generate_training_input.py 文件源码

def read_roads(roads_shp, records, buffer_size):
    """Reads shapefile and extracts roads and projection
    :param roads_shp: Path to the shapefile containing roads
    :param records: List of shapely geometries representing record points
    :param buffer_size: Number of units to buffer record for checking if road should be kept
    """
    # Create a spatial index for record buffers to efficiently find intersecting roads
    record_buffers_index = rtree.index.Index()
    for idx, record in enumerate(records):
        record_point = record['point']
        record_buffer_bounds = record_point.buffer(buffer_size).bounds
        record_buffers_index.insert(idx, record_buffer_bounds)

    shp_file = fiona.open(roads_shp)
    roads = []
    logger.info('Number of total roads in shapefile: {:,}'.format(len(shp_file)))
    for road in shp_file:
        road_shp = shape(road['geometry'])
        if should_keep_road(road, road_shp, record_buffers_index):
            roads.append(road_shp)

    return (roads, shp_file.bounds)