def test_cog_translate_valid():
"""Should work as expected (create cogeo file)."""
runner = CliRunner()
with runner.isolated_filesystem():
cog_translate(raster_path_rgb, "cogeo.tif", jpeg_profile, quiet=True)
with rasterio.open("cogeo.tif") as src:
assert src.height == 512
assert src.width == 512
assert src.meta["dtype"] == "uint8"
assert src.is_tiled
assert src.profile["blockxsize"] == 64
assert src.profile["blockysize"] == 64
assert src.compression.value == "JPEG"
assert src.photometric.value == "YCbCr"
assert src.interleaving.value == "PIXEL"
assert src.overviews(1) == [2, 4, 8]
assert src.tags()["OVR_RESAMPLING_ALG"] == "NEAREST"
assert not has_mask_band(src)
cog_translate(raster_path_rgb,
"cogeo.tif",
jpeg_profile,
add_mask=True,
quiet=True)
with rasterio.open("cogeo.tif") as src:
assert has_mask_band(src)
def test_cog_translate_NodataMask():
"""Should work as expected (create cogeo and translate nodata to mask)."""
runner = CliRunner()
with runner.isolated_filesystem():
cog_translate(
raster_path_missingnodata,
"cogeo.tif",
deflate_profile,
nodata=-9999,
add_mask=True,
quiet=True,
)
with rasterio.open("cogeo.tif") as src:
assert src.nodata is None
assert has_mask_band(src)
assert not src.dataset_mask().all()
cog_translate(raster_path_nodata,
"cogeo.tif",
deflate_profile,
add_mask=True,
quiet=True)
with rasterio.open("cogeo.tif") as src:
assert src.nodata is None
assert has_mask_band(src)
assert not src.dataset_mask().all()
def test_cogeo_validnodata():
"""Should work as expected."""
runner = CliRunner()
with runner.isolated_filesystem():
with pytest.warns(LossyCompression):
result = runner.invoke(
cogeo, [raster_path_rgb, "output.tif", "--nodata", "0"])
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
assert src.nodata == 0
assert not has_mask_band(src)
result = runner.invoke(
cogeo,
[
raster_path_nodata,
"output.tif",
"--co",
"BLOCKXSIZE=64",
"--co",
"BLOCKYSIZE=64",
"--cog-profile",
"deflate",
],
)
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
assert src.nodata == -9999
assert not has_mask_band(src)
def test_cog_translate_mask():
"""Should work as expected (copy mask from input)."""
runner = CliRunner()
with runner.isolated_filesystem():
cog_translate(raster_path_mask, "cogeo.tif", jpeg_profile, quiet=True)
with rasterio.open("cogeo.tif") as src:
assert has_mask_band(src)
def test_cog_translate_validAlpha(runner):
"""Should work as expected (create cogeo file with alpha band)."""
with runner.isolated_filesystem():
cog_translate(raster_path_rgba, "cogeo.tif", webp_profile, quiet=True)
with rasterio.open("cogeo.tif") as src:
assert src.height == 512
assert src.width == 512
assert src.meta["dtype"] == "uint8"
assert src.is_tiled
assert src.compression.value == "WEBP"
assert has_alpha_band(src)
with rasterio.open(raster_path_rgba) as src:
with rasterio.open("cogeo.tif") as dst:
assert src.colorinterp == dst.colorinterp
with pytest.warns(UserWarning):
cog_translate(raster_path_rgba, "cogeo.tif", jpeg_profile, quiet=True)
with rasterio.open("cogeo.tif") as src:
assert src.count == 3
with pytest.warns(UserWarning):
cog_translate(
raster_path_rgba,
"cogeo.tif",
jpeg_profile,
indexes=(1, 2, 3, 4),
quiet=True,
)
with rasterio.open("cogeo.tif") as src:
assert src.count == 3
assert src.compression.value == "JPEG"
assert has_mask_band(src)
with pytest.warns(UserWarning):
cog_translate(
raster_path_rgba, "cogeo.tif", jpeg_profile, indexes=(1,), quiet=True
)
with rasterio.open("cogeo.tif") as src:
assert src.count == 1
assert src.compression.value == "JPEG"
assert has_mask_band(src)
def test_cog_translate_NodataLossyWarning(runner):
"""Should work as expected (create cogeo file but warns no lossy compression)."""
with runner.isolated_filesystem():
with pytest.warns(LossyCompression):
cog_translate(
raster_path_rgb, "cogeo.tif", jpeg_profile, nodata=0, quiet=True
)
with rasterio.open("cogeo.tif") as src:
assert src.nodata == 0
assert src.compression.value == "JPEG"
assert not has_mask_band(src)
def test_cog_translate_optionWarnings(runner):
"""Should work as expected but warns about invalid options."""
with runner.isolated_filesystem():
with pytest.warns(UserWarning):
cog_translate(
raster_path_rgb, "cogeo.tif", jpeg_profile, nodata=0, quiet=True
)
with rasterio.open("cogeo.tif") as src:
assert src.nodata == 0
assert src.compression.value == "JPEG"
assert not has_mask_band(src)
def test_cogeo_validnodata(runner):
"""Should work as expected."""
with runner.isolated_filesystem():
with pytest.warns(UserWarning):
result = runner.invoke(
cogeo,
[
"create",
raster_path_rgb,
"output.tif",
"--nodata",
"0",
"--cog-profile",
"jpeg",
],
)
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
assert not src.nodata
assert has_mask_band(src)
result = runner.invoke(
cogeo,
[
"create",
raster_path_nodata,
"output.tif",
"--co",
"BLOCKXSIZE=64",
"--co",
"BLOCKYSIZE=64",
"--cog-profile",
"deflate",
],
)
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
assert src.nodata == -9999
assert not has_mask_band(src)
def test_cogeo_validbidx():
"""Should work as expected."""
runner = CliRunner()
with runner.isolated_filesystem():
result = runner.invoke(cogeo, [
raster_path_rgb, "output.tif", "-b", "1", "-p", "raw", "--add-mask"
])
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
assert has_mask_band(src)
assert src.count == 1
def test_cogeo_valid_external_mask(monkeypatch, runner):
"""Should work as expected."""
