Ejemplo n.º 1
0
    def process(self, args, outputs):
        tree = outputs['tree']
        reconstruction = outputs['reconstruction']
        verbose = '-verbose' if args.verbose else ''

        # define paths and create working directories
        system.mkdir_p(tree.odm_orthophoto)

        if not io.file_exists(tree.odm_orthophoto_file) or self.rerun():

            # odm_orthophoto definitions
            kwargs = {
                'bin': context.odm_modules_path,
                'log': tree.odm_orthophoto_log,
                'ortho': tree.odm_orthophoto_file,
                'corners': tree.odm_orthophoto_corners,
                'res': 1.0 / (gsd.cap_resolution(args.orthophoto_resolution, tree.opensfm_reconstruction, ignore_gsd=args.ignore_gsd) / 100.0),
                'verbose': verbose
            }

            # Have geo coordinates?
            georef = reconstruction.georef

            # Check if the georef object is initialized
            # (during a --rerun this might not be)
            # TODO: this should be moved to a more central location?
            if reconstruction.is_georeferenced() and not reconstruction.georef.valid_utm_offsets():
                georeferencing_dir = tree.odm_georeferencing if args.use_3dmesh and not args.skip_3dmodel else tree.odm_25dgeoreferencing
                odm_georeferencing_model_txt_geo_file = os.path.join(georeferencing_dir, tree.odm_georeferencing_model_txt_geo)

                if io.file_exists(odm_georeferencing_model_txt_geo_file):
                    reconstruction.georef.extract_offsets(odm_georeferencing_model_txt_geo_file)
                else:
                    log.ODM_WARNING('Cannot read UTM offset from {}. An orthophoto will not be generated.'.format(odm_georeferencing_model_txt_geo_file))

            if reconstruction.is_georeferenced():
                if args.use_3dmesh:
                    kwargs['model_geo'] = os.path.join(tree.odm_texturing, tree.odm_georeferencing_model_obj_geo)
                else:
                    kwargs['model_geo'] = os.path.join(tree.odm_25dtexturing, tree.odm_georeferencing_model_obj_geo)
            else:
                if args.use_3dmesh:
                    kwargs['model_geo'] = os.path.join(tree.odm_texturing, tree.odm_textured_model_obj)
                else:
                    kwargs['model_geo'] = os.path.join(tree.odm_25dtexturing, tree.odm_textured_model_obj)

            # run odm_orthophoto
            system.run('{bin}/odm_orthophoto -inputFile {model_geo} '
                       '-logFile {log} -outputFile {ortho} -resolution {res} {verbose} '
                       '-outputCornerFile {corners}'.format(**kwargs))

            # Create georeferenced GeoTiff
            geotiffcreated = False

            if reconstruction.is_georeferenced() and reconstruction.georef.valid_utm_offsets():
                ulx = uly = lrx = lry = 0.0
                with open(tree.odm_orthophoto_corners) as f:
                    for lineNumber, line in enumerate(f):
                        if lineNumber == 0:
                            tokens = line.split(' ')
                            if len(tokens) == 4:
                                ulx = float(tokens[0]) + \
                                    float(reconstruction.georef.utm_east_offset)
                                lry = float(tokens[1]) + \
                                    float(reconstruction.georef.utm_north_offset)
                                lrx = float(tokens[2]) + \
                                    float(reconstruction.georef.utm_east_offset)
                                uly = float(tokens[3]) + \
                                    float(reconstruction.georef.utm_north_offset)
                log.ODM_INFO('Creating GeoTIFF')

                orthophoto_vars = orthophoto.get_orthophoto_vars(args)

                kwargs = {
                    'ulx': ulx,
                    'uly': uly,
                    'lrx': lrx,
                    'lry': lry,
                    'vars': ' '.join(['-co %s=%s' % (k, orthophoto_vars[k]) for k in orthophoto_vars]),
                    'proj': reconstruction.georef.proj4(),
                    'png': tree.odm_orthophoto_file,
                    'tiff': tree.odm_orthophoto_tif,
                    'log': tree.odm_orthophoto_tif_log,
                    'max_memory': get_max_memory(),
                }

                system.run('gdal_translate -a_ullr {ulx} {uly} {lrx} {lry} '
                           '{vars} '
                           '-a_srs \"{proj}\" '
                           '--config GDAL_CACHEMAX {max_memory}% '
                           '{png} {tiff} > {log}'.format(**kwargs))

                bounds_file_path = os.path.join(tree.odm_georeferencing, 'odm_georeferenced_model.bounds.gpkg')
                    
