def __init__(self,
data_provider,
output=None,
ps_data_provider=None,
common=None,
rds_conn=None,
front_facing=False,
custom_scif=None,
custom_matches=None,
**kwargs):
super(Block, self).__init__(data_provider, output, ps_data_provider,
common, rds_conn, **kwargs)
self._position_graphs = PositionGraphs(self.data_provider)
self.front_facing = front_facing
self.outliers_threshold = Default.outliers_threshold
self.check_vertical_horizontal = Default.check_vertical_horizontal
self.include_stacking = Default.include_stacking
self.ignore_empty = Default.ignore_empty
self.allowed_edge_type = Default.allowed_edge_type
self.scif = data_provider.scene_item_facts if custom_scif is None else custom_scif
self.matches = data_provider.matches if custom_matches is None else custom_matches
self.adj_graphs_by_scene = {}
self.masking_data = transform_maskings(
retrieve_maskings(
self.data_provider.project_name,
self.data_provider.scenes_info['scene_fk'].to_list()))
self.masking_data = self.masking_data.merge(
self.matches[['probe_match_fk', 'scene_fk']],
on=['probe_match_fk'])
self.matches_df = self.matches.merge(
self.data_provider.all_products_including_deleted, on='product_fk')
self.matches_df = self.matches_df[
~(self.matches_df['product_type'].isin(['POS']))
& (self.matches_df['stacking_layer'] > 0)]
self.matches_df[Block.BLOCK_KEY] = None
def _load_maskings(project_name, scene_id):
return transform_maskings(retrieve_maskings(project_name, [scene_id]))