monkeypatch.setenv("GDAL_TIFF_INTERNAL_MASK", "FALSE")
monkeypatch.setenv("GDAL_DISABLE_READDIR_ON_OPEN", "TRUE")
with runner.isolated_filesystem():
result = runner.invoke(
cogeo, ["create", raster_path_rgb, "output.tif", "--add-mask"])
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
assert has_mask_band(src)
assert "output.tif.msk" in src.files
def _validate_translated_rgb_jpeg(src):
assert src.height == 512
assert src.width == 512
assert src.meta["dtype"] == "uint8"
assert src.is_tiled
assert src.profile["blockxsize"] == 64
assert src.profile["blockysize"] == 64
assert src.compression.value == "JPEG"
assert src.photometric.value == "YCbCr"
assert src.interleaving.value == "PIXEL"
assert src.overviews(1) == [2, 4, 8]
assert src.tags()["OVR_RESAMPLING_ALG"] == "NEAREST"
assert not has_mask_band(src)
def test_cog_translate_valid(runner):
"""Should work as expected (create cogeo file)."""
with runner.isolated_filesystem():
cog_translate(raster_path_rgb, "cogeo.tif", jpeg_profile, quiet=True)
with rasterio.open("cogeo.tif") as src:
_validate_translated_rgb_jpeg(src)
cog_translate(
raster_path_rgb, "cogeo.tif", jpeg_profile, add_mask=True, quiet=True
)
with rasterio.open("cogeo.tif") as src:
assert has_mask_band(src)
with rasterio.open("cogeo.tif", OVERVIEW_LEVEL=1) as src:
assert src.block_shapes[0] == (64, 64)
def _get_info(asset: str) -> Dict:
with rasterio.open(asset) as src_dst:
description = [
src_dst.descriptions[b - 1] for i, b in enumerate(src_dst.indexes)
]
mask = has_mask_band(src_dst)
return (
src_dst.count,
src_dst.dtypes[0],
description,
src_dst.tags(),
src_dst.nodata,
mask,
)
def test_cogeo_valid(runner):
"""Should work as expected."""
with runner.isolated_filesystem():
result = runner.invoke(
cogeo, ["create", raster_path_rgb, "output.tif", "--add-mask", "--quiet"]
)
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
assert src.height == 512
assert src.width == 512
assert src.meta["dtype"] == "uint8"
assert src.is_tiled
assert src.compression.value == "DEFLATE"
assert not src.photometric
assert src.interleaving.value == "PIXEL"
assert not src.overviews(1)
assert has_mask_band(src)
def test_cogeo_valid():
"""Should work as expected."""
runner = CliRunner()
with runner.isolated_filesystem():
result = runner.invoke(
cogeo, [raster_path_rgb, "output.tif", "--add-mask", "--quiet"])
assert not result.exception
assert result.exit_code == 0
with rasterio.open("output.tif") as src:
assert src.height == 512
assert src.width == 512
assert src.meta["dtype"] == "uint8"
assert (
not src.is_tiled
) # Because blocksize is 512 and the file is 512, the output is not tiled
assert src.compression.value == "JPEG"
assert src.photometric.value == "YCbCr"
assert src.interleaving.value == "PIXEL"
assert not src.overviews(1)
assert has_mask_band(src)
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,
)
def cog_translate(
src_path,
dst_path,
dst_kwargs,
indexes=None,
nodata=None,
add_mask=None,
overview_level=None,
overview_resampling="nearest",
web_optimized=False,
latitude_adjustment=True,
resampling="nearest",
in_memory=None,
config=None,
quiet=False,
):
"""
Create Cloud Optimized Geotiff.
Parameters
----------
src_path : str or PathLike object
A dataset path or URL. Will be opened in "r" mode.
dst_path : str or Path-like object
An output dataset path or or PathLike object.
Will be opened in "w" mode.
dst_kwargs: dict
Output dataset creation options.
indexes : tuple, int, optional
Raster band indexes to copy.
nodata, int, optional
Overwrite nodata masking values for input dataset.
add_mask, bool, optional
Force output dataset creation with a mask.
overview_level : int, optional (default: 6)
COGEO overview (decimation) level
overview_resampling : str, optional (default: "nearest")
Resampling algorithm for overviews
web_optimized: bool, option (default: False)
Create web-optimized cogeo.
latitude_adjustment: bool, option (default: True)
Use mercator meters for zoom calculation or ensure max zoom equality.
resampling : str, optional (default: "nearest")
Resampling algorithm.
in_memory: bool, optional
Force processing raster in memory (default: process in memory if small)
config : dict
Rasterio Env options.
quiet: bool, optional (default: False)
Mask processing steps.
