def test_init(self): # test bare minimum sensor = kapture.Sensor('unknown', []) self.assertEqual(sensor.name, None) self.assertEqual(sensor.sensor_type, 'unknown') self.assertListEqual(sensor.sensor_params, []) # test typical camera sensor_name = 'GOPRO_FUSION' sensor_type = 'camera' # SIMPLE_PINHOLE, w, h, f, cx, cy sensor_params = ['SIMPLE_PINHOLE', 640, 480, 100, 320, 240] sensor = kapture.Sensor(sensor_type, sensor_params, name=sensor_name) self.assertEqual(sensor.name, sensor_name) self.assertEqual(sensor.sensor_type, sensor_type) self.assertListEqual(sensor.sensor_params, [i for i in sensor_params]) self.assertIsInstance(sensor.__repr__(), str) sensor = kapture.Camera(sensor_params[0], sensor_params[1:], name=sensor_name) self.assertEqual(sensor.name, sensor_name) self.assertEqual(sensor.sensor_type, sensor_type) self.assertEqual(sensor.camera_type, kapture.CameraType.SIMPLE_PINHOLE) self.assertListEqual(sensor.sensor_params, [str(i) for i in sensor_params]) self.assertListEqual(sensor.camera_params, [float(i) for i in sensor_params[1:]]) self.assertIsInstance(sensor.__repr__(), str)
def test_init(self): lidar0 = kapture.Sensor('lidar', []) cam0 = kapture.Sensor('camera', []) sensors = kapture.Sensors() sensors['cam0'] = cam0 kapture_data = kapture.Kapture(sensors=sensors) self.assertEqual(sensors, kapture_data.sensors) self.assertEqual(sensors['cam0'], kapture_data.sensors['cam0']) # assign sensors = kapture_data.sensors self.assertIsInstance(sensors, kapture.Sensors) kapture_data.sensors = sensors kapture_data.sensors['lidar0'] = lidar0
def test_init(self): sensors = kapture.Sensors() self.assertEqual(0, len(sensors)) sensors['cam0'] = kapture.Sensor('unknown', []) self.assertEqual(1, len(sensors)) self.assertIn('cam0', sensors) self.assertIn('unknown', sensors['cam0'].sensor_type)
def test_type_checking(self): sensors = kapture.Sensors() invalid_sensor_id = tuple('a', ) valid_sensor_id = 'cam0' invalid_sensor = int(0) valid_sensor = kapture.Sensor('camera') self.assertRaises(TypeError, sensors.__setitem__, valid_sensor_id, invalid_sensor) self.assertRaises(TypeError, sensors.__setitem__, invalid_sensor_id, valid_sensor) self.assertRaises(TypeError, sensors.__setitem__, invalid_sensor_id, invalid_sensor)
def _import_gnss(opensfm_root_dir, kapture_sensors, image_sensors, image_timestamps, disable_tqdm) \ -> Optional[kapture.RecordsGnss]: """ Imports the GNSS info from the images exif. """ # gps from pre-extracted exif, in exif/image_name.jpg.exif kapture_gnss = None opensfm_exif_dir_path = path.join(opensfm_root_dir, 'exif') opensfm_exif_suffix = '.exif' if path.isdir(opensfm_exif_dir_path): logger.info('importing GNSS from exif ...') camera_ids = set(image_sensors.values()) # add a gps sensor for each camera map_cam_to_gnss_sensor = { cam_id: 'GPS_' + cam_id for cam_id in camera_ids } for gnss_id in map_cam_to_gnss_sensor.values(): kapture_sensors[gnss_id] = kapture.Sensor( sensor_type='gnss', sensor_params=['EPSG:4326']) # build epsg_code for all cameras kapture_gnss = kapture.RecordsGnss() opensfm_exif_filepath_list = ( path.join(dir_path, filename) for dir_path, _, filename_list in os.walk(opensfm_exif_dir_path) for filename in filename_list if filename.endswith(opensfm_exif_suffix)) for opensfm_exif_filepath in tqdm(opensfm_exif_filepath_list, disable=disable_tqdm): image_filename = path.relpath( opensfm_exif_filepath, opensfm_exif_dir_path)[:-len(opensfm_exif_suffix)] image_timestamp = image_timestamps[image_filename] image_sensor_id = image_sensors[image_filename] gnss_timestamp = image_timestamp gnss_sensor_id = map_cam_to_gnss_sensor[image_sensor_id] with open(opensfm_exif_filepath, 'rt') as f: js_root = json.load(f) if 'gps' not in js_root: logger.warning(f'NO GPS data in "{opensfm_exif_filepath}"') continue gps_coords = { 'x': js_root['gps']['longitude'], 'y': js_root['gps']['latitude'], 'z': js_root['gps'].get('altitude', 0.0), 'dop': js_root['gps'].get('dop', 0), 'utc': 0, } logger.debug( f'found GPS data for ({gnss_timestamp}, {gnss_sensor_id}) in "{opensfm_exif_filepath}"' ) kapture_gnss[gnss_timestamp, gnss_sensor_id] = kapture.RecordGnss(**gps_coords) return kapture_gnss
