comparison vamp/process.py @ 140:1a494598ee2b

Support step size, block size, process timestamp method kwargs

         if ix in results:
             for r in results[ix]:
                 yield { o: r }
 
 
-def process_audio(data, sample_rate, plugin_key, output = "", parameters = {}):
+def process_audio(data, sample_rate, plugin_key, output = "", parameters = {}, **kwargs):
     """Process audio data with a Vamp plugin, and make the results from a
     single plugin output available as a generator.
 
     The provided data should be a 1- or 2-dimensional list or NumPy
     array of floats. If it is 2-dimensional, the first dimension is

 
     If you would prefer to obtain all features in a single output
     structure, consider using vamp.collect() instead.
     """
 
-    plugin, step_size, block_size = vamp.load.load_and_configure(data, sample_rate, plugin_key, parameters)
+    plugin, step_size, block_size = vamp.load.load_and_configure(data, sample_rate, plugin_key, parameters, **kwargs)
 
     if output == "":
         output = plugin.get_output(0)["identifier"]
 
     ff = vamp.frames.frames_from_array(data, step_size, block_size)

                 yield r
         
     plugin.unload()
     
 
-def process_audio_multiple_outputs(data, sample_rate, plugin_key, outputs, parameters = {}):
+def process_audio_multiple_outputs(data, sample_rate, plugin_key, outputs, parameters = {}, **kwargs):
     """Process audio data with a Vamp plugin, and make the results from a
     set of plugin outputs available as a generator.
 
     The provided data should be a 1- or 2-dimensional list or NumPy
     array of floats. If it is 2-dimensional, the first dimension is

     represented as a dictionary containing, optionally, timestamp and
     duration (RealTime objects), label (string), and a 1-dimensional
     array of float values.
     """
 
-    plugin, step_size, block_size = vamp.load.load_and_configure(data, sample_rate, plugin_key, parameters)
+    plugin, step_size, block_size = vamp.load.load_and_configure(data, sample_rate, plugin_key, parameters, **kwargs)
 
     ff = vamp.frames.frames_from_array(data, step_size, block_size)
 
     for r in process_with_initialised_plugin(ff, sample_rate, step_size, plugin, outputs):
         yield r