"""
config = config or {}
with rasterio.Env(**config):
with rasterio.open(src_path) as src_dst:
meta = src_dst.meta
indexes = indexes if indexes else src_dst.indexes
nodata = nodata if nodata is not None else src_dst.nodata
alpha = has_alpha_band(src_dst)
mask = has_mask_band(src_dst)
if not add_mask and (
(nodata is not None or alpha)
and dst_kwargs.get("compress") in ["JPEG", "jpeg"]):
warnings.warn(
"Using lossy compression with Nodata or Alpha band "
"can results in unwanted artefacts.",
LossyCompression,
)
tilesize = min(int(dst_kwargs["blockxsize"]),
int(dst_kwargs["blockysize"]))
if src_dst.width < tilesize or src_dst.height < tilesize:
tilesize = 2**int(
math.log(min(src_dst.width, src_dst.height), 2))
if tilesize < 64:
warnings.warn(
"Raster has dimension < 64px. Output COG cannot be tiled"
" and overviews cannot be added.",
IncompatibleBlockRasterSize,
)
dst_kwargs.pop("blockxsize", None)
dst_kwargs.pop("blockysize", None)
dst_kwargs.pop("tiled")
overview_level = 0
else:
warnings.warn(
"Block Size are bigger than raster sizes. "
"Setting blocksize to {}".format(tilesize),
IncompatibleBlockRasterSize,
)
dst_kwargs["blockxsize"] = tilesize
dst_kwargs["blockysize"] = tilesize
vrt_params = dict(add_alpha=True)
if nodata is not None:
vrt_params.update(
dict(nodata=nodata, add_alpha=False, src_nodata=nodata))
if alpha:
vrt_params.update(dict(add_alpha=False))
if web_optimized:
bounds = list(
transform_bounds(*[src_dst.crs, "epsg:4326"] +
list(src_dst.bounds),
densify_pts=21))
center = [(bounds[0] + bounds[2]) / 2,
(bounds[1] + bounds[3]) / 2]
lat = 0 if latitude_adjustment else center[1]
max_zoom = get_max_zoom(src_dst, lat=lat, tilesize=tilesize)
extrema = tile_extrema(bounds, max_zoom)
w, n = mercantile.xy(*mercantile.ul(
extrema["x"]["min"], extrema["y"]["min"], max_zoom))
vrt_res = _meters_per_pixel(max_zoom, 0, tilesize=tilesize)
vrt_transform = Affine(vrt_res, 0, w, 0, -vrt_res, n)
vrt_width = (extrema["x"]["max"] -
extrema["x"]["min"]) * tilesize
vrt_height = (extrema["y"]["max"] -
extrema["y"]["min"]) * tilesize
vrt_params.update(
dict(
crs="epsg:3857",
transform=vrt_transform,
width=vrt_width,
height=vrt_height,
resampling=ResamplingEnums[resampling],
))
with WarpedVRT(src_dst, **vrt_params) as vrt_dst:
meta = vrt_dst.meta
meta["count"] = len(indexes)
if add_mask:
meta.pop("nodata", None)
meta.pop("alpha", None)
meta.update(**dst_kwargs)
meta.pop("compress", None)
meta.pop("photometric", None)
if in_memory is None:
in_memory = vrt_dst.width * vrt_dst.height < IN_MEMORY_THRESHOLD
with ExitStack() as ctx:
if in_memory:
tmpfile = ctx.enter_context(MemoryFile())
tmp_dst = ctx.enter_context(tmpfile.open(**meta))
else:
tmpfile = ctx.enter_context(
TemporaryRasterFile(dst_path))
tmp_dst = ctx.enter_context(
rasterio.open(tmpfile.name, "w", **meta))
wind = list(tmp_dst.block_windows(1))
if not quiet:
click.echo("Reading input: {}".format(src_path),
err=True)
fout = os.devnull if quiet else sys.stderr
with click.progressbar(wind,
length=len(wind),
file=fout,
show_percent=True) as windows:
for ij, w in windows:
matrix = vrt_dst.read(window=w, indexes=indexes)
tmp_dst.write(matrix, window=w)
if add_mask or mask:
mask_value = vrt_dst.dataset_mask(window=w)
tmp_dst.write_mask(mask_value, window=w)
if overview_level is None:
overview_level = get_maximum_overview_level(
vrt_dst, tilesize)
if not quiet and overview_level:
click.echo("Adding overviews...", err=True)
overviews = [2**j for j in range(1, overview_level + 1)]
tmp_dst.build_overviews(
overviews, ResamplingEnums[overview_resampling])
if not quiet:
click.echo("Updating dataset tags...", err=True)
for i, b in enumerate(indexes):
tmp_dst.set_band_description(
i + 1, src_dst.descriptions[b - 1])
tags = src_dst.tags()
tags.update(
dict(OVR_RESAMPLING_ALG=ResamplingEnums[
overview_resampling].name.upper()))
tmp_dst.update_tags(**tags)
if not quiet:
click.echo("Writing output to: {}".format(dst_path),
err=True)
copy(tmp_dst,
dst_path,
copy_src_overviews=True,
**dst_kwargs)
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 cog_translate( # noqa: C901
source: Union[str, pathlib.PurePath, DatasetReader, DatasetWriter,
WarpedVRT],
dst_path: Union[str, pathlib.PurePath],
dst_kwargs: Dict,
indexes: Optional[Sequence[int]] = None,
nodata: Optional[Union[str, int, float]] = None,
dtype: Optional[str] = None,
add_mask: bool = False,
overview_level: Optional[int] = None,
overview_resampling: str = "nearest",
web_optimized: bool = False,
tms: morecantile.TileMatrixSet = morecantile.tms.get("WebMercatorQuad"),
zoom_level_strategy: str = "auto",
aligned_levels: Optional[int] = None,
resampling: str = "nearest",
in_memory: Optional[bool] = None,
config: Optional[Dict] = None,
allow_intermediate_compression: bool = False,
forward_band_tags: bool = False,
quiet: bool = False,
temporary_compression: str = "DEFLATE",
):
"""
Create Cloud Optimized Geotiff.
Parameters
----------
source : str, PathLike object or rasterio.io.DatasetReader
A dataset path, URL or rasterio.io.DatasetReader object.
Will be opened in "r" mode.
dst_path : str or PathLike object
An output dataset path or or PathLike object.
Will be opened in "w" mode.
dst_kwargs: dict
Output dataset creation options.
indexes : tuple or int, optional
Raster band indexes to copy.
nodata, int, optional
Overwrite nodata masking values for input dataset.
dtype: str, optional
Overwrite output data type. Default will be the input data type.
add_mask, bool, optional
Force output dataset creation with a mask.
overview_level : int, optional (default: None)
COGEO overview (decimation) level. By default, inferred from data size.
overview_resampling : str, optional (default: "nearest")
Resampling algorithm for overviews
web_optimized: bool, optional (default: False)
Create web-optimized cogeo.
tms: morecantile.TileMatrixSet, optional (default: "WebMercatorQuad")
TileMatrixSet to use for reprojection, resolution and alignment.
zoom_level_strategy: str, optional (default: auto)
Strategy to determine zoom level (same as in GDAL 3.2).
LOWER will select the zoom level immediately below the theoretical computed non-integral zoom level, leading to subsampling.
On the contrary, UPPER will select the immediately above zoom level, leading to oversampling.
Defaults to AUTO which selects the closest zoom level.
ref: https://gdal.org/drivers/raster/cog.html#raster-cog
aligned_levels: int, optional.
Number of overview levels for which GeoTIFF tile and tiles defined in the tiling scheme match.
Default is to use the maximum overview levels.
resampling : str, optional (default: "nearest")
Resampling algorithm.
in_memory: bool, optional
Force processing raster in memory (default: process in memory if small)
config : dict
Rasterio Env options.
allow_intermediate_compression: bool, optional (default: False)
Allow intermediate file compression to reduce memory/disk footprint.
Note: This could reduce the speed of the process.
