Source code for eoreader.products.optical.vhr_product

# -*- coding: utf-8 -*-
# Copyright 2023, SERTIT-ICube - France, https://sertit.unistra.fr/
# This file is part of eoreader project
#     https://github.com/sertit/eoreader
#
# 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
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#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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"""
Maxar super class.
See `here <https://earth.esa.int/eogateway/documents/20142/37627/DigitalGlobe-Standard-Imagery.pdf>`_
for more information.
"""
import logging
import os
from abc import abstractmethod
from typing import Union

import affine
import numpy as np
import rasterio
import xarray as xr
from rasterio import rpc
from rasterio import shutil as rio_shutil
from rasterio import warp
from rasterio.crs import CRS
from rasterio.enums import Resampling
from rasterio.vrt import WarpedVRT
from sertit import AnyPath, path, rasters, rasters_rio
from sertit.snap import MAX_CORES
from sertit.types import AnyPathStrType, AnyPathType

from eoreader import EOREADER_NAME, utils
from eoreader.bands import BandNames
from eoreader.env_vars import DEM_PATH, TILE_SIZE
from eoreader.exceptions import InvalidProductError
from eoreader.keywords import DEM_KW
from eoreader.products import OpticalProduct
from eoreader.utils import DEFAULT_TILE_SIZE

LOGGER = logging.getLogger(EOREADER_NAME)


[docs]class VhrProduct(OpticalProduct): """ Super Class of VHR products. Implementing mechanisms for orthorectification, default transform... """
[docs] def __init__( self, product_path: AnyPathStrType, archive_path: AnyPathStrType = None, output_path: AnyPathStrType = None, remove_tmp: bool = False, **kwargs, ) -> None: self.ortho_path = None """ Orthorectified path. Can be set to use manually orthorectified or pansharpened data, especially useful for VHR data on steep terrain. """ self._proj_prod_type = [] self.band_combi = None """ Band combination, i.e. PAN, PMS, MS... """ # Order id (product name more or less) self._order_id = None # Resolutions self._pan_res = None self._ms_res = None self._job_id = None self._raw_nodata = 0 # Initialization from the super class super().__init__(product_path, archive_path, output_path, remove_tmp, **kwargs)
def _post_init(self, **kwargs) -> None: """ Function used to post_init the products (setting sensor type, band names and so on) """ # Job ID self._job_id = self._get_job_id() # Post init done by the super class super()._post_init(**kwargs)
[docs] def get_default_band_path(self, **kwargs) -> AnyPathType: """ Get default band (:code:`GREEN` for optical data) path. .. WARNING: If you are using a non orthorectified product, this function will orthorectify the stack. To do so, you **MUST** provide a DEM through the EOREADER_DEM_PATH environment variable .. WARNING: If you are using a non-projected product, this function will reproject the stack. .. code-block:: python >>> from eoreader.reader import Reader >>> path = r"IMG_PHR1B_PMS_001" >>> prod = Reader().open(path) >>> prod.get_default_band_path() 'IMG_PHR1A_PMS_001/DIM_PHR1A_PMS_202005110231585_ORT_5547047101.XML' Args: kwargs: Additional arguments Returns: AnyPathType: Default band path """ return self._get_default_utm_band(self.pixel_size, **kwargs)
@abstractmethod def _get_raw_crs(self) -> CRS: """ Get raw CRS of the tile Returns: rasterio.crs.CRS: CRS object """ raise NotImplementedError def _get_ortho_path(self, **kwargs) -> AnyPathType: """ Get the orthorectified path of the bands. Returns: AnyPathType: Orthorectified path """ if self.product_type in self._proj_prod_type: ortho_name = f"{self.condensed_name}_ortho.tif" ortho_path, ortho_exists = self._get_out_path(ortho_name) if not ortho_exists: LOGGER.info( "Manually orthorectified stack not given by the user. " "Reprojecting whole stack, this may take a while. " "(May be inaccurate on steep terrain, depending on the DEM pixel size)" ) # Reproject and write on disk data dem_path = self._get_dem_path(**kwargs) with rasterio.open(str(self._get_tile_path())) as src: if "rpcs" in kwargs: rpcs = kwargs.pop("rpcs") else: rpcs = src.rpcs if not rpcs: raise InvalidProductError( "Your projected VHR data doesn't have any RPC. " "EOReader cannot orthorectify it!" ) out_arr, meta = self._reproject( src.read(), src.meta, rpcs, dem_path, **kwargs ) rasters_rio.write(out_arr, meta, ortho_path, tags=src.tags()) else: ortho_path = self._get_tile_path() return ortho_path
