def __init__(self):
pi = _pi
# Transform from raw mercator projection to tile coordinates
t = deriveTransformation(-pi, pi, 0, 0, pi, pi, 1, 0, -pi, -pi, 0, 1)
MercatorProjection.__init__(self, 0, t)
def __init__(self):
p = _pi
# Transform from geography in radians to tile coordinates
t = deriveTransformation(-p, p/2, 0, 0, p, p/2, 2, 0, -p, -p/2, 0, 1)
LinearProjection.__init__(self, 0, t)
def __init__(self):
p = _pi
# Transform from geography in radians to tile coordinates
t = deriveTransformation(-p, p/2, 0, 0, p, p/2, 2, 0, -p, -p/2, 0, 1)
LinearProjection.__init__(self, 0, t)
def __init__(self):
pi = _pi
# Transform from raw mercator projection to tile coordinates
t = deriveTransformation(-pi, pi, 0, 0, pi, pi, 1, 0, -pi, -pi, 0, 1)
MercatorProjection.__init__(self, 0, t)
def __init__(self):
t = deriveTransformation(-pi, pi, 0, 0, pi, pi, 1, 0, -pi, -pi, 0, 1)
self.projection = MercatorProjection(0, t)
def get_projection():
''' Return the correct spherical mercator project for Nokia.
'''
# the spherical mercator world tile covers (-π, -π) to (π, π)
t = deriveTransformation(-pi, pi, 0, 0, pi, pi, 1, 0, -pi, -pi, 0, 1)
return MercatorProjection(0, t)
def generate_map_tiles(mysql, bucket, map_id):
'''
'''
mysql.execute('''SELECT * FROM maps WHERE id = %s''', (map_id, ))
map = mysql.fetchdict()
#
# Retrieve the original uploaded image from storage.
#
img = bucket.get_key(map['image'])
if not img:
# started using unqoute_plus to name the keys, to handle double encoding of file names on S3
img = bucket.get_key(unquote_plus(map['image']))
# ok give up
if not img:
logging.error("No image found for map: %s"%(map['id']))
return
tmpdir = mkdtemp(prefix='gen-map-tiles-')
imgname = join(tmpdir, basename(img.name))
img.get_contents_to_filename(imgname)
img = Image.open(imgname)
w, h = img.size
#
# Calculate a geo transformation based on three corner points.
#
size, theta, (ul, ur, lr, ll) \
= build_rough_placement_polygon(map['aspect'], map['ul_lat'], map['ul_lon'], map['lr_lat'], map['lr_lon'])
logging.info(preview_url(ul, ur, lr, ll))
ul = terra.transform(Point(*ul))
ur = terra.transform(Point(*ur))
ll = terra.transform(Point(*ll))
lr = terra.transform(Point(*lr))
args = (0, 0, ul.x, ul.y, 0, h, ll.x, ll.y, w, h, lr.x, lr.y)
xform = deriveTransformation(*args)
#
# Build a VRT file in spherical mercator projection.
#
vrtname = join(tmpdir, 'image.vrt')
vrt = build_vrt(basename(imgname), img.size[0], img.size[1], xform)
vrt.write(open(vrtname, 'w'))
key = bucket.new_key(join(dirname(map['image']), 'image.vrt'))
key.set_contents_from_filename(vrtname, {'Content-Type': 'application/gdal-vrt+xml'}, policy='public-read')
#
# Generate image tiles and upload them.
#
queue = JoinableQueue()
tiles = join(dirname(map['image']), 'tiles')
uploader1 = Process(target=upload_map_tiles, args=(queue, bucket, tiles))
uploader2 = Process(target=upload_map_tiles, args=(queue, bucket, tiles))
uploader1.start()
uploader2.start()
max_zoom = round(1 + native_zoom(w, h, ul, lr))
logging.info("max_zoom from native_zoom: %s"%(max_zoom))
# cap zoom at 18
max_zoom = min(max_zoom,18.0)
cut_map_tiles(vrtname, queue, ul, ur, lr, ll, max_zoom)
uploader1.join()
uploader2.join()
#
# Clean up.
#
rmtree(tmpdir)
logging.info('Set %s on %s' % (repr(dict(tiles=basename(tiles))), map['id']))
mysql.execute('UPDATE maps SET tiles = %s WHERE id = %s', (tiles, map['id']))
def get_projection():
''' Return the correct spherical mercator project for Nokia.