Ref: https://github.com/cogeotiff/rio-cogeo/issues/103
forward_band_tags: bool, optional
Forward band tags to output bands.
Ref: https://github.com/cogeotiff/rio-cogeo/issues/19
quiet: bool, optional (default: False)
Mask processing steps.
temporary_compression: str, optional
Compression used for the intermediate file, default is deflate.
"""
if isinstance(indexes, int):
indexes = (indexes, )
config = config or {}
with rasterio.Env(**config):
with ExitStack() as ctx:
if isinstance(source, (DatasetReader, DatasetWriter, WarpedVRT)):
src_dst = source
else:
src_dst = ctx.enter_context(rasterio.open(source))
meta = src_dst.meta
indexes = indexes if indexes else src_dst.indexes
nodata = nodata if nodata is not None else src_dst.nodata
dtype = dtype if dtype else src_dst.dtypes[0]
alpha = utils.has_alpha_band(src_dst)
mask = utils.has_mask_band(src_dst)
if not add_mask and (
(nodata is not None or alpha)
and dst_kwargs.get("compress") in ["JPEG", "jpeg"]):
warnings.warn(
"Using lossy compression with Nodata or Alpha band "
"can results in unwanted artefacts.",
LossyCompression,
)
tilesize = min(int(dst_kwargs["blockxsize"]),
int(dst_kwargs["blockysize"]))
if src_dst.width < tilesize or src_dst.height < tilesize:
tilesize = 2**int(
math.log(min(src_dst.width, src_dst.height), 2))
if tilesize < 64:
warnings.warn(
"Raster has dimension < 64px. Output COG cannot be tiled"
" and overviews cannot be added.",
IncompatibleBlockRasterSize,
)
dst_kwargs.pop("blockxsize", None)
dst_kwargs.pop("blockysize", None)
dst_kwargs.pop("tiled")
overview_level = 0
else:
warnings.warn(
"Block Size are bigger than raster sizes. "
"Setting blocksize to {}".format(tilesize),
IncompatibleBlockRasterSize,
)
dst_kwargs["blockxsize"] = tilesize
dst_kwargs["blockysize"] = tilesize
vrt_params = {
"add_alpha": True,
"dtype": dtype,
"width": src_dst.width,
"height": src_dst.height,
}
if nodata is not None:
vrt_params.update(
dict(nodata=nodata, add_alpha=False, src_nodata=nodata))
if alpha:
vrt_params.update(dict(add_alpha=False))
if web_optimized:
params = utils.get_web_optimized_params(
src_dst,
tilesize=tilesize,
warp_resampling=resampling,
zoom_level_strategy=zoom_level_strategy,
aligned_levels=aligned_levels,
tms=tms,
)
vrt_params.update(**params)
with WarpedVRT(src_dst, **vrt_params) as vrt_dst:
meta = vrt_dst.meta
meta["count"] = len(indexes)
if add_mask:
meta.pop("nodata", None)
meta.pop("alpha", None)
if (dst_kwargs.get("photometric", "").upper() == "YCBCR"
and meta["count"] == 1):
warnings.warn(
"PHOTOMETRIC=YCBCR not supported on a 1-band raster"
" and has been set to 'MINISBLACK'")
dst_kwargs["photometric"] = "MINISBLACK"
meta.update(**dst_kwargs)
meta.pop("compress", None)
meta.pop("photometric", None)
if allow_intermediate_compression:
meta["compress"] = temporary_compression
if in_memory is None:
in_memory = vrt_dst.width * vrt_dst.height < IN_MEMORY_THRESHOLD
if in_memory:
tmpfile = ctx.enter_context(MemoryFile())
tmp_dst = ctx.enter_context(tmpfile.open(**meta))
else:
tmpfile = ctx.enter_context(TemporaryRasterFile(dst_path))
tmp_dst = ctx.enter_context(
rasterio.open(tmpfile.name, "w", **meta))
# Transfer color interpolation
if len(indexes) == 1 and (vrt_dst.colorinterp[indexes[0] - 1]
is not ColorInterp.palette):
tmp_dst.colorinterp = [ColorInterp.gray]
else:
tmp_dst.colorinterp = [
vrt_dst.colorinterp[b - 1] for b in indexes
]
if tmp_dst.colorinterp[0] is ColorInterp.palette:
try:
tmp_dst.write_colormap(1, vrt_dst.colormap(1))
except ValueError:
warnings.warn(
"Dataset has `Palette` color interpretation"
" but is missing colormap information")
wind = list(tmp_dst.block_windows(1))
if not quiet:
click.echo("Reading input: {}".format(source), err=True)
fout = os.devnull if quiet else sys.stderr
with click.progressbar(
wind, file=fout,
show_percent=True) as windows: # type: ignore
for _, w in windows:
matrix = vrt_dst.read(window=w, indexes=indexes)
tmp_dst.write(matrix, window=w)
if add_mask or mask:
# Cast mask to uint8 to fix rasterio 1.1.2 error (ref #115)
mask_value = vrt_dst.dataset_mask(
window=w).astype("uint8")
tmp_dst.write_mask(mask_value, window=w)
if overview_level is None:
overview_level = get_maximum_overview_level(
vrt_dst.width, vrt_dst.height, minsize=tilesize)
if not quiet and overview_level:
click.echo("Adding overviews...", err=True)
overviews = [2**j for j in range(1, overview_level + 1)]
tmp_dst.build_overviews(overviews,
ResamplingEnums[overview_resampling])
if not quiet:
click.echo("Updating dataset tags...", err=True)
for i, b in enumerate(indexes):
tmp_dst.set_band_description(i + 1,
src_dst.descriptions[b - 1])
if forward_band_tags:
tmp_dst.update_tags(i + 1, **src_dst.tags(b))
tags = src_dst.tags()
tags.update(
dict(
OVR_RESAMPLING_ALG=ResamplingEnums[overview_resampling]
.name.upper()))
tmp_dst.update_tags(**tags)
tmp_dst._set_all_scales(
[vrt_dst.scales[b - 1] for b in indexes])
tmp_dst._set_all_offsets(
[vrt_dst.offsets[b - 1] for b in indexes])
if not quiet:
click.echo("Writing output to: {}".format(dst_path),
err=True)
copy(tmp_dst, dst_path, copy_src_overviews=True, **dst_kwargs)
def cog_translate(
source,
dst_path,
dst_kwargs,
indexes=None,
nodata=None,
dtype=None,
add_mask=None,
overview_level=None,
overview_resampling="nearest",
web_optimized=False,
latitude_adjustment=True,
resampling="nearest",
in_memory=None,
config=None,
allow_intermediate_compression=False,
forward_band_tags=False,
quiet=False,
):
"""
Create Cloud Optimized Geotiff.
