Python APIs for writing UDF for gst-udf-loader
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^


* 
  Initialization

   In case of Python the initialization callback is also same as the native case. User must create a **\ *Udf class*\ ** and the **\ *__init__()*\ ** function defined in class act as a initialization routine for custom UDF.  Following is the dummy constructor code:

  .. code-block:: Python

       class Udf:
       """Example UDF
       """
       def __init__(self):
           """Constructor
           """
           # Add the initialization code in this method.

* 
  Process Actual Data

  The API used to process the actual frame is as follows:

  .. code-block:: Python

       process(self, frame, metadata):
           # Process the frame in this method
           # metadata can be used to return inference result

  **Argument:**

  *frame*\ : Image frame in numpy's ndarray format

  *metadata*\ : An empty dictionary. Inference results can be inserted in this data structure.

  **Return value:**

  This function returns three values.

  *1st Value* : Represents if the frame Need to be dropped or Not. It is boolean in nature. In case of failure user can return *True* in this positional return value.

  *2nd Value* : It represents the actual modified frame if at all it has been modified. Hence the type is **numpy's ndarray**. If the frame is not modified user can return a *None* in this place.

  *3rd Value* : Metadata is returned in this place. Hence the type is **dict**. In general user can return the passed argument as part of this function.

For reference, you can find example UDFs code in links.


* Dummy UDF(\ ``[WORK_DIR]/IEdgeInsights/EdgeVideoAnalyticsMicroservice/eva_udfs/dummy.py``\ )