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gdal2tiles_new.py
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gdal2tiles_new.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#******************************************************************************
# $Id: gdal2tiles.py 27044 2014-03-16 23:41:27Z rouault $
#
# 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 mines-paris dot org>
#
# 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.
#******************************************************************************
import sys
try:
from osgeo import gdal
from osgeo import osr
except:
import gdal
print('You are using "old gen" bindings. gdal2tiles needs "new gen" bindings.')
sys.exit(1)
import os
import math
try:
from PIL import Image
import numpy
import osgeo.gdal_array as gdalarray
except:
# 'antialias' resampling is not available
pass
__version__ = "$Id: gdal2tiles.py 27044 2014-03-16 23:41:27Z rouault $"
resampling_list = ('average','near','bilinear','cubic','cubicspline','lanczos','antialias')
profile_list = ('mercator','geodetic','raster') #,'zoomify')
webviewer_list = ('all','google','openlayers','none')
# =============================================================================
# =============================================================================
# =============================================================================
__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:900913 = EPSG:3785)
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 usefull 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).
"""
import math
MAXZOOMLEVEL = 32
class GlobalMercator(object):
"""
TMS Global Mercator Profile
---------------------------
Functions necessary for generation of tiles in Spherical Mercator projection,
EPSG:900913 (EPSG:gOOglE, Google Maps Global Mercator), EPSG:3785, OSGEO:41001.
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 metres XY pixels Z zoom XYZ from TMS
EPSG:4326 EPSG:900913
.----. --------- -- TMS
/ \ <-> | | <-> /----/ <-> Google
\ / | | /--------/ QuadTree
----- --------- /------------/
KML, public WebMapService Web Clients TileMapService
What is the coordinate extent of Earth in EPSG:900913?
[-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:900913
Polar areas with abs(latitude) bigger then 85.05112878 are clipped off.
What are zoom level constants (pixels/meter) for pyramid with EPSG:900913?
whole region is on top of pyramid (zoom=0) covered by 256x256 pixels tile,
every lower zoom level resolution is always divided by two
initialResolution = 20037508.342789244 * 2 / 256 = 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, yeh?
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 noticable.
How do I create a raster in EPSG:900913 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:900913'.
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 degined as EPSG:3785. 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 EPGS:900913:
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, tileSize=256):
"Initialize the TMS Global Mercator pyramid"
self.tileSize = tileSize
self.initialResolution = 2 * math.pi * 6378137 / self.tileSize
# 156543.03392804062 for tileSize 256 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:900913"
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:900913 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:900913"
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:900913 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.tileSize) ) - 1 )
ty = int( math.ceil( py / float(self.tileSize) ) - 1 )
return tx, ty
def PixelsToRaster(self, px, py, zoom):
"Move the origin of pixel coordinates to top-left corner"
mapSize = self.tileSize << 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:900913 coordinates"
minx, miny = self.PixelsToMeters( tx*self.tileSize, ty*self.tileSize, zoom )
maxx, maxy = self.PixelsToMeters( (tx+1)*self.tileSize, (ty+1)*self.tileSize, zoom )
return ( minx, miny, maxx, maxy )
def TileLatLonBounds(self, tx, ty, zoom ):
"Returns bounds of the given tile in latutude/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.tileSize * 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):
if i!=0:
return i-1
else:
return 0 # We don't want to scale up
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):
"""
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 512x256 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, tileSize = 256):
self.tileSize = tileSize
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.tileSize
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.tileSize
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.tileSize) ) - 1 )
ty = int( math.ceil( py / float(self.tileSize) ) - 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
#return 180 / float( 1 << (8+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):
if i!=0:
return i-1
else:
return 0 # We don't want to scale up
def TileBounds(self, tx, ty, zoom):
"Returns bounds of the given tile"
res = self.resFact / 2**zoom
return (
tx*self.tileSize*res - 180,
ty*self.tileSize*res - 90,
(tx+1)*self.tileSize*res - 180,
(ty+1)*self.tileSize*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])
#---------------------
# TODO: Finish Zoomify implemtentation!!!
class Zoomify(object):
"""
Tiles compatible with the Zoomify viewer
----------------------------------------
"""
def __init__(self, width, height, tilesize = 256, tileformat='jpg'):
"""Initialization of the Zoomify tile tree"""
self.tilesize = tilesize
self.tileformat = tileformat
imagesize = (width, height)
tiles = ( math.ceil( width / tilesize ), math.ceil( height / tilesize ) )