Parameters
----------
source : str, PathLike object or rasterio.io.DatasetReader
A dataset path, URL or rasterio.io.DatasetReader object.
Will be opened in "r" mode.
dst_path : str or Path-like object
An output dataset path or or PathLike object.
Will be opened in "w" mode.
dst_kwargs: dict
Output dataset creation options.
indexes : tuple or int, optional
Raster band indexes to copy.
nodata, int, optional
Overwrite nodata masking values for input dataset.
dtype: str, optional
Overwrite output data type. Default will be the input data type.
add_mask, bool, optional
Force output dataset creation with a mask.
overview_level : int, optional (default: 6)
COGEO overview (decimation) level
overview_resampling : str, optional (default: "nearest")
Resampling algorithm for overviews
web_optimized: bool, option (default: False)
Create web-optimized cogeo.
latitude_adjustment: bool, option (default: True)
Use mercator meters for zoom calculation or ensure max zoom equality.
resampling : str, optional (default: "nearest")
Resampling algorithm.
in_memory: bool, optional
Force processing raster in memory (default: process in memory if small)
config : dict
Rasterio Env options.
allow_intermediate_compression: bool, optional (default: False)
Allow intermediate file compression to reduce memory/disk footprint.
Note: This could reduce the speed of the process.
Ref: https://github.com/cogeotiff/rio-cogeo/issues/103
forward_band_tags: bool, optional
Forward band tags to output bands.
Ref: https://github.com/cogeotiff/rio-cogeo/issues/19
quiet: bool, optional (default: False)
Mask processing steps.
"""
if isinstance(indexes, int):
indexes = (indexes, )
config = config or {}
with rasterio.Env(**config):
with ExitStack() as ctx:
if isinstance(source, (DatasetReader, DatasetWriter, WarpedVRT)):
src_dst = source
else:
src_dst = ctx.enter_context(rasterio.open(source))
meta = src_dst.meta
indexes = indexes if indexes else src_dst.indexes
nodata = nodata if nodata is not None else src_dst.nodata
dtype = dtype if dtype else src_dst.dtypes[0]
alpha = has_alpha_band(src_dst)
mask = has_mask_band(src_dst)
if not add_mask and (
(nodata is not None or alpha)
and dst_kwargs.get("compress") in ["JPEG", "jpeg"]):
warnings.warn(
"Using lossy compression with Nodata or Alpha band "
"can results in unwanted artefacts.",
LossyCompression,
)
tilesize = min(int(dst_kwargs["blockxsize"]),
int(dst_kwargs["blockysize"]))
if src_dst.width < tilesize or src_dst.height < tilesize:
tilesize = 2**int(
math.log(min(src_dst.width, src_dst.height), 2))
if tilesize < 64:
warnings.warn(
"Raster has dimension < 64px. Output COG cannot be tiled"
" and overviews cannot be added.",
IncompatibleBlockRasterSize,
)
dst_kwargs.pop("blockxsize", None)
dst_kwargs.pop("blockysize", None)
dst_kwargs.pop("tiled")
overview_level = 0
else:
warnings.warn(
"Block Size are bigger than raster sizes. "
"Setting blocksize to {}".format(tilesize),
IncompatibleBlockRasterSize,
)
dst_kwargs["blockxsize"] = tilesize
dst_kwargs["blockysize"] = tilesize
vrt_params = dict(add_alpha=True, dtype=dtype)
if nodata is not None:
vrt_params.update(
dict(nodata=nodata, add_alpha=False, src_nodata=nodata))
if alpha:
vrt_params.update(dict(add_alpha=False))
if web_optimized:
bounds = list(
transform_bounds(*[src_dst.crs, "epsg:4326"] +
list(src_dst.bounds),
densify_pts=21))
center = [(bounds[0] + bounds[2]) / 2,
(bounds[1] + bounds[3]) / 2]
lat = 0 if latitude_adjustment else center[1]
max_zoom = get_max_zoom(src_dst, lat=lat, tilesize=tilesize)
extrema = tile_extrema(bounds, max_zoom)
w, n = mercantile.xy(*mercantile.ul(
extrema["x"]["min"], extrema["y"]["min"], max_zoom))
vrt_res = _meters_per_pixel(max_zoom, 0, tilesize=tilesize)
vrt_transform = Affine(vrt_res, 0, w, 0, -vrt_res, n)
vrt_width = (extrema["x"]["max"] -
extrema["x"]["min"]) * tilesize
vrt_height = (extrema["y"]["max"] -
extrema["y"]["min"]) * tilesize
vrt_params.update(
dict(
crs="epsg:3857",
transform=vrt_transform,
width=vrt_width,
height=vrt_height,
resampling=ResamplingEnums[resampling],
))
with WarpedVRT(src_dst, **vrt_params) as vrt_dst:
meta = vrt_dst.meta
meta["count"] = len(indexes)
if add_mask:
meta.pop("nodata", None)
meta.pop("alpha", None)
if (dst_kwargs.get("photometric", "").upper() == "YCBCR"
and meta["count"] == 1):
warnings.warn(
"PHOTOMETRIC=YCBCR not supported on a 1-band raster"
" and has been set to 'MINISBLACK'")
dst_kwargs["photometric"] = "MINISBLACK"
meta.update(**dst_kwargs)
if not allow_intermediate_compression:
meta.pop("compress", None)
meta.pop("photometric", None)
if in_memory is None:
in_memory = vrt_dst.width * vrt_dst.height < IN_MEMORY_THRESHOLD
if in_memory:
tmpfile = ctx.enter_context(MemoryFile())
tmp_dst = ctx.enter_context(tmpfile.open(**meta))
else:
tmpfile = ctx.enter_context(TemporaryRasterFile(dst_path))
tmp_dst = ctx.enter_context(
rasterio.open(tmpfile.name, "w", **meta))
# Transfer color interpolation
if len(indexes) == 1 and (vrt_dst.colorinterp[indexes[0] - 1]
is not ColorInterp.palette):
tmp_dst.colorinterp = [ColorInterp.gray]
else:
tmp_dst.colorinterp = [
vrt_dst.colorinterp[b - 1] for b in indexes
]
if tmp_dst.colorinterp[0] is ColorInterp.palette:
try:
tmp_dst.write_colormap(1, vrt_dst.colormap(1))
except ValueError:
warnings.warn(
"Dataset has `Palette` color interpretation"
" but is missing colormap information")
wind = list(tmp_dst.block_windows(1))
if not quiet:
click.echo("Reading input: {}".format(source), err=True)
