def get_color_table(
color_palette_or_path_or_strings_or_ds: ColorPaletteOrPathOrStrings,
min_key=0,
max_key=255,
fill_missing_colors=True) -> Optional[gdal.ColorTable]:
if (color_palette_or_path_or_strings_or_ds is None or isinstance(
color_palette_or_path_or_strings_or_ds, gdal.ColorTable)):
return color_palette_or_path_or_strings_or_ds
if isinstance(color_palette_or_path_or_strings_or_ds, gdal.Dataset):
return get_color_table_from_raster(
color_palette_or_path_or_strings_or_ds)
pal = get_color_palette(color_palette_or_path_or_strings_or_ds)
if pal is None:
return get_color_table_from_raster(
color_palette_or_path_or_strings_or_ds)
color_table = gdal.ColorTable()
if fill_missing_colors:
keys = sorted(list(pal.pal.keys()))
if min_key is None:
min_key = keys[0]
if max_key is None:
max_key = keys[-1]
c = pal.color_to_color_entry(pal.pal[keys[0]])
for key in range(min_key, max_key + 1):
if key in keys:
c = pal.color_to_color_entry(pal.pal[key])
color_table.SetColorEntry(key, c)
else:
for key, col in pal.pal.items():
color_table.SetColorEntry(
key, pal.color_to_color_entry(col)) # set color for each key
return color_table
def get_color_table(color_palette_or_path_or_strings_or_ds: Optional[ColorTableLike],
**kwargs) -> Optional[gdal.ColorTable]:
if (color_palette_or_path_or_strings_or_ds is None or
isinstance(color_palette_or_path_or_strings_or_ds, gdal.ColorTable)):
return color_palette_or_path_or_strings_or_ds
if isinstance(color_palette_or_path_or_strings_or_ds, gdal.Dataset):
return get_color_table_from_raster(color_palette_or_path_or_strings_or_ds)
try:
pal = get_color_palette(color_palette_or_path_or_strings_or_ds)
color_table = gdal.ColorTable()
res = color_table_from_color_palette(pal, color_table, **kwargs)
return color_table if res else None
except:
# the input might be a filename of a raster file
return get_color_table_from_raster(color_palette_or_path_or_strings_or_ds)
def pct2rgb(src_filename: PathLikeOrStr, pct_filename: Optional[PathLikeOrStr], dst_filename: PathLikeOrStr,
band_number: int = 1, out_bands: int = 3, driver_name: Optional[str] = None):
# Open source file
src_ds = open_ds(src_filename)
if src_ds is None:
raise Exception(f'Unable to open {src_filename} ')
src_band = src_ds.GetRasterBand(band_number)
# ----------------------------------------------------------------------------
# Ensure we recognise the driver.
if driver_name is None:
driver_name = GetOutputDriverFor(dst_filename)
dst_driver = gdal.GetDriverByName(driver_name)
if dst_driver is None:
raise Exception(f'"{driver_name}" driver not registered.')
# ----------------------------------------------------------------------------
# Build color table.
if pct_filename is not None:
pal = get_color_palette(pct_filename)
if pal.has_percents():
min_val = src_band.GetMinimum()
max_val = src_band.GetMinimum()
pal.apply_percent(min_val, max_val)
ct = get_color_table(pal)
else:
ct = src_band.GetRasterColorTable()
ct_size = ct.GetCount()
lookup = [np.arange(ct_size),
np.arange(ct_size),
np.arange(ct_size),
np.ones(ct_size) * 255]
if ct is not None:
for i in range(ct_size):
entry = ct.GetColorEntry(i)
for c in range(4):
lookup[c][i] = entry[c]
# ----------------------------------------------------------------------------
# Create the working file.
if driver_name.lower() == 'gtiff':
tif_filename = dst_filename
else:
tif_filename = 'temp.tif'
gtiff_driver = gdal.GetDriverByName('GTiff')
tif_ds = gtiff_driver.Create(tif_filename, src_ds.RasterXSize, src_ds.RasterYSize, out_bands)
# ----------------------------------------------------------------------------
# We should copy projection information and so forth at this point.
tif_ds.SetProjection(src_ds.GetProjection())
tif_ds.SetGeoTransform(src_ds.GetGeoTransform())
if src_ds.GetGCPCount() > 0:
tif_ds.SetGCPs(src_ds.GetGCPs(), src_ds.GetGCPProjection())
# ----------------------------------------------------------------------------
# Do the processing one scanline at a time.
progress(0.0)
for iY in range(src_ds.RasterYSize):
src_data = src_band.ReadAsArray(0, iY, src_ds.RasterXSize, 1)
for iBand in range(out_bands):
band_lookup = lookup[iBand]
dst_data = np.take(band_lookup, src_data)
tif_ds.GetRasterBand(iBand + 1).WriteArray(dst_data, 0, iY)
progress((iY + 1.0) / src_ds.RasterYSize)
# ----------------------------------------------------------------------------
# Translate intermediate file to output format if desired format is not TIFF.
if tif_filename == dst_filename:
dst_ds = tif_ds
else:
dst_ds = dst_driver.CreateCopy(dst_filename or '', tif_ds)
tif_ds = None
gtiff_driver.Delete(tif_filename)
return dst_ds