# Size (in tiles) for each tier of pyramid.
self.tierSizeInTiles = []
self.tierSizeInTiles.push( tiles )
# Image size in pixels for each pyramid tierself
self.tierImageSize = []
self.tierImageSize.append( imagesize );
while (imagesize[0] > tilesize or imageSize[1] > tilesize ):
imagesize = (math.floor( imagesize[0] / 2 ), math.floor( imagesize[1] / 2) )
tiles = ( math.ceil( imagesize[0] / tilesize ), math.ceil( imagesize[1] / tilesize ) )
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 / 256 ),
"%s-%s-%s.%s" % ( z, x, y, self.tileformat))
# =============================================================================
# =============================================================================
# =============================================================================
class GDAL2Tiles(object):
# -------------------------------------------------------------------------
def process(self):
"""The main processing function, runs all the main steps of processing"""
# Opening and preprocessing of the input file
self.open_input()
# Generation of main metadata files and HTML viewers
self.generate_metadata()
# Generation of the lowest tiles
self.generate_base_tiles()
# Generation of the overview tiles (higher in the pyramid)
self.generate_overview_tiles()
# -------------------------------------------------------------------------
def error(self, msg, details = "" ):
"""Print an error message and stop the processing"""
if details:
self.parser.error(msg + "\n\n" + details)
else:
self.parser.error(msg)
# -------------------------------------------------------------------------
def progressbar(self, complete = 0.0):
"""Print progressbar for float value 0..1"""
gdal.TermProgress_nocb(complete)
# -------------------------------------------------------------------------
def stop(self):
"""Stop the rendering immediately"""
self.stopped = True
# -------------------------------------------------------------------------
def __init__(self, arguments ):
"""Constructor function - initialization"""
self.stopped = False
self.input = None
self.output = None
# Tile format
self.tilesize = 256
self.tiledriver = 'PNG'
self.tileext = 'png'
# Should we read bigger window of the input raster and scale it down?
# Note: Modified leter by open_input()
# Not for 'near' resampling
# Not for Wavelet based drivers (JPEG2000, ECW, MrSID)
# Not for 'raster' profile
self.scaledquery = True
# How big should be query window be for scaling down
# Later on reset according the chosen resampling algorightm
self.querysize = 4 * self.tilesize
# Should we use Read on the input file for generating overview tiles?
# Note: Modified later by open_input()
# Otherwise the overview tiles are generated from existing underlying tiles
self.overviewquery = False
# RUN THE ARGUMENT PARSER:
self.optparse_init()
self.options, self.args = self.parser.parse_args(args=arguments)
if not self.args:
self.error("No input file specified")
# POSTPROCESSING OF PARSED ARGUMENTS:
# Workaround for old versions of GDAL
try:
if (self.options.verbose and self.options.resampling == 'near') or gdal.TermProgress_nocb:
pass
except:
self.error("This version of GDAL is not supported. Please upgrade to 1.6+.")
#,"You can try run crippled version of gdal2tiles with parameters: -v -r 'near'")
# Is output directory the last argument?
# Test output directory, if it doesn't exist
if os.path.isdir(self.args[-1]) or ( len(self.args) > 1 and not os.path.exists(self.args[-1])):
self.output = self.args[-1]
self.args = self.args[:-1]
# More files on the input not directly supported yet
if (len(self.args) > 1):
self.error("Processing of several input files is not supported.",
"""Please first use a tool like gdal_vrtmerge.py or gdal_merge.py on the files:
gdal_vrtmerge.py -o merged.vrt %s""" % " ".join(self.args))
# TODO: Call functions from gdal_vrtmerge.py directly
self.input = self.args[0]
# Default values for not given options
if not self.output:
# Directory with input filename without extension in actual directory
self.output = os.path.splitext(os.path.basename( self.input ))[0]
if not self.options.title:
self.options.title = os.path.basename( self.input )
if self.options.url and not self.options.url.endswith('/'):
self.options.url += '/'
if self.options.url:
self.options.url += os.path.basename( self.output ) + '/'
# Supported options
self.resampling = None
if self.options.resampling == 'average':
try:
if gdal.RegenerateOverview:
pass
except:
self.error("'average' resampling algorithm is not available.", "Please use -r 'near' argument or upgrade to newer version of GDAL.")
