def georeference_raster_tile(x, y, z, input_path, output_path, expandRgba):
bounds = tile_edges(x, y, z)
named_args = {
"outputSRS": "EPSG:4326",
"outputBounds": bounds,
}
if expandRgba:
named_args["rgbExpand"] = "rgba"
Translate(
output_path,
input_path,
**named_args,
)
def copy_vrt(in_fname, out_fname=None, bbox=None, verbose=True):
"""Create a VRT for (a subset of) a gdal-readable file
bbox format: (left, bottom, right, top)"""
from gdal import Translate
if out_fname is None:
out_fname = in_fname + ".vrt"
# Using Translate... but would use Warp if every reprojecting
if bbox:
left, bottom, right, top = bbox
projwin = (left, top, right, bottom
) # unclear why Translate does UL LR
else:
projwin = None
if verbose:
logger.info(f"Creating {out_fname}, subset bbox: {bbox}")
Translate(out_fname, in_fname, projWin=projwin)
def _convert_to_tif(
partial_coverage_tiles: List[PartialCoverageTile], wms_crs_code: str
) -> None:
for tile in partial_coverage_tiles:
if os.path.exists(tile.wms_path):
logging.debug(f"Converting {tile.wms_path} to {tile.tif_path}")
src_file = Open(tile.wms_path, GA_ReadOnly)
Translate(
tile.tif_path,
src_file,
format="GTiff",
noData=None,
outputSRS=wms_crs_code,
# Translate expects bounds in format ulX, ulY, lrX, lrY so flip minY and maxY
outputBounds=(tile.x_min, tile.y_max, tile.x_max, tile.y_min),
)
if remove_intermediaries():
os.remove(tile.wms_path)
else:
logging.warn(f"Expected file {tile.wms_path} does not exist")
def resize_with_gdal(geo_dataset_path, resize_dim):
dest_path = geo_dataset_path.parent / geo_dataset_path.name[:-1]
geo_obj = gdal.Open(str(geo_dataset_path))
t_o = {"width": resize_dim[0], "height": resize_dim[1]}
ds = Translate(str(dest_path), geo_obj, **t_o)
ds = None
path_to_image.unlink()
if __name__ == '__main__':
dataset_name = "20210325175353219035"
make_dataset(dataset_name)
# not used in this stub but often useful for finding various files
# find .env automagically by walking up directories until it's found, then
# load up the .env entries as environment variables
# refine_glc()
# path_to_img = Path("..", "..", "data", "processed", "20210324225635924767", "images", "20210324225635924767_0.tiff")
# my_img_array = gdal.Open(str(path_to_img)).ReadAsArray()
# my_img_array = np.swapaxes(my_img_array, 0, 2).copy()
# new_array = crop_centre(my_img_array, 256, 256)
# print(my_img_array.shape, new_array.shape)
# fig, axs = plt.subplots(ncols=2, nrows=1)
# axs[0].imshow(my_img_array)
# axs[1].imshow(new_array)
# fig.show()
path_to_img = Path("/home/matt/Dropbox/github/climate_hackathon/data/processed/20210325175353219035/masks/20210325175353219035_0.tiff")
dest_path = path_to_img.parent / path_to_img.name[:-1]
geo_obj = gdal.Open(str(path_to_img))
t_o = {"width": 256, "height": 256}
ds = Translate(str(dest_path), geo_obj, **t_o)
ds = None