                # Cutline computation, before cropping
                # We want to use the full orthophoto, not the cropped one.
                if args.orthophoto_cutline:
                    compute_cutline(tree.odm_orthophoto_tif, 
                                    bounds_file_path,
                                    os.path.join(tree.odm_orthophoto, "cutline.gpkg"),
                                    args.max_concurrency,
                                    tmpdir=os.path.join(tree.odm_orthophoto, "grass_cutline_tmpdir"),
                                    scale=0.25)

                if args.crop > 0:
                    Cropper.crop(bounds_file_path, tree.odm_orthophoto_tif, orthophoto_vars)

                if args.build_overviews:
                    orthophoto.build_overviews(tree.odm_orthophoto_tif)

                geotiffcreated = True
            if not geotiffcreated:
                log.ODM_WARNING('No geo-referenced orthophoto created due '
                                'to missing geo-referencing or corner coordinates.')

        else:
            log.ODM_WARNING('Found a valid orthophoto in: %s' % tree.odm_orthophoto_file)
Ejemplo n.º 2
0
    def process(self, args, outputs):
        tree = outputs['tree']
        reconstruction = outputs['reconstruction']

        if outputs['large']:
            if not os.path.exists(tree.submodels_path):
                log.ODM_ERROR(
                    "We reached the merge stage, but %s folder does not exist. Something must have gone wrong at an earlier stage. Check the log and fix possible problem before restarting?"
                    % tree.submodels_path)
                exit(1)

            # Merge point clouds
            if args.merge in ['all', 'pointcloud']:
                if not io.file_exists(
                        tree.odm_georeferencing_model_laz) or self.rerun():
                    all_point_clouds = get_submodel_paths(
                        tree.submodels_path, "odm_georeferencing",
                        "odm_georeferenced_model.laz")

                    try:
                        # pdal.merge_point_clouds(all_point_clouds, tree.odm_georeferencing_model_laz, args.verbose)
                        entwine.build(all_point_clouds,
                                      tree.entwine_pointcloud,
                                      max_concurrency=args.max_concurrency,
                                      rerun=self.rerun())
                    except Exception as e:
                        log.ODM_WARNING(
                            "Could not merge point cloud: %s (skipping)" %
                            str(e))

                    if io.dir_exists(tree.entwine_pointcloud):
                        try:
                            system.run('pdal translate "ept://{}" "{}"'.format(
                                tree.entwine_pointcloud,
                                tree.odm_georeferencing_model_laz))
                        except Exception as e:
                            log.ODM_WARNING(
                                "Cannot export EPT dataset to LAZ: %s" %
                                str(e))
                else:
                    log.ODM_WARNING("Found merged point cloud in %s" %
                                    tree.odm_georeferencing_model_laz)

            self.update_progress(25)

            # Merge crop bounds
            merged_bounds_file = os.path.join(
                tree.odm_georeferencing, 'odm_georeferenced_model.bounds.gpkg')
            if not io.file_exists(merged_bounds_file) or self.rerun():
                all_bounds = get_submodel_paths(
                    tree.submodels_path, 'odm_georeferencing',
                    'odm_georeferenced_model.bounds.gpkg')
                log.ODM_INFO("Merging all crop bounds: %s" % all_bounds)
                if len(all_bounds) > 0:
                    # Calculate a new crop area
                    # based on the convex hull of all crop areas of all submodels
                    # (without a buffer, otherwise we are double-cropping)
                    Cropper.merge_bounds(all_bounds, merged_bounds_file, 0)
                else:
                    log.ODM_WARNING("No bounds found for any submodel.")

            # Merge orthophotos
            if args.merge in ['all', 'orthophoto']:
                if not io.dir_exists(tree.odm_orthophoto):
                    system.mkdir_p(tree.odm_orthophoto)

                if not io.file_exists(tree.odm_orthophoto_tif) or self.rerun():
                    all_orthos_and_cutlines = get_all_submodel_paths(
                        tree.submodels_path,
                        os.path.join("odm_orthophoto", "odm_orthophoto.tif"),
                        os.path.join("odm_orthophoto", "cutline.gpkg"),
                    )

                    if len(all_orthos_and_cutlines) > 1:
                        log.ODM_INFO(
                            "Found %s submodels with valid orthophotos and cutlines"
                            % len(all_orthos_and_cutlines))

                        # TODO: histogram matching via rasterio
                        # currently parts have different color tones

                        merged_geotiff = os.path.join(
                            tree.odm_orthophoto, "odm_orthophoto.merged.tif")