elif self.options.resampling == 'antialias':
try:
if numpy:
pass
except:
self.error("'antialias' resampling algorithm is not available.", "Install PIL (Python Imaging Library) and numpy.")
elif self.options.resampling == 'near':
self.resampling = gdal.GRA_NearestNeighbour
self.querysize = self.tilesize
elif self.options.resampling == 'bilinear':
self.resampling = gdal.GRA_Bilinear
self.querysize = self.tilesize * 2
elif self.options.resampling == 'cubic':
self.resampling = gdal.GRA_Cubic
elif self.options.resampling == 'cubicspline':
self.resampling = gdal.GRA_CubicSpline
elif self.options.resampling == 'lanczos':
self.resampling = gdal.GRA_Lanczos
# User specified zoom levels
self.tminz = None
self.tmaxz = None
if self.options.zoom:
minmax = self.options.zoom.split('-',1)
minmax.extend([''])
min, max = minmax[:2]
self.tminz = int(min)
if max:
self.tmaxz = int(max)
else:
self.tmaxz = int(min)
# KML generation
self.kml = self.options.kml
# Output the results
if self.options.verbose:
print("Options:", self.options)
print("Input:", self.input)
print("Output:", self.output)
print("Cache: %s MB" % (gdal.GetCacheMax() / 1024 / 1024))
print('')
# -------------------------------------------------------------------------
def optparse_init(self):
"""Prepare the option parser for input (argv)"""
from optparse import OptionParser, OptionGroup
usage = "Usage: %prog [options] input_file(s) [output]"
p = OptionParser(usage, version="%prog "+ __version__)
p.add_option("-p", "--profile", dest='profile', type='choice', choices=profile_list,
help="Tile cutting profile (%s) - default 'mercator' (Google Maps compatible)" % ",".join(profile_list))
p.add_option("-r", "--resampling", dest="resampling", type='choice', choices=resampling_list,
help="Resampling method (%s) - default 'average'" % ",".join(resampling_list))
p.add_option('-s', '--s_srs', dest="s_srs", metavar="SRS",
help="The spatial reference system used for the source input data")
p.add_option('-z', '--zoom', dest="zoom",
help="Zoom levels to render (format:'2-5' or '10').")
p.add_option('-e', '--resume', dest="resume", action="store_true",
help="Resume mode. Generate only missing files.")
p.add_option('-a', '--srcnodata', dest="srcnodata", metavar="NODATA",
help="NODATA transparency value to assign to the input data")
p.add_option('-d', '--tmscompatible', dest="tmscompatible", action="store_true",
help="When using the geodetic profile, specifies the base resolution as 0.703125 or 2 tiles at zoom level 0.")
p.add_option("-v", "--verbose",
action="store_true", dest="verbose",
help="Print status messages to stdout")
# KML options
g = OptionGroup(p, "KML (Google Earth) options", "Options for generated Google Earth SuperOverlay metadata")
g.add_option("-k", "--force-kml", dest='kml', action="store_true",
help="Generate KML for Google Earth - default for 'geodetic' profile and 'raster' in EPSG:4326. For a dataset with different projection use with caution!")
g.add_option("-n", "--no-kml", dest='kml', action="store_false",
help="Avoid automatic generation of KML files for EPSG:4326")
g.add_option("-u", "--url", dest='url',
help="URL address where the generated tiles are going to be published")
p.add_option_group(g)
# HTML options
g = OptionGroup(p, "Web viewer options", "Options for generated HTML viewers a la Google Maps")
g.add_option("-w", "--webviewer", dest='webviewer', type='choice', choices=webviewer_list,
help="Web viewer to generate (%s) - default 'all'" % ",".join(webviewer_list))
g.add_option("-t", "--title", dest='title',
help="Title of the map")
g.add_option("-c", "--copyright", dest='copyright',
help="Copyright for the map")
g.add_option("-g", "--googlekey", dest='googlekey',
help="Google Maps API key from http://code.google.com/apis/maps/signup.html")
g.add_option("-b", "--bingkey", dest='bingkey',
help="Bing Maps API key from https://www.bingmapsportal.com/"),
p.add_option_group(g)
# TODO: MapFile + TileIndexes per zoom level for efficient MapServer WMS
#g = OptionGroup(p, "WMS MapServer metadata", "Options for generated mapfile and tileindexes for MapServer")
#g.add_option("-i", "--tileindex", dest='wms', action="store_true"
# help="Generate tileindex and mapfile for MapServer (WMS)")
# p.add_option_group(g)
p.set_defaults(verbose=False, profile="mercator", kml=False, url='',
webviewer='all', copyright='', resampling='average', resume=False,
googlekey='INSERT_YOUR_KEY_HERE', bingkey='INSERT_YOUR_KEY_HERE')
self.parser = p
# -------------------------------------------------------------------------
def open_input(self):
"""Initialization of the input raster, reprojection if necessary"""
gdal.AllRegister()
# Initialize necessary GDAL drivers
self.out_drv = gdal.GetDriverByName( self.tiledriver )
self.mem_drv = gdal.GetDriverByName( 'MEM' )
if not self.out_drv:
raise Exception("The '%s' driver was not found, is it available in this GDAL build?", self.tiledriver)
if not self.mem_drv:
raise Exception("The 'MEM' driver was not found, is it available in this GDAL build?")