fout = os.devnull if quiet else sys.stderr
with click.progressbar(wind,
length=len(wind),
file=fout,
show_percent=True) as windows:
for ij, w in windows:
matrix = vrt_dst.read(window=w, indexes=indexes)
tmp_dst.write(matrix, window=w)
if add_mask or mask:
# Cast mask to uint8 to fix rasterio 1.1.2 error (ref #115)
mask_value = vrt_dst.dataset_mask(
window=w).astype("uint8")
tmp_dst.write_mask(mask_value, window=w)
if overview_level is None:
overview_level = get_maximum_overview_level(
vrt_dst, tilesize)
if not quiet and overview_level:
click.echo("Adding overviews...", err=True)
overviews = [2**j for j in range(1, overview_level + 1)]
tmp_dst.build_overviews(overviews,
ResamplingEnums[overview_resampling])
if not quiet:
click.echo("Updating dataset tags...", err=True)
for i, b in enumerate(indexes):
tmp_dst.set_band_description(i + 1,
src_dst.descriptions[b - 1])
if forward_band_tags:
tmp_dst.update_tags(i + 1, **src_dst.tags(b))
tags = src_dst.tags()
tags.update(
dict(
OVR_RESAMPLING_ALG=ResamplingEnums[overview_resampling]
.name.upper()))
tmp_dst.update_tags(**tags)
tmp_dst._set_all_scales(
[vrt_dst.scales[b - 1] for b in indexes])
tmp_dst._set_all_offsets(
[vrt_dst.offsets[b - 1] for b in indexes])
if not quiet:
click.echo("Writing output to: {}".format(dst_path),
err=True)
copy(tmp_dst, dst_path, copy_src_overviews=True, **dst_kwargs)
def cog_translate(
src_path,
dst_path,
dst_kwargs,
indexes=None,
nodata=None,
add_mask=None,
overview_level=None,
overview_resampling="nearest",
config=None,
quiet=False,
):
"""
Create Cloud Optimized Geotiff.
Parameters
----------
src_path : str or PathLike object
A dataset path or URL. Will be opened in "r" mode.
dst_path : str or Path-like object
An output dataset path or or PathLike object.
Will be opened in "w" mode.
dst_kwargs: dict
output dataset creation options.
indexes : tuple, int, optional
Raster band indexes to copy.
nodata, int, optional
Overwrite nodata masking values for input dataset.
add_mask, bool, optional
Force output dataset creation with a mask.
overview_level : int, optional (default: 6)
COGEO overview (decimation) level
overview_resampling : str, optional (default: "nearest")
Resampling algorithm for overviews
config : dict
Rasterio Env options.
quiet: bool, optional (default: False)
Mask processing steps.
"""
config = config or {}
if overview_level is None:
overview_level = get_maximum_overview_level(
src_path,
min(int(dst_kwargs["blockxsize"]), int(dst_kwargs["blockysize"])))
with rasterio.Env(**config):
with rasterio.open(src_path) as src_dst:
meta = src_dst.meta
indexes = indexes if indexes else src_dst.indexes
nodata = nodata if nodata is not None else src_dst.nodata
alpha = has_alpha_band(src_dst)
mask = has_mask_band(src_dst)
if not add_mask and (
(nodata is not None or alpha)
and dst_kwargs.get("compress") in ["JPEG", "jpeg"]):
warnings.warn(
"Using lossy compression with Nodata or Alpha band "
"can results in unwanted artefacts.",
LossyCompression,
)
vrt_params = dict(add_alpha=True)
if nodata is not None:
vrt_params.update(
dict(nodata=nodata, add_alpha=False, src_nodata=nodata))
if alpha:
vrt_params.update(dict(add_alpha=False))
with WarpedVRT(src_dst, **vrt_params) as vrt_dst:
meta = vrt_dst.meta
meta["count"] = len(indexes)
if add_mask:
meta.pop("nodata", None)
meta.pop("alpha", None)
meta.update(**dst_kwargs)
meta.pop("compress", None)
meta.pop("photometric", None)
with MemoryFile() as memfile:
with memfile.open(**meta) as mem:
wind = list(mem.block_windows(1))
if not quiet:
click.echo("Reading input: {}".format(src_path),
err=True)
fout = os.devnull if quiet else sys.stderr
with click.progressbar(wind,
length=len(wind),
file=fout,
show_percent=True) as windows:
for ij, w in windows:
matrix = vrt_dst.read(window=w,
indexes=indexes)
mem.write(matrix, window=w)
if add_mask or mask:
mask_value = vrt_dst.dataset_mask(window=w)
mem.write_mask(mask_value, window=w)
if not quiet:
click.echo("Adding overviews...", err=True)
overviews = [
2**j for j in range(1, overview_level + 1)
]
mem.build_overviews(overviews,
Resampling[overview_resampling])
if not quiet:
click.echo("Updating dataset tags...", err=True)
for i, b in enumerate(indexes):
mem.set_band_description(
i + 1, src_dst.descriptions[b - 1])
tags = src_dst.tags()
tags.update(
dict(OVR_RESAMPLING_ALG=Resampling[
overview_resampling].name.upper()))
mem.update_tags(**tags)
if not quiet:
click.echo(
"Writing output to: {}".format(dst_path),
err=True)
copy(mem,
dst_path,
copy_src_overviews=True,
**dst_kwargs)
def cog_translate( # noqa: C901
source: Union[str, pathlib.PurePath, DatasetReader, DatasetWriter,
WarpedVRT],
dst_path: Union[str, pathlib.PurePath],
dst_kwargs: Dict,
indexes: Optional[Sequence[int]] = None,
nodata: Optional[Union[str, int, float]] = None,
dtype: Optional[str] = None,
add_mask: bool = False,
overview_level: Optional[int] = None,
overview_resampling: str = "nearest",
web_optimized: bool = False,
tms: Optional[morecantile.TileMatrixSet] = None,
zoom_level_strategy: str = "auto",
zoom_level: Optional[int] = None,
aligned_levels: Optional[int] = None,
resampling: str = "nearest",
in_memory: Optional[bool] = None,
config: Optional[Dict] = None,
allow_intermediate_compression: bool = False,
forward_band_tags: bool = False,
quiet: bool = False,
temporary_compression: str = "DEFLATE",
colormap: Optional[Dict] = None,
additional_cog_metadata: Optional[Dict] = None,
use_cog_driver: bool = False,
):
"""
Create Cloud Optimized Geotiff.
