| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.## Licensed under the Apache License, Version 2.0 (the "License");# you may not use this file except in compliance with the License.# You may obtain a copy of the License at##    http://www.apache.org/licenses/LICENSE-2.0## Unless required by applicable law or agreed to in writing, software# distributed under the License is distributed on an "AS IS" BASIS,# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.# See the License for the specific language governing permissions and# limitations under the License.import os.path as ospimport numpy as npfrom typing import List, Tuple, Unionfrom paddlers.transforms.functions import to_uint8 as raster2uint8try:    from osgeo import gdalexcept:    import gdalclass Raster:    def __init__(self,                 path: str,                 band_list: Union[List[int], Tuple[int], None]=None,                 to_uint8: bool=False) -> None:        """ Class of read raster.        Args:            path (str): The path of raster.            band_list (Union[List[int], Tuple[int], None], optional):                 band list (start with 1) or None (all of bands). Defaults to None.            to_uint8 (bool, optional):                 Convert uint8 or return raw data. Defaults to False.        """        super(Raster, self).__init__()        if osp.exists(path):            self.path = path            self.ext_type = path.split(".")[-1]            if self.ext_type.lower() in ["npy", "npz"]:                self._src_data = None            else:                try:                    # raster format support in GDAL:                     # https://www.osgeo.cn/gdal/drivers/raster/index.html                    self._src_data = gdal.Open(path)                except:                    raise TypeError("Unsupported data format: `{}`".format(                        self.ext_type))            self.to_uint8 = to_uint8            self.setBands(band_list)            self._getInfo()        else:            raise ValueError("The path {0} not exists.".format(path))    def setBands(self, band_list: Union[List[int], Tuple[int], None]) -> None:        """ Set band of data.        Args:            band_list (Union[List[int], Tuple[int], None]):                 band list (start with 1) or None (all of bands).        """        if band_list is not None:            if len(band_list) > self.bands:                raise ValueError(                    "The lenght of band_list must be less than {0}.".format(                        str(self.bands)))            if max(band_list) > self.bands or min(band_list) < 1:                raise ValueError("The range of band_list must within [1, {0}].".                                 format(str(self.bands)))        self.band_list = band_list    def getArray(            self,            start_loc: Union[List[int], Tuple[int], None]=None,            block_size: Union[List[int], Tuple[int]]=[512, 512]) -> np.ndarray:        """ Get ndarray data         Args:            start_loc (Union[List[int], Tuple[int], None], optional):                 Coordinates of the upper left corner of the block, if None means return full image.            block_size (Union[List[int], Tuple[int]], optional):                 Block size. Defaults to [512, 512].        Returns:            np.ndarray: data's ndarray.        """        if self._src_data is not None:            if start_loc is None:                return self._getAarray()            else:                return self._getBlock(start_loc, block_size)        else:            print("Numpy doesn't support blocking temporarily.")            return self._getNumpy()    def _getInfo(self) -> None:        if self._src_data is not None:            self.bands = self._src_data.RasterCount            self.width = self._src_data.RasterXSize            self.height = self._src_data.RasterYSize            self.geot = self._src_data.GetGeoTransform()            self.proj = self._src_data.GetProjection()            d_name = self._getBlock([0, 0], [1, 1]).dtype.name        else:            d_img = self._getNumpy()            d_shape = d_img.shape            d_name = d_img.dtype.name            if len(d_shape) == 3:                self.height, self.width, self.bands = d_shape            else:                self.height, self.width = d_shape                self.bands = 1            self.geot = None            self.proj = None        if "int8" in d_name:            self.datatype = gdal.GDT_Byte        elif "int16" in d_name:            self.datatype = gdal.GDT_UInt16        else:            self.datatype = gdal.GDT_Float32    def _getNumpy(self):        ima = np.load(self.path)        if self.band_list is not None:            band_array = []            for b in self.band_list:                band_i = ima[:, :, b - 1]                band_array.append(band_i)            ima = np.stack(band_array, axis=0)        return ima    def _getAarray(            self,            window: Union[None, List[int], Tuple[int]]=None) -> np.ndarray:        if window is not None:            xoff, yoff, xsize, ysize = window        if self.band_list is None:            if window is None:                ima = self._src_data.ReadAsArray()            else:                ima = self._src_data.ReadAsArray(xoff, yoff, xsize, ysize)        else:            band_array = []            for b in self.band_list:                if window is None:                    band_i = self._src_data.GetRasterBand(b).ReadAsArray()                else:                    band_i = self._src_data.GetRasterBand(b).ReadAsArray(                        xoff, yoff, xsize, ysize)                band_array.append(band_i)            ima = np.stack(band_array, axis=0)        if self.bands == 1:            # the type is complex means this is a SAR data            if isinstance(type(ima[0, 0]), complex):                ima = abs(ima)        else:            ima = ima.transpose((1, 2, 0))        if self.to_uint8 is True:            ima = raster2uint8(ima)        return ima    def _getBlock(            self,            start_loc: Union[List[int], Tuple[int]],            block_size: Union[List[int], Tuple[int]]=[512, 512]) -> np.ndarray:        if len(start_loc) != 2 or len(block_size) != 2:            raise ValueError("The length start_loc/block_size must be 2.")        xoff, yoff = start_loc        xsize, ysize = block_size        if (xoff < 0 or xoff > self.width) or (yoff < 0 or yoff > self.height):            raise ValueError("start_loc must be within [0-{0}, 0-{1}].".format(                str(self.width), str(self.height)))        if xoff + xsize > self.width:            xsize = self.width - xoff        if yoff + ysize > self.height:            ysize = self.height - yoff        ima = self._getAarray([int(xoff), int(yoff), int(xsize), int(ysize)])        h, w = ima.shape[:2] if len(ima.shape) == 3 else ima.shape        if self.bands != 1:            tmp = np.zeros(                (block_size[0], block_size[1], self.bands), dtype=ima.dtype)            tmp[:h, :w, :] = ima        else:            tmp = np.zeros((block_size[0], block_size[1]), dtype=ima.dtype)            tmp[:h, :w] = ima        return tmp
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