# Open the input file
if self.input:
self.in_ds = gdal.Open(self.input, gdal.GA_ReadOnly)
else:
raise Exception("No input file was specified")
if self.options.verbose:
print("Input file:", "( %sP x %sL - %s bands)" % (self.in_ds.RasterXSize, self.in_ds.RasterYSize, self.in_ds.RasterCount))
if not self.in_ds:
# Note: GDAL prints the ERROR message too
self.error("It is not possible to open the input file '%s'." % self.input )
# Read metadata from the input file
if self.in_ds.RasterCount == 0:
self.error( "Input file '%s' has no raster band" % self.input )
if self.in_ds.GetRasterBand(1).GetRasterColorTable():
# TODO: Process directly paletted dataset by generating VRT in memory
self.error( "Please convert this file to RGB/RGBA and run gdal2tiles on the result.",
"""From paletted file you can create RGBA file (temp.vrt) by:
gdal_translate -of vrt -expand rgba %s temp.vrt
then run:
gdal2tiles temp.vrt""" % self.input )
# Get NODATA value
self.in_nodata = []
for i in range(1, self.in_ds.RasterCount+1):
if self.in_ds.GetRasterBand(i).GetNoDataValue() != None:
self.in_nodata.append( self.in_ds.GetRasterBand(i).GetNoDataValue() )
if self.options.srcnodata:
nds = list(map( float, self.options.srcnodata.split(',')))
if len(nds) < self.in_ds.RasterCount:
self.in_nodata = (nds * self.in_ds.RasterCount)[:self.in_ds.RasterCount]
else:
self.in_nodata = nds
if self.options.verbose:
print("NODATA: %s" % self.in_nodata)
#
# Here we should have RGBA input dataset opened in self.in_ds
#
if self.options.verbose:
print("Preprocessed file:", "( %sP x %sL - %s bands)" % (self.in_ds.RasterXSize, self.in_ds.RasterYSize, self.in_ds.RasterCount))
# Spatial Reference System of the input raster
self.in_srs = None
if self.options.s_srs:
self.in_srs = osr.SpatialReference()
self.in_srs.SetFromUserInput(self.options.s_srs)
self.in_srs_wkt = self.in_srs.ExportToWkt()
else:
self.in_srs_wkt = self.in_ds.GetProjection()
if not self.in_srs_wkt and self.in_ds.GetGCPCount() != 0:
self.in_srs_wkt = self.in_ds.GetGCPProjection()
if self.in_srs_wkt:
self.in_srs = osr.SpatialReference()
self.in_srs.ImportFromWkt(self.in_srs_wkt)
#elif self.options.profile != 'raster':
# self.error("There is no spatial reference system info included in the input file.","You should run gdal2tiles with --s_srs EPSG:XXXX or similar.")
# Spatial Reference System of tiles
self.out_srs = osr.SpatialReference()
if self.options.profile == 'mercator':
self.out_srs.ImportFromEPSG(900913)
elif self.options.profile == 'geodetic':
self.out_srs.ImportFromEPSG(4326)
else:
self.out_srs = self.in_srs
# Are the reference systems the same? Reproject if necessary.
self.out_ds = None
if self.options.profile in ('mercator', 'geodetic'):
if (self.in_ds.GetGeoTransform() == (0.0, 1.0, 0.0, 0.0, 0.0, 1.0)) and (self.in_ds.GetGCPCount() == 0):
self.error("There is no georeference - neither affine transformation (worldfile) nor GCPs. You can generate only 'raster' profile tiles.",
"Either gdal2tiles with parameter -p 'raster' or use another GIS software for georeference e.g. gdal_transform -gcp / -a_ullr / -a_srs")
if self.in_srs:
if (self.in_srs.ExportToProj4() != self.out_srs.ExportToProj4()) or (self.in_ds.GetGCPCount() != 0):
# Generation of VRT dataset in tile projection, default 'nearest neighbour' warping
self.out_ds = gdal.AutoCreateWarpedVRT( self.in_ds, self.in_srs_wkt, self.out_srs.ExportToWkt() )
# TODO: HIGH PRIORITY: Correction of AutoCreateWarpedVRT according the max zoomlevel for correct direct warping!!!
if self.options.verbose:
print("Warping of the raster by AutoCreateWarpedVRT (result saved into 'tiles.vrt')")
self.out_ds.GetDriver().CreateCopy("tiles.vrt", self.out_ds)
# Note: self.in_srs and self.in_srs_wkt contain still the non-warped reference system!!!
# Correction of AutoCreateWarpedVRT for NODATA values
if self.in_nodata != []:
import tempfile
tempfilename = tempfile.mktemp('-gdal2tiles.vrt')
self.out_ds.GetDriver().CreateCopy(tempfilename, self.out_ds)
# open as a text file
s = open(tempfilename).read()
# Add the warping options
s = s.replace("""<GDALWarpOptions>""","""<GDALWarpOptions>
<Option name="INIT_DEST">NO_DATA</Option>
<Option name="UNIFIED_SRC_NODATA">YES</Option>""")
# replace BandMapping tag for NODATA bands....
for i in range(len(self.in_nodata)):
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), self.in_nodata[i], self.in_nodata[i])) # Or rewrite to white by: , 255 ))
# save the corrected VRT
open(tempfilename,"w").write(s)
# open by GDAL as self.out_ds
self.out_ds = gdal.Open(tempfilename) #, gdal.GA_ReadOnly)
# delete the temporary file
os.unlink(tempfilename)
# set NODATA_VALUE metadata
self.out_ds.SetMetadataItem('NODATA_VALUES','%i %i %i' % (self.in_nodata[0],self.in_nodata[1],self.in_nodata[2]))
if self.options.verbose:
print("Modified warping result saved into 'tiles1.vrt'")
open("tiles1.vrt","w").write(s)
# -----------------------------------
# Correction of AutoCreateWarpedVRT for Mono (1 band) and RGB (3 bands) files without NODATA:
# equivalent of gdalwarp -dstalpha
if self.in_nodata == [] and self.out_ds.RasterCount in [1,3]:
import tempfile
tempfilename = tempfile.mktemp('-gdal2tiles.vrt')
self.out_ds.GetDriver().CreateCopy(tempfilename, self.out_ds)
# open as a text file
s = open(tempfilename).read()
# Add the warping options
s = s.replace("""<BlockXSize>""","""<VRTRasterBand dataType="Byte" band="%i" subClass="VRTWarpedRasterBand">
<ColorInterp>Alpha</ColorInterp>
</VRTRasterBand>
<BlockXSize>""" % (self.out_ds.RasterCount + 1))
s = s.replace("""</GDALWarpOptions>""", """<DstAlphaBand>%i</DstAlphaBand>
</GDALWarpOptions>""" % (self.out_ds.RasterCount + 1))
s = s.replace("""</WorkingDataType>""", """</WorkingDataType>
<Option name="INIT_DEST">0</Option>""")
# save the corrected VRT
open(tempfilename,"w").write(s)
# open by GDAL as self.out_ds
self.out_ds = gdal.Open(tempfilename) #, gdal.GA_ReadOnly)
# delete the temporary file
os.unlink(tempfilename)
if self.options.verbose:
print("Modified -dstalpha warping result saved into 'tiles1.vrt'")
open("tiles1.vrt","w").write(s)
s = '''
'''
else:
self.error("Input file has unknown SRS.", "Use --s_srs ESPG:xyz (or similar) to provide source reference system." )
if self.out_ds and self.options.verbose:
print("Projected file:", "tiles.vrt", "( %sP x %sL - %s bands)" % (self.out_ds.RasterXSize, self.out_ds.RasterYSize, self.out_ds.RasterCount))
if not self.out_ds:
self.out_ds = self.in_ds
#
# Here we should have a raster (out_ds) in the correct Spatial Reference system
#
# Get alpha band (either directly or from NODATA value)
self.alphaband = self.out_ds.GetRasterBand(1).GetMaskBand()
if (self.alphaband.GetMaskFlags() & gdal.GMF_ALPHA) or self.out_ds.RasterCount==4 or self.out_ds.RasterCount==2:
# TODO: Better test for alpha band in the dataset
self.dataBandsCount = self.out_ds.RasterCount - 1
else:
self.dataBandsCount = self.out_ds.RasterCount
# KML test
self.isepsg4326 = False
srs4326 = osr.SpatialReference()
srs4326.ImportFromEPSG(4326)
if self.out_srs and srs4326.ExportToProj4() == self.out_srs.ExportToProj4():
self.kml = True
self.isepsg4326 = True
if self.options.verbose:
print("KML autotest OK!")
