def test_cog_translate_web_align():
"""
Test Web-Optimized COG.
- Test COG bounds (thus block) is aligned with Zoom levels
"""
tms = morecantile.tms.get("WebMercatorQuad")
runner = CliRunner()
with runner.isolated_filesystem():
web_profile = cog_profiles.get("raw")
web_profile.update({"blockxsize": 256, "blockysize": 256})
config = dict(GDAL_TIFF_OVR_BLOCKSIZE="256")
with rasterio.open(raster_path_web) as src_dst:
_, max_zoom = get_zooms(src_dst)
cog_translate(
raster_path_web,
"cogeo.tif",
web_profile,
quiet=True,
web_optimized=True,
config=config,
aligned_levels=2,
)
with COGReader(raster_path_web) as src_dst:
bounds = src_dst.bounds
with COGReader("cogeo.tif") as cog:
_, max_zoom = get_zooms(cog.dataset)
ulTile = tms.xy_bounds(tms.tile(bounds[0], bounds[3], max_zoom - 2))
assert round(cog.dataset.bounds[0], 5) == round(ulTile.left, 5)
assert round(cog.dataset.bounds[3], 5) == round(ulTile.top, 5)
lrTile = tms.xy_bounds(tms.tile(bounds[2], bounds[1], max_zoom - 2))
assert round(cog.dataset.bounds[2], 5) == round(lrTile.right, 5)
assert round(cog.dataset.bounds[1], 5) == round(lrTile.bottom, 5)
cog_translate(
raster_path_web,
"cogeo.tif",
web_profile,
quiet=True,
web_optimized=True,
config=config,
aligned_levels=3,
)
with COGReader(raster_path_web) as src_dst:
bounds = src_dst.bounds
with COGReader("cogeo.tif") as cog_dst:
_, max_zoom = get_zooms(cog_dst.dataset)
ulTile = tms.xy_bounds(tms.tile(bounds[0], bounds[3], max_zoom - 3))
assert round(cog_dst.dataset.bounds[0], 5) == round(ulTile.left, 5)
assert round(cog_dst.dataset.bounds[3], 5) == round(ulTile.top, 5)
lrTile = tms.xy_bounds(tms.tile(bounds[2], bounds[1], max_zoom - 3))
assert round(cog_dst.dataset.bounds[2], 5) == round(lrTile.right, 5)
assert round(cog_dst.dataset.bounds[1], 5) == round(lrTile.bottom, 5)
def test_cog_translate_webZooms():
"""
Test Web-Optimized COG.
- Test COG size is a multiple of 256 (mercator tile size)
- Test COG bounds are aligned with mercator grid at max zoom
- Test high resolution internal tiles are equal to mercator tile using
cogdumper and rio-tiler
- Test overview internal tiles are equal to mercator tile using
cogdumper and rio-tiler
"""
runner = CliRunner()
with runner.isolated_filesystem():
web_profile = cog_profiles.get("raw")
web_profile.update({"blockxsize": 256, "blockysize": 256})
config = dict(GDAL_TIFF_OVR_BLOCKSIZE="128")
cog_translate(
raster_path_north,
"cogeo.tif",
web_profile,
quiet=True,
web_optimized=True,
config=config,
)
with rasterio.open("cogeo.tif") as out_dst:
_, maxzoom = get_zooms(out_dst)
assert maxzoom == 8
cog_translate(
raster_path_north,
"cogeo.tif",
web_profile,
quiet=True,
web_optimized=True,
latitude_adjustment=False,
config=config,
)
with rasterio.open("cogeo.tif") as out_dst:
_, maxzoom = get_zooms(out_dst)
assert maxzoom == 10
def test_cog_translate_web():
"""
Test Web-Optimized COG.
- Test COG size is a multiple of 256 (mercator tile size)
- Test COG bounds are aligned with mercator grid at max zoom
"""
tms = morecantile.tms.get("WebMercatorQuad")
runner = CliRunner()
with runner.isolated_filesystem():
web_profile = cog_profiles.get("raw")
web_profile.update({"blockxsize": 256, "blockysize": 256})
config = dict(GDAL_TIFF_OVR_BLOCKSIZE="256")
cog_translate(
raster_path_web,
"cogeo.tif",
web_profile,
quiet=True,
web_optimized=True,
config=config,
aligned_levels=0,
)
with rasterio.open(raster_path_web) as src_dst:
with rasterio.open("cogeo.tif") as out_dst:
blocks = list(set(out_dst.block_shapes))
assert len(blocks) == 1
ts = blocks[0][0]
assert not out_dst.width % ts
assert not out_dst.height % ts
_, max_zoom = get_zooms(out_dst)
bounds = list(
transform_bounds(src_dst.crs,
"epsg:4326",
*src_dst.bounds,
densify_pts=21))
ulTile = tms.xy_bounds(tms.tile(bounds[0], bounds[3],
max_zoom))
assert out_dst.bounds.left == ulTile.left
assert out_dst.bounds.top == ulTile.top
lrTile = tms.xy_bounds(tms.tile(bounds[2], bounds[1],
max_zoom))
assert out_dst.bounds.right == lrTile.right
assert round(out_dst.bounds.bottom,
6) == round(lrTile.bottom, 6)
def test_cogeo_zoom_level(runner):
"""Should work as expected."""
