OpenDroneMap-ODM/stages/dataset.py

import os
import json

from opendm import context
from opendm import io
from opendm import types
from opendm import log
from opendm import system
from opendm.geo import GeoFile
from shutil import copyfile
from opendm import progress
from opendm import boundary

def save_images_database(photos, database_file):
    with open(database_file, 'w') as f:
        f.write(json.dumps([p.__dict__ for p in photos]))
    
    log.ODM_INFO("Wrote images database: %s" % database_file)

def load_images_database(database_file):
    # Empty is used to create types.ODM_Photo class
    # instances without calling __init__
    class Empty:
        pass

    result = []

    log.ODM_INFO("Loading images database: %s" % database_file)

    with open(database_file, 'r') as f:
        photos_json = json.load(f)
        for photo_json in photos_json:
            p = Empty()
            for k in photo_json:
                setattr(p, k, photo_json[k])
            p.__class__ = types.ODM_Photo
            result.append(p)

    return result

class ODMLoadDatasetStage(types.ODM_Stage):
    def process(self, args, outputs):
        outputs['start_time'] = system.now_raw()
        tree = types.ODM_Tree(args.project_path, args.gcp, args.geo)
        outputs['tree'] = tree

        if args.time and io.file_exists(tree.benchmarking):
            # Delete the previously made file
            os.remove(tree.benchmarking)
            with open(tree.benchmarking, 'a') as b:
                b.write('ODM Benchmarking file created %s\nNumber of Cores: %s\n\n' % (system.now(), context.num_cores))
    
        # check if the image filename is supported
        def valid_image_filename(filename):
            (pathfn, ext) = os.path.splitext(filename)
            return ext.lower() in context.supported_extensions and pathfn[-5:] != "_mask"

        # Get supported images from dir
        def get_images(in_dir):
            log.ODM_DEBUG(in_dir)
            entries = os.listdir(in_dir)
            valid, rejects = [], []
            for f in entries:
                if valid_image_filename(f):
                    valid.append(f)
                else:
                    rejects.append(f)
            return valid, rejects

        def find_mask(photo_path, masks):
            (pathfn, ext) = os.path.splitext(os.path.basename(photo_path))
            k = "{}_mask".format(pathfn)
            
            mask = masks.get(k)
            if mask:
                # Spaces are not supported due to OpenSfM's mask_list.txt format reqs
                if not " " in mask:
                    return mask
                else:
                    log.ODM_WARNING("Image mask {} has a space. Spaces are currently not supported for image masks.".format(mask))

        # get images directory
        images_dir = tree.dataset_raw

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

        log.ODM_INFO('Loading dataset from: %s' % images_dir)

        # check if we rerun cell or not
        images_database_file = os.path.join(tree.root_path, 'images.json')
        if not io.file_exists(images_database_file) or self.rerun():
            if not os.path.exists(images_dir):
                raise system.ExitException("There are no images in %s! Make sure that your project path and dataset name is correct. The current is set to: %s" % (images_dir, args.project_path))

            files, rejects = get_images(images_dir)
            if files:
                # create ODMPhoto list
                path_files = [os.path.join(images_dir, f) for f in files]

                # Lookup table for masks
                masks = {}
                for r in rejects:
                    (p, ext) = os.path.splitext(r)
                    if p[-5:] == "_mask" and ext.lower() in context.supported_extensions:
                        masks[p] = r

                photos = []
                with open(tree.dataset_list, 'w') as dataset_list:
                    log.ODM_INFO("Loading %s images" % len(path_files))
                    for f in path_files:
                        p = types.ODM_Photo(f)
                        p.set_mask(find_mask(f, masks))
                        photos += [p]
                        dataset_list.write(photos[-1].filename + '\n')
                
                # Check if a geo file is available
                if tree.odm_geo_file is not None and os.path.exists(tree.odm_geo_file):
                    log.ODM_INFO("Found image geolocation file")
                    gf = GeoFile(tree.odm_geo_file)
                    updated = 0
                    for p in photos:
                        entry = gf.get_entry(p.filename)
                        if entry:
                            p.update_with_geo_entry(entry)
                            updated += 1
                    log.ODM_INFO("Updated %s image positions" % updated)

                # Save image database for faster restart
                save_images_database(photos, images_database_file)
            else:
                raise system.ExitException('Not enough supported images in %s' % images_dir)
        else:
            # We have an images database, just load it
            photos = load_images_database(images_database_file)

        log.ODM_INFO('Found %s usable images' % len(photos))
        log.logger.log_json_images(len(photos))

        # Create reconstruction object
        reconstruction = types.ODM_Reconstruction(photos)
        
        if tree.odm_georeferencing_gcp and not args.use_exif:
            reconstruction.georeference_with_gcp(tree.odm_georeferencing_gcp,
                                                 tree.odm_georeferencing_coords,
                                                 tree.odm_georeferencing_gcp_utm,
                                                 tree.odm_georeferencing_model_txt_geo,
                                                 rerun=self.rerun())
        else:
            reconstruction.georeference_with_gps(tree.dataset_raw, 
                                                 tree.odm_georeferencing_coords, 
                                                 tree.odm_georeferencing_model_txt_geo,
                                                 rerun=self.rerun())
        
        reconstruction.save_proj_srs(os.path.join(tree.odm_georeferencing, tree.odm_georeferencing_proj))
        outputs['reconstruction'] = reconstruction

        # Try to load boundaries
        if args.boundary:
            if reconstruction.is_georeferenced():
                outputs['boundary'] = boundary.load_boundary(args.boundary, reconstruction.get_proj_srs())
            else:
                args.boundary = None
                log.ODM_WARNING("Reconstruction is not georeferenced, but boundary file provided (will ignore boundary file)")