# Read the georeference
self.out_gt = self.out_ds.GetGeoTransform()
#originX, originY = self.out_gt[0], self.out_gt[3]
#pixelSize = self.out_gt[1] # = self.out_gt[5]
# Test the size of the pixel
# MAPTILER - COMMENTED
#if self.out_gt[1] != (-1 * self.out_gt[5]) and self.options.profile != 'raster':
# TODO: Process corectly coordinates with are have swichted Y axis (display in OpenLayers too)
#self.error("Size of the pixel in the output differ for X and Y axes.")
# Report error in case rotation/skew is in geotransform (possible only in 'raster' profile)
if (self.out_gt[2], self.out_gt[4]) != (0,0):
self.error("Georeference of the raster contains rotation or skew. Such raster is not supported. Please use gdalwarp first.")
# TODO: Do the warping in this case automaticaly
#
# Here we expect: pixel is square, no rotation on the raster
#
# Output Bounds - coordinates in the output SRS
self.ominx = self.out_gt[0]
self.omaxx = self.out_gt[0]+self.out_ds.RasterXSize*self.out_gt[1]
self.omaxy = self.out_gt[3]
self.ominy = self.out_gt[3]-self.out_ds.RasterYSize*self.out_gt[1]
# Note: maybe round(x, 14) to avoid the gdal_translate behaviour, when 0 becomes -1e-15
if self.options.verbose:
print("Bounds (output srs):", round(self.ominx, 13), self.ominy, self.omaxx, self.omaxy)
#
# Calculating ranges for tiles in different zoom levels
#
if self.options.profile == 'mercator':
self.mercator = GlobalMercator() # from globalmaptiles.py
# Function which generates SWNE in LatLong for given tile
self.tileswne = self.mercator.TileLatLonBounds
# Generate table with min max tile coordinates for all zoomlevels
self.tminmax = list(range(0,32))
for tz in range(0, 32):
tminx, tminy = self.mercator.MetersToTile( self.ominx, self.ominy, tz )
tmaxx, tmaxy = self.mercator.MetersToTile( self.omaxx, self.omaxy, tz )
# crop tiles extending world limits (+-180,+-90)
tminx, tminy = max(0, tminx), max(0, tminy)
tmaxx, tmaxy = min(2**tz-1, tmaxx), min(2**tz-1, tmaxy)
self.tminmax[tz] = (tminx, tminy, tmaxx, tmaxy)
# TODO: Maps crossing 180E (Alaska?)
# Get the minimal zoom level (map covers area equivalent to one tile)
if self.tminz == None:
self.tminz = self.mercator.ZoomForPixelSize( self.out_gt[1] * max( self.out_ds.RasterXSize, self.out_ds.RasterYSize) / float(self.tilesize) )
# Get the maximal zoom level (closest possible zoom level up on the resolution of raster)
if self.tmaxz == None:
self.tmaxz = self.mercator.ZoomForPixelSize( self.out_gt[1] )
if self.options.verbose:
print("Bounds (latlong):", self.mercator.MetersToLatLon( self.ominx, self.ominy), self.mercator.MetersToLatLon( self.omaxx, self.omaxy))
print('MinZoomLevel:', self.tminz)
print("MaxZoomLevel:", self.tmaxz, "(", self.mercator.Resolution( self.tmaxz ),")")
if self.options.profile == 'geodetic':
self.geodetic = GlobalGeodetic(self.options.tmscompatible) # from globalmaptiles.py
# Function which generates SWNE in LatLong for given tile
self.tileswne = self.geodetic.TileLatLonBounds
# Generate table with min max tile coordinates for all zoomlevels