def polygonize_pmap(pmap_ds: gdal.Dataset,
pmap_threshold=131,
layer_name='unknown.gpkg',
path_out=None) -> gdal.Dataset:
pmap_bin_img = (pmap_ds.ReadAsArray() > pmap_threshold).astype(np.uint8)
pmap_bin_ds = add_ref_to_img(pmap_bin_img, pmap_ds)
#
srs = osr.SpatialReference()
srs.ImportFromWkt(pmap_ds.GetProjectionRef())
#
if path_out is None:
ds_out = ogr.GetDriverByName('MEMORY').CreateDataSource('wrk')
# ds_out = ogr.GetDriverByName('ESRI Shapefile').CreateDataSource(f'/vsimem/{layer_name}.shp')
else:
drv = ogr.GetDriverByName('GPKG')
if os.path.isfile(path_out):
drv.DeleteDataSource(path_out)
ds_out = drv.CreateDataSource(path_out)
layer_name = os.path.splitext(os.path.basename(path_out))[0]
ds_layer = ds_out.CreateLayer(layer_name,
geom_type=ogr.wkbPolygon,
srs=srs)
fd = ogr.FieldDefn('DN', ogr.OFTInteger)
ds_layer.CreateField(fd)
dst_field = 0
# path_pmap = '/home/ar/data/uiip/quarry_data_test/s2_u8_t3_msk.tif'
ds_band = pmap_bin_ds.GetRasterBand(1)
gdal.Polygonize(ds_band,
ds_band,
ds_layer,
dst_field, [],
callback=gdal.TermProgress)
return ds_out
def load_from_dataset(self, image_dataset: gdal.Dataset) -> Image:
geo_transform = self._load_geotransform(image_dataset)
projection = image_dataset.GetProjection()
pixels = image_dataset.ReadAsArray()
if pixels.ndim > 2:
pixels = pixels.transpose(1, 2, 0)
return Image(pixels, geo_transform, projection)
def load_from_dataset_and_clip(self, image_dataset: gdal.Dataset,
extent: GeoPolygon) -> Image:
geo_transform = self._load_geotransform(image_dataset)
pixel_polygon = extent.to_pixel(geo_transform)
bounds = [int(bound) for bound in pixel_polygon.polygon.bounds]
pixels = image_dataset.ReadAsArray(bounds[0], bounds[1],
bounds[2] - bounds[0],
bounds[3] - bounds[1])
subset_geo_transform = geo_transform.subset(x=bounds[0], y=bounds[1])
pixel_polygon = extent.to_pixel(subset_geo_transform)
if pixels.ndim > 2:
pixels = pixels.transpose(1, 2, 0)
return Image(pixels, subset_geo_transform, image_dataset.GetProjection())\
.clip_with(pixel_polygon, mask_value=0)
def gdal_to_json(ds: gdal.Dataset):
gt = ds.GetGeoTransform(can_return_null=True)
xsize = ds.RasterXSize
ysize = ds.RasterYSize
srs = get_srs(ds)
srs = srs.ExportToProj4()
minx = gt[0] + gt[1] * 0 + gt[2] * 0
miny = gt[3] + gt[4] * 0 + gt[5] * 0
maxx = gt[0] + gt[1] * xsize + gt[2] * ysize
maxy = gt[3] + gt[4] * xsize + gt[5] * ysize
bbox = miny, minx, maxy, maxx
band_list = range(1, ds.RasterCount + 1)
data = [
ds.ReadAsArray(band_list=[bnd]).ravel().tolist() for bnd in band_list
]
ndv = [ds.GetRasterBand(i).GetNoDataValue() for i in band_list]
result = dict(bbox=bbox,
gt=gt,
srs=srs,
size=(xsize, ysize),
data=data,
ndv=ndv)
return result