[docs] def get_band_paths( self, band_list: list, pixel_size: float = None, **kwargs ) -> dict: """ Return the paths of required bands. .. code-block:: python >>> from eoreader.reader import Reader >>> from eoreader.bands import * >>> path = r"IMG_PHR1B_PMS_001" >>> prod = Reader().open(path) >>> prod.get_band_paths([GREEN, RED]) { <SpectralBandNames.GREEN: 'GREEN'>: 'IMG_PHR1A_PMS_001/DIM_PHR1A_PMS_202005110231585_ORT_5547047101.XML', <SpectralBandNames.RED: 'RED'>: 'IMG_PHR1A_PMS_001/DIM_PHR1A_PMS_202005110231585_ORT_5547047101.XML' } Args: band_list (list): List of the wanted bands pixel_size (float): Band pixel size kwargs: Other arguments used to load bands Returns: dict: Dictionary containing the path of each queried band """ if not self.ortho_path: self.ortho_path = self._get_ortho_path(**kwargs) # Processed path names band_paths = {} for band in band_list: # Get clean band path clean_band = self._get_clean_band_path( band, pixel_size=pixel_size, **kwargs ) if clean_band.is_file(): band_paths[band] = clean_band else: # First look for reprojected bands reproj_path = self._get_utm_band_path( band=band.name, pixel_size=pixel_size ) if not reproj_path.is_file(): # Then for original data band_path = self.ortho_path else: band_path = reproj_path band_paths[band] = band_path return band_paths
def _get_dem_path(self, **kwargs) -> str: """ Get DEM path Returns: str: DEM path """ # Get DEM path dem_path = os.environ.get(DEM_PATH, kwargs.get(DEM_KW)) if not dem_path: raise ValueError( f"As you are using a non orthorectified VHR product ({self.path}), " f"you must provide a valid DEM through the {DEM_PATH} environment variable" ) else: if path.is_cloud_path(dem_path): raise ValueError( "gdalwarp cannot process DEM stored on cloud with 'RPC_DEM' argument, " "hence cloud-stored DEM cannot be used with non orthorectified DIMAP data." f"(DEM: {dem_path}, DIMAP data: {self.name})" ) return dem_path def _reproject( self, src_arr: np.ndarray, src_meta: dict, rpcs: rpc.RPC, dem_path, **kwargs ) -> (np.ndarray, dict): """ Reproject using RPCs (cannot use another pixel size than src to ensure RPCs are valid) Args: src_arr (np.ndarray): Array to reproject src_meta (dict): Metadata rpcs (rpc.RPC): RPCs dem_path (str): DEM path Returns: (np.ndarray, dict): Reprojected array and its metadata """ # Set RPC keywords LOGGER.debug(f"Orthorectifying data with {dem_path}") kwargs = { "RPC_DEM": dem_path, "RPC_DEM_MISSING_VALUE": 0, "OSR_USE_ETMERC": "YES", "BIGTIFF": "IF_NEEDED", } # Reproject # WARNING: may not give correct output pixel size out_arr, dst_transform = warp.reproject( src_arr, rpcs=rpcs, src_crs=self._get_raw_crs(), src_nodata=self._raw_nodata, dst_crs=self.crs(), dst_resolution=self.pixel_size, dst_nodata=self._raw_nodata, # input data should be in integer num_threads=MAX_CORES, resampling=Resampling.bilinear, **kwargs, ) # Get dims count, height, width = out_arr.shape # Update metadata meta = src_meta.copy() meta["transform"] = dst_transform meta["driver"] = "GTiff" meta["compress"] = "lzw" meta["nodata"] = self._raw_nodata meta["crs"] = self.crs() meta["width"] = width meta["height"] = height meta["count"] = count return out_arr, meta def _read_band( self, band_path: AnyPathType, band: BandNames = None, pixel_size: Union[tuple, list, float] = None, size: Union[list, tuple] = None, **kwargs, ) -> xr.DataArray: """ Read band from disk. .. WARNING:: Invalid pixels are not managed here Args: band_path (AnyPathType): Band path band (BandNames): Band to read pixel_size (Union[tuple, list, float]): Size of the pixels of the wanted band, in dataset unit (X, Y) size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided. kwargs: Other arguments used to load bands Returns: xr.DataArray: Band xarray """ with rasterio.open(str(band_path)) as dst: dst_crs = dst.crs # Compute pixel_size from size (if needed) if pixel_size is None and size is not None: pixel_size = self._pixel_size_from_img_size(size) # Reproj path in case reproj_path = self._get_utm_band_path(band=band.name, pixel_size=pixel_size) # Manage the case if we got a LAT LON product if not dst_crs.is_projected: if not reproj_path.is_file(): reproj_path = self._get_utm_band_path( band=band.name, pixel_size=pixel_size, writable=True ) # Warp band if needed self._warp_band( band_path, reproj_path=reproj_path, pixel_size=pixel_size, ) # Read band LOGGER.debug(f"Reading warped {band.name}.") band_arr = utils.read( reproj_path, pixel_size=pixel_size, size=size, resampling=Resampling.bilinear, indexes=[self.bands[band].id], **kwargs, ) # Manage the case if we open a simple band (EOReader processed bands) elif dst.count == 1: # Read band band_arr = utils.read( band_path, pixel_size=pixel_size, size=size, resampling=Resampling.bilinear, **kwargs, ) # Manage the case if we open a stack (native DIMAP bands) else: # Read band band_arr = utils.read( band_path, pixel_size=pixel_size, size=size, resampling=Resampling.bilinear, indexes=[self.bands[band].id], **kwargs, ) # Pop useless long name if "long_name" in band_arr.attrs: band_arr.attrs.pop("long_name") return band_arr def _load_bands( self, bands: list, pixel_size: float = None, size: Union[list, tuple] = None, **kwargs, ) -> dict: """ Load bands as numpy arrays with the same pixel size (and same metadata). Args: bands list: List of the wanted bands pixel_size (float): Band pixel size in meters size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided. kwargs: Other arguments used to load bands Returns: dict: Dictionary {band_name, band_xarray} """ # Return empty if no band are specified if not bands: return {} # Get band paths if pixel_size is None and size is not None: pixel_size = self._pixel_size_from_img_size(size) band_paths = self.get_band_paths(bands, pixel_size=pixel_size, **kwargs) # Open bands and get array (resampled if needed) band_arrays = self._open_bands( band_paths, pixel_size=pixel_size, size=size, **kwargs ) return band_arrays def _manage_invalid_pixels( self, band_arr: xr.DataArray, band: BandNames, **kwargs ) -> xr.DataArray: """ Manage invalid pixels (Nodata, saturated, defective...) Args: band_arr (xr.DataArray): Band array band (BandNames): Band name as an SpectralBandNames kwargs: Other arguments used to load bands Returns: xr.DataArray: Cleaned band array """ return self._manage_nodata(band_arr, band, **kwargs) def _manage_nodata( self, band_arr: xr.DataArray, band: BandNames, **kwargs ) -> xr.DataArray: """ Manage only nodata pixels Args: band_arr (xr.DataArray): Band array band (BandNames): Band name as an SpectralBandNames kwargs: Other arguments used to load bands Returns: xr.DataArray: Cleaned band array """ # If nodata not set, set it here if not band_arr.rio.encoded_nodata: band_arr = rasters.set_nodata(band_arr, self._raw_nodata) return band_arr def _get_condensed_name(self) -> str: """ Get PlanetScope products condensed name ({date}_PLD_{product_type}_{band_combi}). Returns: str: Condensed name """ return f"{self.get_datetime()}_{self.constellation.name}_{self.product_type.name}_{self.band_combi.name}_{self._job_id}" def _get_path(self, filename: str = "", extension: str = "") -> AnyPathType: """ Get either the archived path of the normal path of an asset Args: filename (str): Filename with wildcards extension (str): Extension Returns: Union[list, AnyPathType]: Path or list of paths (needs this because of potential mosaic) """ prod_path = [] try: if filename and not filename.startswith("*"): filename = f"*{filename}" if self.is_archived: prod_path = path.get_archived_rio_path( self.path, rf".{filename}.*\.{extension}", ) else: prod_path = next(self.path.glob(f"{filename}*.{extension}")) except (FileNotFoundError, IndexError): LOGGER.warning( f"No file corresponding to *{filename}*.