def test_as_dict(self): kapture_data = kapture.Kapture() # test empty members = kapture_data.as_dict() self.assertEqual(members, {}) members = kapture_data.as_dict(keep_none=True) self.assertEqual(len(members), 18) self.assertTrue(all(member is None for member in members.values())) # test sensors only kapture_data.sensors = kapture.Sensors({'cam0': kapture.Sensor('camera', [])}) members = kapture_data.as_dict() self.assertEqual(len(members), 1) self.assertEqual(members, {'sensors': kapture_data.sensors}) members = kapture_data.as_dict(keep_none=True) self.assertEqual(len(members), 18) self.assertEqual(members['sensors'], kapture_data.sensors) self.assertTrue(all(member is None for name, member in members.items() if name != 'sensors'))
def extract_gps_from_exif(kapture_data: kapture.Kapture, kapture_dirpath: str): """ Extract GPS coordinates from kapture dataset, returns the new sensor and gnss records. Gnss timestamps and sensor ids are guessed from timestamps and camera_id from images. The GNSS sensor_id are built prefixing 'GPS_'<cam_id>, with cam_id the sensor_id of the corresponding camera. :param kapture_data: input kapture data, must contains sensors and records_camera. :param kapture_dirpath: input path to kapture directory. :return: """ # only load sensors + records_data: disable_tqdm = logger.getEffectiveLevel() != logging.INFO # make up new gps ids cam_to_gps_id = { # cam_id -> gps_id cam_id: 'GPS_' + cam_id for cam_id, sensor in kapture_data.sensors.items() if sensor.sensor_type == 'camera' } # cam_id -> gps_id # set all gps to EPSG:4326 gps_epsg_codes = {gps_id: 'EPSG:4326' for gps_id in cam_to_gps_id.values()} # add new gps ids to sensors gnss_kapture_sensors = kapture.Sensors() for gps_id, epsg in gps_epsg_codes.items(): gnss_kapture_sensors[gps_id] = kapture.Sensor(sensor_type='gnss', sensor_params=[epsg]) image_filepaths = images_to_filepaths(kapture_data.records_camera, kapture_dirpath=kapture_dirpath) records_gnss = kapture.RecordsGnss() for timestamp, cam_id, image_name in tqdm(kapture.flatten( kapture_data.records_camera), disable=disable_tqdm): image_filepath = image_filepaths[image_name] logger.debug(f'extracting GPS tags from {image_filepath}') gps_id = cam_to_gps_id[cam_id] exif_data = read_exif(image_filepath) gps_record = convert_gps_to_kapture_record(exif_data) records_gnss[timestamp, gps_id] = gps_record return gnss_kapture_sensors, records_gnss
def test_update(self): sensor = kapture.Sensor('unknown', [])
def import_opensfm( opensfm_rootdir: str, kapture_rootdir: str, force_overwrite_existing: bool = False, images_import_method: TransferAction = TransferAction.copy) -> None: disable_tqdm = logger.getEffectiveLevel() != logging.INFO # load reconstruction opensfm_reconstruction_filepath = path.join(opensfm_rootdir, 'reconstruction.json') with open(opensfm_reconstruction_filepath, 'rt') as f: opensfm_reconstruction = json.load(f) # remove the single list @ root opensfm_reconstruction = opensfm_reconstruction[0] # prepare space for output os.makedirs(kapture_rootdir, exist_ok=True) delete_existing_kapture_files(kapture_rootdir, force_erase=force_overwrite_existing) # import cameras kapture_sensors = kapture.Sensors() assert 'cameras' in opensfm_reconstruction # import cameras for osfm_camera_id, osfm_camera in opensfm_reconstruction['cameras'].items( ): camera = import_camera(osfm_camera, name=osfm_camera_id) kapture_sensors[osfm_camera_id] = camera # import shots logger.info('importing images and trajectories ...') kapture_images = kapture.RecordsCamera() kapture_trajectories = kapture.Trajectories() opensfm_image_dirpath = path.join(opensfm_rootdir, 'images') assert 'shots' in opensfm_reconstruction image_timestamps, image_sensors = {}, { } # used later to retrieve the timestamp of an image. for timestamp, (image_filename, shot) in enumerate( opensfm_reconstruction['shots'].items()): sensor_id = shot['camera'] image_timestamps[image_filename] = timestamp image_sensors[image_filename] = sensor_id # in OpenSfm, (sensor, timestamp) is not unique. rotation_vector = shot['rotation'] q = quaternion.from_rotation_vector(rotation_vector) translation = shot['translation'] # capture_time = shot['capture_time'] # may be invalid # gps_position = shot['gps_position'] kapture_images[timestamp, sensor_id] = image_filename kapture_trajectories[timestamp, sensor_id] = kapture.PoseTransform(r=q, t=translation) # copy image files filename_list = [f for _, _, f in kapture.flatten(kapture_images)] import_record_data_from_dir_auto( source_record_dirpath=opensfm_image_dirpath, destination_kapture_dirpath=kapture_rootdir, filename_list=filename_list, copy_strategy=images_import_method) # gps from pre-extracted exif, in exif/image_name.jpg.exif kapture_gnss = None opensfm_exif_dirpath = path.join(opensfm_rootdir, 'exif') opensfm_exif_suffix = '.exif' if path.isdir(opensfm_exif_dirpath): logger.info('importing GNSS from exif ...') camera_ids = set(image_sensors.values()) # add a gps sensor for each camera map_cam_to_gnss_sensor = { cam_id: 'GPS_' + cam_id for cam_id in camera_ids } for gnss_id in map_cam_to_gnss_sensor.values(): kapture_sensors[gnss_id] = kapture.Sensor( sensor_type='gnss', sensor_params=['EPSG:4326']) # build epsg_code for all cameras kapture_gnss = kapture.RecordsGnss() opensfm_exif_filepath_list = ( path.join(dirpath, filename) for dirpath, _, filename_list in os.walk(opensfm_exif_dirpath) for filename in filename_list if filename.endswith(opensfm_exif_suffix)) for opensfm_exif_filepath in tqdm(opensfm_exif_filepath_list, disable=disable_tqdm): image_filename = path.relpath( opensfm_exif_filepath, opensfm_exif_dirpath)[:-len(opensfm_exif_suffix)] image_timestamp = image_timestamps[image_filename] image_sensor_id = image_sensors[image_filename] gnss_timestamp = image_timestamp gnss_sensor_id = map_cam_to_gnss_sensor[image_sensor_id] with open(opensfm_exif_filepath, 'rt') as f: js_root = json.load(f) if 'gps' not in js_root: logger.warning(f'NO GPS data in "{opensfm_exif_filepath}"') continue gps_coords = { 'x': js_root['gps']['longitude'], 'y': js_root['gps']['latitude'], 'z': js_root['gps'].get('altitude', 0.0), 'dop': js_root['gps'].get('dop', 0), 'utc': 0, } logger.debug( f'found GPS data for ({gnss_timestamp}, {gnss_sensor_id}) in "{opensfm_exif_filepath}"' ) kapture_gnss[gnss_timestamp, gnss_sensor_id] = kapture.RecordGnss(**gps_coords) # import features (keypoints + descriptors) kapture_keypoints = None # kapture.Keypoints(type_name='opensfm', dsize=4, dtype=np.float64) kapture_descriptors = None # kapture.Descriptors(type_name='opensfm', dsize=128, dtype=np.uint8) opensfm_features_dirpath = path.join(opensfm_rootdir, 'features') opensfm_features_suffix = '.features.npz' if path.isdir(opensfm_features_dirpath): logger.info('importing keypoints and descriptors ...') opensfm_features_file_list = (path.join( dp, fn) for dp, _, fs in os.walk(opensfm_features_dirpath) for fn in fs) opensfm_features_file_list = ( filepath for filepath in opensfm_features_file_list if filepath.endswith(opensfm_features_suffix)) for opensfm_feature_filename in tqdm(opensfm_features_file_list, disable=disable_tqdm): image_filename = path.relpath( opensfm_feature_filename, opensfm_features_dirpath)[:-len(opensfm_features_suffix)] opensfm_image_features = np.load(opensfm_feature_filename) opensfm_image_keypoints = opensfm_image_features['points'] opensfm_image_descriptors = opensfm_image_features['descriptors'] logger.debug( f'parsing keypoints and descriptors in {opensfm_feature_filename}' ) if kapture_keypoints is None: # print(type(opensfm_image_keypoints.dtype)) # HAHOG = Hessian Affine feature point detector + HOG descriptor kapture_keypoints = kapture.Keypoints( type_name='HessianAffine', dsize=opensfm_image_keypoints.shape[1], dtype=opensfm_image_keypoints.dtype) if kapture_descriptors is None: kapture_descriptors = kapture.Descriptors( type_name='HOG', dsize=opensfm_image_descriptors.shape[1], dtype=opensfm_image_descriptors.dtype) # convert keypoints file keypoint_filpath = kapture.io.features.get_features_fullpath( data_type=kapture.Keypoints, kapture_dirpath=kapture_rootdir, image_filename=image_filename) kapture.io.features.image_keypoints_to_file( filepath=keypoint_filpath, image_keypoints=opensfm_image_keypoints) # register the file kapture_keypoints.add(image_filename) # convert descriptors file descriptor_filpath = kapture.io.features.get_features_fullpath( data_type=kapture.Descriptors, kapture_dirpath=kapture_rootdir, image_filename=image_filename) kapture.io.features.image_descriptors_to_file( filepath=descriptor_filpath, image_descriptors=opensfm_image_descriptors) # register the file kapture_descriptors.add(image_filename) # import matches kapture_matches = kapture.Matches() opensfm_matches_suffix = '_matches.pkl.gz' opensfm_matches_dirpath = path.join(opensfm_rootdir, 'matches') if path.isdir(opensfm_matches_dirpath): logger.info('importing matches ...') opensfm_matches_file_list = (path.join( dp, fn) for dp, _, fs in os.walk(opensfm_matches_dirpath) for fn in fs) opensfm_matches_file_list = ( filepath for filepath in opensfm_matches_file_list if filepath.endswith(opensfm_matches_suffix)) for opensfm_matches_filename in tqdm(opensfm_matches_file_list, disable=disable_tqdm): image_filename_1 = path.relpath( opensfm_matches_filename, opensfm_matches_dirpath)[:-len(opensfm_matches_suffix)] logger.debug(f'parsing mathes in {image_filename_1}') with gzip.open(opensfm_matches_filename, 'rb') as f: opensfm_matches = pickle.load(f) for image_filename_2, opensfm_image_matches in opensfm_matches.items( ): image_pair = (image_filename_1, image_filename_2) # register the pair to kapture kapture_matches.add(*image_pair) # convert the bin file to kapture kapture_matches_filepath = kapture.io.features.get_matches_fullpath( image_filename_pair=image_pair, kapture_dirpath=kapture_rootdir) kapture_image_matches = np.hstack([ opensfm_image_matches.astype(np.float64), # no macthes scoring = assume all to one np.ones(shape=(opensfm_image_matches.shape[0], 1), dtype=np.float64) ]) kapture.io.features.image_matches_to_file( kapture_matches_filepath, kapture_image_matches) # import 3-D points if 'points' in opensfm_reconstruction: logger.info('importing points 3-D') opensfm_points = opensfm_reconstruction['points'] points_data = [] for point_id in sorted(opensfm_points): point_data = opensfm_points[point_id] point_data = point_data['coordinates'] + point_data['color'] points_data.append(point_data) kapture_points = kapture.Points3d(points_data) else: kapture_points = None # saving kapture csv files logger.info('saving kapture files') kapture_data = kapture.Kapture(sensors=kapture_sensors, records_camera=kapture_images, records_gnss=kapture_gnss, trajectories=kapture_trajectories, keypoints=kapture_keypoints, descriptors=kapture_descriptors, matches=kapture_matches, points3d=kapture_points) kapture.io.csv.kapture_to_dir(dirpath=kapture_rootdir, kapture_data=kapture_data)