Parameters
----------
source : str, PathLike object or rasterio.io.DatasetReader
A dataset path, URL or rasterio.io.DatasetReader object.
Will be opened in "r" mode.
dst_path : str or PathLike object
An output dataset path or or PathLike object.
Will be opened in "w" mode.
dst_kwargs: dict
Output dataset creation options.
indexes : tuple or int, optional
Raster band indexes to copy.
nodata, int, optional
Overwrite nodata masking values for input dataset.
dtype: str, optional
Overwrite output data type. Default will be the input data type.
add_mask, bool, optional
Force output dataset creation with a mask.
overview_level : int, optional (default: None)
COGEO overview (decimation) level. By default, inferred from data size.
overview_resampling : str, optional (default: "nearest")
Resampling algorithm for overviews
web_optimized: bool, optional (default: False)
Create web-optimized cogeo.
tms: morecantile.TileMatrixSet, optional (default: "WebMercatorQuad")
TileMatrixSet to use for reprojection, resolution and alignment.
zoom_level_strategy: str, optional (default: auto)
Strategy to determine zoom level (same as in GDAL 3.2).
LOWER will select the zoom level immediately below the theoretical computed non-integral zoom level, leading to subsampling.
On the contrary, UPPER will select the immediately above zoom level, leading to oversampling.
Defaults to AUTO which selects the closest zoom level.
ref: https://gdal.org/drivers/raster/cog.html#raster-cog
zoom_level: int, optional.
Zoom level number (starting at 0 for coarsest zoom level). If this option is specified, `--zoom-level-strategy` is ignored.
aligned_levels: int, optional.
Number of overview levels for which GeoTIFF tile and tiles defined in the tiling scheme match.
Default is to use the maximum overview levels. Note: GDAL use number of resolution levels instead of overview levels.
resampling : str, optional (default: "nearest")
Resampling algorithm.
in_memory: bool, optional
Force processing raster in memory (default: process in memory if small)
config : dict
Rasterio Env options.
allow_intermediate_compression: bool, optional (default: False)
Allow intermediate file compression to reduce memory/disk footprint.
Note: This could reduce the speed of the process.
Ref: https://github.com/cogeotiff/rio-cogeo/issues/103
forward_band_tags: bool, optional
Forward band tags to output bands.
Ref: https://github.com/cogeotiff/rio-cogeo/issues/19
quiet: bool, optional (default: False)
Mask processing steps.
temporary_compression: str, optional
Compression used for the intermediate file, default is deflate.
colormap: dict, optional
Overwrite or add a colormap to the output COG.
additional_cog_metadata: dict, optional
Additional dataset metadata to add to the COG.
use_cog_driver: bool, optional (default: False)
Use GDAL COG driver if set to True. COG driver is available starting with GDAL 3.1.
"""
tms = tms or morecantile.tms.get("WebMercatorQuad")
dst_kwargs = dst_kwargs.copy()
if isinstance(indexes, int):
indexes = (indexes, )
config = config or {}
with rasterio.Env(**config):
with ExitStack() as ctx:
if isinstance(source, (DatasetReader, DatasetWriter, WarpedVRT)):
src_dst = source
else:
src_dst = ctx.enter_context(rasterio.open(source))
meta = src_dst.meta
indexes = indexes if indexes else src_dst.indexes
nodata = nodata if nodata is not None else src_dst.nodata
dtype = dtype if dtype else src_dst.dtypes[0]
alpha = utils.has_alpha_band(src_dst)
mask = utils.has_mask_band(src_dst)
if colormap and len(indexes) > 1:
raise IncompatibleOptions(
"Cannot add a colormap for multiple bands data.")