{extension} found in {self.path}" ) return prod_path def _get_utm_band_path( self, band: str, pixel_size: Union[float, tuple, list] = None, writable: bool = False, ) -> AnyPathType: """ Create the UTM band path Args: band (str): Band in string as written on the filepath pixel_size (Union[float, tuple, list]): Pixel size of the wanted UTM band writable (bool): Do we need to write the UTM band ? Returns: AnyPathType: UTM band path """ res_str = self._pixel_size_to_str(pixel_size) return self._get_band_folder(writable).joinpath( f"{self.condensed_name}_{band}_{res_str}.vrt" ) def _warp_band( self, band_path: AnyPathStrType, reproj_path: AnyPathStrType, pixel_size: float = None, ) -> None: """ Warp band to UTM Args: band_path (AnyPathStrType): Band path to warp reproj_path (AnyPathStrType): Path where to write the reprojected band pixel_size (int): Band pixel size in meters """ # Do not warp if existing file if reproj_path.is_file(): return if not pixel_size: pixel_size = self.pixel_size LOGGER.info( f"Warping {path.get_filename(band_path)} to UTM with a {pixel_size} m pixel size." ) # Read band with rasterio.open(str(band_path)) as src: # Calculate transform utm_tr, utm_w, utm_h = warp.calculate_default_transform( src.crs, self.crs(), src.width, src.height, *src.bounds, resolution=pixel_size, ) vrt_options = { "crs": self.crs(), "transform": utm_tr, "height": utm_h, "width": utm_w, # TODO: go nearest to speed up results ? "resampling": Resampling.bilinear, "nodata": self._raw_nodata, # Float32 is the max possible "warp_mem_limit": 32 * int(os.getenv(TILE_SIZE, DEFAULT_TILE_SIZE)) ** 2 / 1e6, "dtype": src.meta["dtype"], "num_threads": MAX_CORES, } with rasterio.Env( **{"GDAL_NUM_THREADS": "ALL_CPUS", "NUM_THREADS": "ALL_CPUS"} ): with WarpedVRT(src, **vrt_options) as vrt: rio_shutil.copy(vrt, reproj_path, driver="vrt") def _get_default_utm_band( self, pixel_size: float = None, size: Union[list, tuple] = None ) -> AnyPathType: """ Get the default UTM band: - If one already exists, get it - If not, create reproject (if needed) the GREEN band Args: pixel_size (int): Band pixel size in meters size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided. Returns: str: Default UTM path """ # Manage pixel_size if pixel_size is None and size is not None: pixel_size = self._pixel_size_from_img_size(size) def_res = pixel_size if pixel_size else self.pixel_size # Get default band path default_band = self.get_default_band() def_path = self.get_band_paths([default_band], pixel_size=def_res)[default_band] # First look for reprojected bands res_str = self._pixel_size_to_str(pixel_size) warped_regex = f"*{self.condensed_name}_*_{res_str}.tif" reproj_bands = list(self._get_band_folder().glob(warped_regex)) if len(reproj_bands) == 0: # Check in the writeable band folder reproj_bands = list(self._get_band_folder(writable=True).glob(warped_regex)) if len(reproj_bands) == 0: # Manage the case if we got a LAT LON product with rasterio.open(str(def_path)) as dst: dst_crs = dst.crs if not dst_crs.is_projected: def_band = self.get_default_band() utm_path = self._get_utm_band_path( band=def_band.name, pixel_size=pixel_size ) # Warp band if needed if not utm_path.is_file(): utm_path = self._get_utm_band_path( band=def_band.name, pixel_size=pixel_size, writable=True ) self._warp_band( def_path, reproj_path=utm_path, pixel_size=pixel_size, ) else: utm_path = def_path else: utm_path = AnyPath(reproj_bands[0]) else: utm_path = AnyPath(reproj_bands[0]) return utm_path
[docs] def default_transform(self, **kwargs) -> (affine.Affine, int, int, CRS): """ Returns default transform data of the default band (UTM), as the :code:`rasterio.warp.calculate_default_transform` does: - transform - width - height - CRS Overload in order not to reproject WGS84 data Args: kwargs: Additional arguments Returns: Affine, int, int, CRS: transform, width, height, CRS """ default_band = self.get_default_band() def_path = self.get_band_paths( [default_band], pixel_size=self.pixel_size, **kwargs )[default_band] with rasterio.open(str(def_path)) as dst: return dst.transform, dst.width, dst.height, dst.crs
@abstractmethod def _get_tile_path(self) -> AnyPathType: """ Get the VHR tile path Returns: AnyPathType: VHR filepath """ raise NotImplementedError @abstractmethod def _get_job_id(self) -> AnyPathType: """ Get VHR job ID Returns: AnyPathType: VHR product ID """ raise NotImplementedError
[docs] def get_raw_band_paths(self, **kwargs) -> dict: """ Return the raw band paths. Args: kwargs: Additional arguments Returns: dict: Dictionary containing the path of each queried band """ raw_band_paths = {} for band in self.get_existing_bands(): raw_band_paths[band] = self._get_tile_path() return raw_band_paths