Building Hybrid Pipelines ========================= The section discusses how to pack multiple pipelines in a single pipeline, separating their compute spaces with custom primary ROI. In Savant, a developer can pack multiple sub-pipelines into a single pipeline, working either on all frames or conditionally based on ROI. Unconditional Processing ------------------------ By default, the primary model analyzes the whole frame; however, under the hood, Savant creates the :doc:`default <../savant_101/25_top_level_roi>` top-level object covering the whole frame; thus, the models without specified input constraints can analyze it. It allows placing multiple primary models one after another and then their secondary models. The only requirement is non-overlapping unit names to avoid object collisions. Normally, there is no difference how to place units if there are no cross dependencies between units; thus, the ordering is important only between elements of sub-pipelines. .. image:: ../_static/img/3_building_hybrid_pipelines_unconditional.png .. tip:: consider placing sub-pipelines in :doc:`element groups <2_element_group>`: it helps to develop and debug them independently. Conditional Processing ---------------------- When you need to process frames conditionally, based on per-stream information, e.g., handle `cam-1` with a car processing sub-pipeline and `cam-2` with a person processing sub-pipeline, a developer must place a special ROI-modifying custom pyfunc before other pipeline elements. .. image:: ../_static/img/3_building_hybrid_pipelines_conditional.png That pyfunc must modify ROI based on ``source-id`` or other knowledge like per-frame attributes: - when ``source-id`` is unknown it can :ref:`be deleted ` to ensure the frame is not processed; - when ``source-id`` is known and relates to the car processing sub-pipeline, :ref:`set ` it to ``car.roi``; - when ``source-id`` is known and relates to the person processing sub-pipeline, :ref:`set ` it to ``person.roi``; The primary models must accept corresponding ROIs rather than work on default ROI: .. code-block:: yaml ... element: nvinfer@detector name: CarDetector model: input: object: car.roi ... element: nvinfer@detector name: PersonDetector model: input: object: person.roi Pros & Cons Of Hybrid Pipelines ------------------------------- Pros: - easier to maintain deployments; - efficient processing; - easier to route video streams (no stream duplication is needed); Cons: - more difficult to develop and troubleshoot, consider :doc:`element groups <2_element_group>`; - increases end-to-end delay; - more difficult to plan compute resources when real-time processing is required.