Evaluate a model for a single recording, after everything has been loaded.

    Parameters
    ----------
    preprocessing_queue : list
        List of all preprocessing objects.
    feature_list : list
        List of all feature objects.
    model : dict
        Neural network model.
    output_semantics : list
        List that defines what an output means.
    recording : string in JSON format
        The handwritten recording in JSON format.
    recording_id : int or None
        For debugging purposes.

def evaluate_model_single_recording_preloaded(preprocessing_queue,
                                              feature_list,
                                              model,
                                              output_semantics,
                                              recording,
                                              recording_id=None):
    """
    Evaluate a model for a single recording, after everything has been loaded.

    Parameters
    ----------
    preprocessing_queue : list
        List of all preprocessing objects.
    feature_list : list
        List of all feature objects.
    model : dict
        Neural network model.
    output_semantics : list
        List that defines what an output means.
    recording : string in JSON format
        The handwritten recording in JSON format.
    recording_id : int or None
        For debugging purposes.
    """
    handwriting = handwritten_data.HandwrittenData(recording,
                                                   raw_data_id=recording_id)
    handwriting.preprocessing(preprocessing_queue)
    x = handwriting.feature_extraction(feature_list)
    import nntoolkit.evaluate
    model_output = nntoolkit.evaluate.get_model_output(model, [x])
    return nntoolkit.evaluate.get_results(model_output, output_semantics)