if not add_mask and (
(nodata is not None or alpha)
and dst_kwargs.get("compress", "").lower() == "jpeg"):
warnings.warn(
"Nodata/Alpha band will be translated to an internal mask band.",
)
add_mask = True
indexes = (utils.non_alpha_indexes(src_dst)
if len(indexes) not in [1, 3] else indexes)
tilesize = min(int(dst_kwargs["blockxsize"]),
int(dst_kwargs["blockysize"]))
if src_dst.width < tilesize or src_dst.height < tilesize:
tilesize = 2**int(
math.log(min(src_dst.width, src_dst.height), 2))
if tilesize < 64:
warnings.warn(
"Raster has dimension < 64px. Output COG cannot be tiled"
" and overviews cannot be added.",
IncompatibleBlockRasterSize,
)
dst_kwargs.pop("blockxsize", None)
dst_kwargs.pop("blockysize", None)
dst_kwargs.pop("tiled")
overview_level = 0
else:
warnings.warn(
"Block Size are bigger than raster sizes. "
"Setting blocksize to {}".format(tilesize),
IncompatibleBlockRasterSize,
)
dst_kwargs["blockxsize"] = tilesize
dst_kwargs["blockysize"] = tilesize
vrt_params = {
"add_alpha": True,
"dtype": dtype,
"width": src_dst.width,
"height": src_dst.height,
"resampling": ResamplingEnums[resampling],
}
if nodata is not None:
vrt_params.update(
dict(nodata=nodata, add_alpha=False, src_nodata=nodata))
if alpha:
vrt_params.update(dict(add_alpha=False))
if web_optimized and not use_cog_driver:
params = utils.get_web_optimized_params(
src_dst,
zoom_level_strategy=zoom_level_strategy,
zoom_level=zoom_level,
aligned_levels=aligned_levels,
tms=tms,
)
vrt_params.update(**params)
with WarpedVRT(src_dst, **vrt_params) as vrt_dst:
meta = vrt_dst.meta
meta["count"] = len(indexes)
if add_mask:
meta.pop("nodata", None)
meta.pop("alpha", None)
if (dst_kwargs.get("photometric", "").upper() == "YCBCR"
and meta["count"] == 1):
warnings.warn(
"PHOTOMETRIC=YCBCR not supported on a 1-band raster"
" and has been set to 'MINISBLACK'")
dst_kwargs["photometric"] = "MINISBLACK"
meta.update(**dst_kwargs)
meta.pop("compress", None)
meta.pop("photometric", None)
if allow_intermediate_compression:
meta["compress"] = temporary_compression
if in_memory is None:
in_memory = vrt_dst.width * vrt_dst.height < IN_MEMORY_THRESHOLD
if in_memory:
tmpfile = ctx.enter_context(MemoryFile())
tmp_dst = ctx.enter_context(tmpfile.open(**meta))
else:
tmpfile = ctx.enter_context(TemporaryRasterFile(dst_path))
tmp_dst = ctx.enter_context(
rasterio.open(tmpfile.name, "w", **meta))
# Transfer color interpolation
if len(indexes) == 1 and (vrt_dst.colorinterp[indexes[0] - 1]
is not ColorInterp.palette):
tmp_dst.colorinterp = [ColorInterp.gray]
else:
tmp_dst.colorinterp = [
vrt_dst.colorinterp[b - 1] for b in indexes
]
if colormap:
if tmp_dst.colorinterp[0] is not ColorInterp.palette:
tmp_dst.colorinterp = [ColorInterp.palette]
warnings.warn(
"Dataset color interpretation was set to `Palette`"
)
tmp_dst.write_colormap(1, colormap)
elif tmp_dst.colorinterp[0] is ColorInterp.palette:
try:
tmp_dst.write_colormap(1, vrt_dst.colormap(1))
except ValueError:
warnings.warn(
"Dataset has `Palette` color interpretation"
" but is missing colormap information")
wind = list(tmp_dst.block_windows(1))
if not quiet:
click.echo("Reading input: {}".format(source), err=True)
fout = ctx.enter_context(open(os.devnull,
"w")) if quiet else sys.stderr
with click.progressbar(
wind, file=fout,
show_percent=True) as windows: # type: ignore
for _, w in windows:
matrix = vrt_dst.read(window=w, indexes=indexes)
tmp_dst.write(matrix, window=w)
if add_mask or mask:
# Cast mask to uint8 to fix rasterio 1.1.2 error (ref #115)
mask_value = vrt_dst.dataset_mask(
window=w).astype("uint8")
tmp_dst.write_mask(mask_value, window=w)
if overview_level is None:
overview_level = get_maximum_overview_level(
vrt_dst.width, vrt_dst.height, minsize=tilesize)
if not quiet and overview_level:
click.echo("Adding overviews...", err=True)
overviews = [2**j for j in range(1, overview_level + 1)]
tmp_dst.build_overviews(overviews,
ResamplingEnums[overview_resampling])
if not quiet:
click.echo("Updating dataset tags...", err=True)
for i, b in enumerate(indexes):
tmp_dst.set_band_description(i + 1,
src_dst.descriptions[b - 1])
if forward_band_tags:
tmp_dst.update_tags(i + 1, **src_dst.tags(b))
tags = src_dst.tags()
tags.update(
dict(
OVR_RESAMPLING_ALG=ResamplingEnums[overview_resampling]
.name.upper()))
if additional_cog_metadata:
tags.update(**additional_cog_metadata)
if web_optimized and not use_cog_driver:
default_zoom = tms.zoom_for_res(
max(tmp_dst.res),
max_z=30,
zoom_level_strategy=zoom_level_strategy,
)
dst_kwargs.update({
"@TILING_SCHEME_NAME":
tms.identifier,
"@TILING_SCHEME_ZOOM_LEVEL":
zoom_level if zoom_level is not None else default_zoom,
})
if aligned_levels:
dst_kwargs.update(
{"@TILING_SCHEME_ALIGNED_LEVELS": aligned_levels})
tmp_dst.update_tags(**tags)
tmp_dst._set_all_scales(
[vrt_dst.scales[b - 1] for b in indexes])
tmp_dst._set_all_offsets(
[vrt_dst.offsets[b - 1] for b in indexes])
if not quiet:
click.echo("Writing output to: {}".format(dst_path),
err=True)
if use_cog_driver:
if not GDALVersion.runtime().at_least("3.1"):
raise Exception(
"GDAL 3.1 or above required to use the COG driver."
)
dst_kwargs["driver"] = "COG"
if web_optimized:
dst_kwargs["TILING_SCHEME"] = (
"GoogleMapsCompatible" if tms.identifier
== "WebMercatorQuad" else tms.identifier)
if zoom_level is not None:
if not GDALVersion.runtime().at_least("3.5"):
warnings.warn(
"ZOOM_LEVEL option is only available with GDAL >3.5."
)
dst_kwargs["ZOOM_LEVEL"] = zoom_level
dst_kwargs["ZOOM_LEVEL_STRATEGY"] = zoom_level_strategy
if aligned_levels is not None:
# GDAL uses Number of resolution (not overviews)
# See https://github.com/OSGeo/gdal/issues/5336#issuecomment-1042946603
dst_kwargs["aligned_levels"] = aligned_levels + 1
if add_mask and dst_kwargs.get("compress", "") != "JPEG":
warnings.warn(
"With GDAL COG driver, mask band will be translated to an alpha band."
)
dst_kwargs["overview_resampling"] = overview_resampling
dst_kwargs["warp_resampling"] = resampling
dst_kwargs["blocksize"] = tilesize
dst_kwargs.pop("blockxsize", None)
dst_kwargs.pop("blockysize", None)
dst_kwargs.pop("tiled", None)
dst_kwargs.pop("interleave", None)
dst_kwargs.pop("photometric", None)
copy(tmp_dst, dst_path, **dst_kwargs)
else:
copy(tmp_dst,
dst_path,
copy_src_overviews=True,
**dst_kwargs)