TODO: gbataille - Old code speak of this being equivalent to gdalwarp -dstalpha
# To be checked
vrt_root = ElementTree.fromstring(vrt_string)
index = 0
nb_bands = 0
for subelem in list(vrt_root):
if subelem.tag == "VRTRasterBand":
nb_bands += 1
color_node = subelem.find("./ColorInterp")
if color_node is not None and color_node.text == "Alpha":
raise Exception("Alpha band already present")
else:
if nb_bands:
# This means that we are one element after the Band definitions
break
index += 1
tb = ElementTree.TreeBuilder()
tb.start("VRTRasterBand",
{'dataType': "Byte", "band": str(nb_bands + 1), "subClass": "VRTWarpedRasterBand"})
tb.start("ColorInterp", {})
tb.data("Alpha")
tb.end("ColorInterp")
tb.end("VRTRasterBand")
elem = tb.close()
vrt_root.insert(index, elem)
warp_options = vrt_root.find(".//GDALWarpOptions")
tb = ElementTree.TreeBuilder()
tb.start("DstAlphaBand", {})
tb.data(str(nb_bands + 1))
tb.end("DstAlphaBand")
elem = tb.close()
warp_options.append(elem)
# TODO: gbataille - this is a GDALWarpOptions. Why put it in a specific place?
tb = ElementTree.TreeBuilder()
tb.start("Option", {"name": "INIT_DEST"})
tb.data("0")
tb.end("Option")
elem = tb.close()
warp_options.append(elem)
return ElementTree.tostring(vrt_root).decode()
def update_alpha_value_for_non_alpha_inputs(warped_vrt_dataset, options=None):
"""
Handles dataset with 1 or 3 bands, i.e. without alpha channel, in the case the nodata value has
not been forced by options
"""
if warped_vrt_dataset.RasterCount in [1, 3]:
vrt_string = warped_vrt_dataset.GetMetadata("xml:VRT")[0]
vrt_string = add_alpha_band_to_string_vrt(vrt_string)
warped_vrt_dataset = gdal.Open(vrt_string)
if options and options.verbose:
print("Modified -dstalpha warping result saved into 'tiles1.vrt'")
with open("tiles1.vrt", "w") as f:
f.write(warped_vrt_dataset.GetMetadata("xml:VRT")[0])
return warped_vrt_dataset
def nb_data_bands(dataset):
"""
Return the number of data (non-alpha) bands of a gdal dataset
"""
alphaband = dataset.GetRasterBand(1).GetMaskBand()
if ((alphaband.GetMaskFlags() & gdal.GMF_ALPHA) or
dataset.RasterCount == 4 or
dataset.RasterCount == 2):
return dataset.RasterCount - 1
return dataset.RasterCount
def create_base_tile(tile_job_info, tile_detail):
dataBandsCount = tile_job_info.nb_data_bands
output = tile_job_info.output_file_path
tileext = tile_job_info.tile_extension
tile_size = tile_job_info.tile_size
options = tile_job_info.options
tilebands = dataBandsCount + 1
cached_ds = getattr(threadLocal, 'cached_ds', None)
if cached_ds and cached_ds.GetDescription() == tile_job_info.src_file:
ds = cached_ds
else:
ds = gdal.Open(tile_job_info.src_file, gdal.GA_ReadOnly)
threadLocal.cached_ds = ds
mem_drv = gdal.GetDriverByName('MEM')
out_drv = gdal.GetDriverByName(tile_job_info.tile_driver)
alphaband = ds.GetRasterBand(1).GetMaskBand()
tx = tile_detail.tx
ty = tile_detail.ty
tz = tile_detail.tz
rx = tile_detail.rx
ry = tile_detail.ry
rxsize = tile_detail.rxsize
rysize = tile_detail.rysize
wx = tile_detail.wx
wy = tile_detail.wy
wxsize = tile_detail.wxsize
wysize = tile_detail.wysize
querysize = tile_detail.querysize
# Tile dataset in memory
tilefilename = os.path.join(
output, str(tz), str(tx), "%s.%s" % (ty, tileext))
dstile = mem_drv.Create('', tile_size, tile_size, tilebands)
data = alpha = None
if options.verbose:
print("\tReadRaster Extent: ",
(rx, ry, rxsize, rysize), (wx, wy, wxsize, wysize))
# Query is in 'nearest neighbour' but can be bigger in then the tile_size
# We scale down the query to the tile_size by supplied algorithm.
if rxsize != 0 and rysize != 0 and wxsize != 0 and wysize != 0:
alpha = alphaband.ReadRaster(rx, ry, rxsize, rysize, wxsize, wysize)
# Detect totally transparent tile and skip its creation
if tile_job_info.exclude_transparent and len(alpha) == alpha.count('\x00'.encode('ascii')):
return
data = ds.ReadRaster(rx, ry, rxsize, rysize, wxsize, wysize,
band_list=list(range(1, dataBandsCount + 1)))
# The tile in memory is a transparent file by default. Write pixel values into it if
# any
if data:
if tile_size == querysize:
# Use the ReadRaster result directly in tiles ('nearest neighbour' query)
dstile.WriteRaster(wx, wy, wxsize, wysize, data,
band_list=list(range(1, dataBandsCount + 1)))
dstile.WriteRaster(wx, wy, wxsize, wysize, alpha, band_list=[tilebands])
# Note: For source drivers based on WaveLet compression (JPEG2000, ECW,
# MrSID) the ReadRaster function returns high-quality raster (not ugly
# nearest neighbour)
# TODO: Use directly 'near' for WaveLet files
else:
# Big ReadRaster query in memory scaled to the tile_size - all but 'near'
# algo
dsquery = mem_drv.Create('', querysize, querysize, tilebands)
# TODO: fill the null value in case a tile without alpha is produced (now
# only png tiles are supported)
dsquery.WriteRaster(wx, wy, wxsize, wysize, data,
band_list=list(range(1, dataBandsCount + 1)))
dsquery.WriteRaster(wx, wy, wxsize, wysize, alpha, band_list=[tilebands])
scale_query_to_tile(dsquery, dstile, tile_job_info.tile_driver, options,
tilefilename=tilefilename)