with runner.isolated_filesystem():
result = runner.invoke(
cogeo,
[
"create",
raster_path_rgb,
"output.tif",
"--web-optimized",
"--zoom-level",
"18",
],
)
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
_, max_zoom = get_zooms(src)
assert max_zoom == 18
result = runner.invoke(
cogeo,
[
"create",
raster_path_rgb,
"output.tif",
"--web-optimized",
"--zoom-level",
"19",
],
)
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
_, max_zoom = get_zooms(src)
assert max_zoom == 19
def cog_info(src_path: Union[str, pathlib.PurePath], **kwargs: Any) -> Dict:
"""Get general info and validate Cloud Optimized Geotiff."""
is_valid, validation_errors, validation_warnings = cog_validate(
src_path,
quiet=True,
**kwargs,
)
with rasterio.open(src_path) as src_dst:
_info = {
"Path":
str(src_path),
"Driver":
src_dst.driver,
"COG":
is_valid,
"Compression":
src_dst.compression.value if src_dst.compression else None,
"ColorSpace":
src_dst.photometric.value if src_dst.photometric else None,
}
if validation_errors:
_info["COG_errors"] = validation_errors
if validation_warnings:
_info["COG_warnings"] = validation_warnings
try:
colormap = src_dst.colormap(1)
except ValueError:
colormap = None
profile = {
"Bands": src_dst.count,
"Width": src_dst.width,
"Height": src_dst.height,
"Tiled": src_dst.is_tiled,
"Dtype": src_dst.dtypes[0],
"Interleave": src_dst.interleaving.value,
"Alpha Band": utils.has_alpha_band(src_dst),
"Internal Mask": utils.has_mask_band(src_dst),
"Nodata": src_dst.nodata,
"ColorInterp":
tuple([color.name for color in src_dst.colorinterp]),
"ColorMap": colormap is not None,
"Scales": src_dst.scales,
"Offsets": src_dst.offsets,
}
try:
crs = (f"EPSG:{src_dst.crs.to_epsg()}"
if src_dst.crs.to_epsg() else src_dst.crs.to_wkt())
except AttributeError:
crs = None
minzoom: Optional[int] = None
maxzoom: Optional[int] = None
try:
minzoom, maxzoom = utils.get_zooms(src_dst)
except Exception:
pass
geo = {
"CRS": crs,
"BoundingBox": tuple(src_dst.bounds),
"Origin": (src_dst.transform.c, src_dst.transform.f),
"Resolution": (src_dst.transform.a, src_dst.transform.e),
"MinZoom": minzoom,
"MaxZoom": maxzoom,
}
ifd_raw = [{
"Level": 0,
"Width": src_dst.width,
"Height": src_dst.height,
"Blocksize": src_dst.block_shapes[0],
"Decimation": 0,
}]
overviews = src_dst.overviews(1)
tags = src_dst.tags()
ifd_ovr = []
for ix, decim in enumerate(overviews):
with rasterio.open(src_path, OVERVIEW_LEVEL=ix) as ovr_dst:
ifd_ovr.append({
"Level": ix + 1,
"Width": ovr_dst.width,
"Height": ovr_dst.height,
"Blocksize": ovr_dst.block_shapes[0],
"Decimation": decim,
})
ifds = ifd_raw + ifd_ovr
output = _info.copy()
output["Profile"] = profile
output["GEO"] = geo
output["Tags"] = tags
output["IFD"] = ifds
return output
def test_cog_translate_Internal():
"""
Test Web-Optimized COG.