'''
# the spherical mercator world tile covers (-π, -π) to (π, π)
t = deriveTransformation(-pi, pi, 0, 0, pi, pi, 1, 0, -pi, -pi, 0, 1)
return MercatorProjection(0, t)
def __init__(self):
t = deriveTransformation(-pi, pi, 0, 0, pi, pi, 1, 0, -pi, -pi, 0, 1)
self.projection = MercatorProjection(0, t)
def __init__(self):
# the spherical mercator world tile covers (-π, -π) to (π, π)
t = deriveTransformation(-pi, pi, 0, 0, pi, pi, 1, 0, -pi, -pi, 0, 1)
self.projection = MercatorProjection(0, t)
def generate_map_tiles(mysql, bucket, map_id):
'''
'''
mysql.execute('''SELECT * FROM maps WHERE id = %s''', (map_id, ))
map = mysql.fetchdict()
#
# Retrieve the original uploaded image from storage.
#
img = bucket.get_key(map['image'])
if not img:
# started using unqoute_plus to name the keys, to handle double encoding of file names on S3
img = bucket.get_key(unquote_plus(map['image']))
# ok give up
if not img:
logging.error("No image found for map: %s" % (map['id']))
return
tmpdir = mkdtemp(prefix='gen-map-tiles-')
imgname = join(tmpdir, basename(img.name))
img.get_contents_to_filename(imgname)
img = Image.open(imgname)
w, h = img.size
#
# Calculate a geo transformation based on three corner points.
#
size, theta, (ul, ur, lr, ll) \
= build_rough_placement_polygon(map['aspect'], map['ul_lat'], map['ul_lon'], map['lr_lat'], map['lr_lon'])
logging.info(preview_url(ul, ur, lr, ll))
ul = terra.transform(Point(*ul))
ur = terra.transform(Point(*ur))
ll = terra.transform(Point(*ll))
lr = terra.transform(Point(*lr))
args = (0, 0, ul.x, ul.y, 0, h, ll.x, ll.y, w, h, lr.x, lr.y)
xform = deriveTransformation(*args)
#
# Build a VRT file in spherical mercator projection.
#
vrtname = join(tmpdir, 'image.vrt')
vrt = build_vrt(basename(imgname), img.size[0], img.size[1], xform)
vrt.write(open(vrtname, 'w'))
key = bucket.new_key(join(dirname(map['image']), 'image.vrt'))
key.set_contents_from_filename(
vrtname, {'Content-Type': 'application/gdal-vrt+xml'},
policy='public-read')
#
# Generate image tiles and upload them.
#
queue = JoinableQueue()
tiles = join(dirname(map['image']), 'tiles')
uploader1 = Process(target=upload_map_tiles, args=(queue, bucket, tiles))
uploader2 = Process(target=upload_map_tiles, args=(queue, bucket, tiles))
uploader1.start()
uploader2.start()
max_zoom = round(1 + native_zoom(w, h, ul, lr))
logging.info("max_zoom from native_zoom: %s" % (max_zoom))
# cap zoom at 18
max_zoom = min(max_zoom, 18.0)
cut_map_tiles(vrtname, queue, ul, ur, lr, ll, max_zoom)
uploader1.join()
uploader2.join()
#
# Clean up.
#
rmtree(tmpdir)
logging.info('Set %s on %s' %
(repr(dict(tiles=basename(tiles))), map['id']))
mysql.execute('UPDATE maps SET tiles = %s WHERE id = %s',
(tiles, map['id']))