                        kwargs = {
                            'orthophoto_merged':
                            merged_geotiff,
                            'input_files':
                            ' '.join(
                                map(lambda i: quote(i[0]),
                                    all_orthos_and_cutlines)),
                            'max_memory':
                            get_max_memory(),
                            'threads':
                            args.max_concurrency,
                        }

                        # use bounds as cutlines (blending)
                        if io.file_exists(merged_geotiff):
                            os.remove(merged_geotiff)

                        system.run('gdal_merge.py -o {orthophoto_merged} '
                                   #'-createonly '
                                   '-co "BIGTIFF=YES" '
                                   '-co "BLOCKXSIZE=512" '
                                   '-co "BLOCKYSIZE=512" '
                                   '--config GDAL_CACHEMAX {max_memory}% '
                                   '{input_files} '.format(**kwargs))

                        for ortho_cutline in all_orthos_and_cutlines:
                            kwargs['input_file'], kwargs[
                                'cutline'] = ortho_cutline

                            # Note: cblend has a high performance penalty
                            system.run(
                                'gdalwarp -cutline {cutline} '
                                '-cblend 20 '
                                '-r bilinear -multi '
                                '-wo NUM_THREADS={threads} '
                                '--config GDAL_CACHEMAX {max_memory}% '
                                '{input_file} {orthophoto_merged}'.format(
                                    **kwargs))

                        # Apply orthophoto settings (compression, tiling, etc.)
                        orthophoto_vars = orthophoto.get_orthophoto_vars(args)

                        if io.file_exists(tree.odm_orthophoto_tif):
                            os.remove(tree.odm_orthophoto_tif)

                        kwargs = {
                            'vars':
                            ' '.join([
                                '-co %s=%s' % (k, orthophoto_vars[k])
                                for k in orthophoto_vars
                            ]),
                            'max_memory':
                            get_max_memory(),
                            'merged':
                            merged_geotiff,
                            'log':
                            tree.odm_orthophoto_tif_log,
                            'orthophoto':
                            tree.odm_orthophoto_tif,
                        }

                        system.run(
                            'gdal_translate '
                            '{vars} '
                            '--config GDAL_CACHEMAX {max_memory}% '
                            '{merged} {orthophoto} > {log}'.format(**kwargs))

                        os.remove(merged_geotiff)

                        # Crop
                        if args.crop > 0:
                            Cropper.crop(merged_bounds_file,
                                         tree.odm_orthophoto_tif,
                                         orthophoto_vars)

                        # Overviews
                        if args.build_overviews:
                            orthophoto.build_overviews(tree.odm_orthophoto_tif)

                    elif len(all_orthos_and_cutlines) == 1:
                        # Simply copy
                        log.ODM_WARNING(
                            "A single orthophoto/cutline pair was found between all submodels."
                        )
                        shutil.copyfile(all_orthos_and_cutlines[0][0],
                                        tree.odm_orthophoto_tif)
                    else:
                        log.ODM_WARNING(
                            "No orthophoto/cutline pairs were found in any of the submodels. No orthophoto will be generated."
                        )
                else:
                    log.ODM_WARNING("Found merged orthophoto in %s" %
                                    tree.odm_orthophoto_tif)

            self.update_progress(75)

            # Merge DEMs
            def merge_dems(dem_filename, human_name):
                if not io.dir_exists(tree.path('odm_dem')):
                    system.mkdir_p(tree.path('odm_dem'))

                dem_file = tree.path("odm_dem", dem_filename)
                if not io.file_exists(dem_file) or self.rerun():
                    all_dems = get_submodel_paths(tree.submodels_path,
                                                  "odm_dem", dem_filename)
                    log.ODM_INFO("Merging %ss" % human_name)

                    # Merge
                    dem_vars = utils.get_dem_vars(args)
                    euclidean_merge_dems(all_dems, dem_file, dem_vars)

                    if io.file_exists(dem_file):
                        # Crop
                        if args.crop > 0:
                            Cropper.crop(merged_bounds_file, dem_file,
                                         dem_vars)
                        log.ODM_INFO("Created %s" % dem_file)
                    else:
                        log.ODM_WARNING("Cannot merge %s, %s was not created" %
                                        (human_name, dem_file))
                else:
                    log.ODM_WARNING("Found merged %s in %s" %
                                    (human_name, dem_filename))

            if args.merge in ['all', 'dem'] and args.dsm:
                merge_dems("dsm.tif", "DSM")

            if args.merge in ['all', 'dem'] and args.dtm:
                merge_dems("dtm.tif", "DTM")

            # Stop the pipeline short! We're done.
            self.next_stage = None
        else:
            log.ODM_INFO("Normal dataset, nothing to merge.")
            self.progress = 0.0