- Test COG size is a multiple of 256 (mercator tile size)
- Test COG bounds are aligned with mercator grid at max zoom
- Test high resolution internal tiles are equal to mercator tile using
cogdumper and rio-tiler
- Test overview internal tiles are equal to mercator tile using
cogdumper and rio-tiler
"""
tms = morecantile.tms.get("WebMercatorQuad")
runner = CliRunner()
with runner.isolated_filesystem():
web_profile = cog_profiles.get("raw")
web_profile.update({"blockxsize": 256, "blockysize": 256})
config = dict(GDAL_TIFF_OVR_BLOCKSIZE="256")
cog_translate(
raster_path_web,
"cogeo.tif",
web_profile,
quiet=True,
web_optimized=True,
config=config,
aligned_levels=0,
)
with rasterio.open(raster_path_web) as src_dst:
with rasterio.open("cogeo.tif") as out_dst:
blocks = list(set(out_dst.block_shapes))
assert len(blocks) == 1
ts = blocks[0][0]
assert not out_dst.width % ts
assert not out_dst.height % ts
_, max_zoom = get_zooms(out_dst)
bounds = list(
transform_bounds(src_dst.crs,
"epsg:4326",
*src_dst.bounds,
densify_pts=21))
minimumTile = tms.tile(bounds[0], bounds[3], max_zoom)
maximumTile = tms.tile(bounds[2], bounds[1], max_zoom)
with open("cogeo.tif", "rb") as out_body:
reader = FileReader(out_body)
cog = COGTiff(reader.read)
# High resolution
# Top Left tile
_, tile = cog.get_tile(0, 0, 0)
tile_length = 256 * 256 * 3
t = struct.unpack_from("{}b".format(tile_length), tile)
arr = numpy.array(t).reshape(256, 256,
3).astype(numpy.uint8)
arr = numpy.transpose(arr, [2, 0, 1])
with rasterio.open("cogeo.tif") as src_dst:
w = from_bounds(*tms.xy_bounds(minimumTile),
src_dst.transform)
data = src_dst.read(window=w,
out_shape=(src_dst.count, 256,
256))
numpy.testing.assert_array_equal(data, arr)
# Bottom right tile
_, tile = cog.get_tile(4, 3, 0)
tile_length = 256 * 256 * 3
t = struct.unpack_from("{}b".format(tile_length), tile)
arr = numpy.array(t).reshape(256, 256,
3).astype(numpy.uint8)
arr = numpy.transpose(arr, [2, 0, 1])
with rasterio.open("cogeo.tif") as src_dst:
w = from_bounds(*tms.xy_bounds(maximumTile),
src_dst.transform)
data = src_dst.read(window=w,
out_shape=(src_dst.count, 256,
256))
numpy.testing.assert_array_equal(data, arr)
def test_cog_translate_Internal():
"""
Test Web-Optimized COG.
- Test COG size is a multiple of 256 (mercator tile size)
- Test COG bounds are aligned with mercator grid at max zoom
- Test high resolution internal tiles are equal to mercator tile using
cogdumper and rio-tiler
- Test overview internal tiles are equal to mercator tile using
cogdumper and rio-tiler
"""
from cogdumper.cog_tiles import COGTiff
from cogdumper.filedumper import Reader as FileReader
runner = CliRunner()
with runner.isolated_filesystem():
web_profile = cog_profiles.get("raw")
web_profile.update({"blockxsize": 256, "blockysize": 256})
config = dict(GDAL_TIFF_OVR_BLOCKSIZE="128")
cog_translate(
raster_path_web,
"cogeo.tif",
web_profile,
quiet=True,
web_optimized=True,
config=config,
)
with rasterio.open(raster_path_web) as src_dst:
with rasterio.open("cogeo.tif") as out_dst:
blocks = list(set(out_dst.block_shapes))
assert len(blocks) == 1
ts = blocks[0][0]
assert not out_dst.width % ts
assert not out_dst.height % ts
_, max_zoom = get_zooms(out_dst)
bounds = list(
transform_bounds(src_dst.crs,
"epsg:4326",
*src_dst.bounds,
densify_pts=21))
minimumTile = mercantile.tile(bounds[0], bounds[3], max_zoom)
maximumTile = mercantile.tile(bounds[2], bounds[1], max_zoom)
with open("cogeo.tif", "rb") as out_body:
reader = FileReader(out_body)
cog = COGTiff(reader.read)
# High resolution
# Top Left tile
_, tile = cog.get_tile(0, 0, 0)
tile_length = 256 * 256 * 3
t = struct.unpack_from("{}b".format(tile_length), tile)
arr = numpy.array(t).reshape(256, 256,
3).astype(numpy.uint8)
arr = numpy.transpose(arr, [2, 0, 1])
with rasterio.open("cogeo.tif") as src_dst:
data, _ = COGreader.tile(src_dst,
*minimumTile,
resampling_method="nearest")
numpy.testing.assert_array_equal(data, arr)
# Bottom right tile
_, tile = cog.get_tile(4, 3, 0)
tile_length = 256 * 256 * 3
t = struct.unpack_from("{}b".format(tile_length), tile)
arr = numpy.array(t).reshape(256, 256,
3).astype(numpy.uint8)
arr = numpy.transpose(arr, [2, 0, 1])
with rasterio.open("cogeo.tif") as src_dst:
data, _ = COGreader.tile(src_dst,
*maximumTile,
resampling_method="nearest")
numpy.testing.assert_array_equal(data, arr)
# Low resolution (overview 1)
# Top Left tile
# NOTE: overview internal tile size is 128px
# We need to stack two internal tiles to compare with
# the 256px mercator tile fetched by rio-tiler
# ref: https://github.com/cogeotiff/rio-cogeo/issues/60
_, tile = cog.get_tile(1, 0, 1)
tile_length = 128 * 128 * 3
t = struct.unpack_from("{}b".format(tile_length), tile)
arr1 = numpy.array(t).reshape(128, 128,
3).astype(numpy.uint8)
arr1 = numpy.transpose(arr1, [2, 0, 1])
_, tile = cog.get_tile(2, 0, 1)
tile_length = 128 * 128 * 3
t = struct.unpack_from("{}b".format(tile_length), tile)
arr2 = numpy.array(t).reshape(128, 128,
3).astype(numpy.uint8)
arr2 = numpy.transpose(arr2, [2, 0, 1])
arr = numpy.dstack((arr1, arr2))
with rasterio.open("cogeo.tif") as src_dst:
data, _ = COGreader.tile(src_dst,
118594,
60034,
17,
resampling_method="nearest")
data = data[:, 128:, :]
numpy.testing.assert_array_equal(data, arr)
def cog_info(src_path: Union[str, pathlib.PurePath],
**kwargs: Any) -> models.Info:
"""Get general info and validate Cloud Optimized Geotiff."""
is_valid, validation_errors, validation_warnings = cog_validate(
src_path,
quiet=True,
**kwargs,
)
with rasterio.open(src_path) as src_dst:
driver = src_dst.driver
compression = src_dst.compression.value if src_dst.compression else None
colorspace = src_dst.photometric.value if src_dst.photometric else None
overviews = src_dst.overviews(1)
tags = {"Image Metadata": src_dst.tags()}
namespaces = src_dst.tag_namespaces()
for ns in namespaces:
if ns in ["DERIVED_SUBDATASETS"]:
continue
tags.update({str.title(ns).replace("_", " "): src_dst.tags(ns=ns)})
band_metadata = {
f"Band {ix}": models.BandMetadata(
**{
"Description": src_dst.descriptions[ix - 1],
"ColorInterp": src_dst.colorinterp[ix - 1].name,
"Offset": src_dst.offsets[ix - 1],
"Scale": src_dst.scales[ix - 1],
"Metadata": src_dst.tags(ix),
})
for ix in src_dst.indexes
}
try:
colormap = src_dst.colormap(1)
except ValueError:
colormap = None
profile = models.Profile(
Bands=src_dst.count,
Width=src_dst.width,
Height=src_dst.height,
Tiled=src_dst.is_tiled,
Dtype=src_dst.dtypes[0],
Interleave=src_dst.interleaving.value,
AlphaBand=utils.has_alpha_band(src_dst),
InternalMask=utils.has_mask_band(src_dst),
Nodata=src_dst.nodata,
ColorInterp=tuple([color.name for color in src_dst.colorinterp]),
ColorMap=colormap is not None,
Scales=src_dst.scales,
Offsets=src_dst.offsets,
)
try:
crs = (f"EPSG:{src_dst.crs.to_epsg()}"
if src_dst.crs.to_epsg() else src_dst.crs.to_wkt())
except AttributeError:
crs = None
minzoom: Optional[int] = None
maxzoom: Optional[int] = None
try:
minzoom, maxzoom = utils.get_zooms(src_dst)
except Exception:
pass
geo = models.Geo(
CRS=crs,
BoundingBox=tuple(src_dst.bounds),
Origin=(src_dst.transform.c, src_dst.transform.f),
Resolution=(src_dst.transform.a, src_dst.transform.e),
MinZoom=minzoom,
MaxZoom=maxzoom,
)
ifds = [
models.IFD(
Level=0,
Width=src_dst.width,
Height=src_dst.height,
Blocksize=src_dst.block_shapes[0],
Decimation=0,
)
]
for ix, decim in enumerate(overviews):
with rasterio.open(src_path, OVERVIEW_LEVEL=ix) as ovr_dst:
ifds.append(
models.IFD(
Level=ix + 1,
Width=ovr_dst.width,
Height=ovr_dst.height,
Blocksize=ovr_dst.block_shapes[0],
Decimation=decim,
))
return models.Info(
Path=str(src_path),
Driver=driver,
COG=is_valid,
Compression=compression,
ColorSpace=colorspace,
COG_errors=validation_errors or None,
COG_warnings=validation_warnings or None,
Profile=profile,
GEO=geo,
Tags=tags,
Band_Metadata=band_metadata,
IFD=ifds,
)
