Casting Fex DataFrame does not correctly assign default Fex metadata

[YounZGrace]

When we run detections, the Detector class automatically fills out all of the relevant Fex meta data. However, when we cast at pandas dataframe as a Fex object, this needs to be manually passed as a keyword. Unfortunately, as a consequence a lot of the internal Fex functions don't work correctly such as compute_identities().

 def __init__(self, *args, **kwargs):
        ### Columns ###
        self.au_columns = kwargs.pop("au_columns", None)
        self.emotion_columns = kwargs.pop("emotion_columns", None)
        self.facebox_columns = kwargs.pop("facebox_columns", None)
        self.landmark_columns = kwargs.pop("landmark_columns", None)
        self.facepose_columns = kwargs.pop("facepose_columns", None)
        self.identity_columns = kwargs.pop("identity_columns", None)
        self.gaze_columns = kwargs.pop("gaze_columns", None)
        self.time_columns = kwargs.pop("time_columns", None)
        self.design_columns = kwargs.pop("design_columns", None)
        
        ### Meta data ###
        self.filename = kwargs.pop("filename", None)
        self.sampling_freq = kwargs.pop("sampling_freq", None)
        self.detector = kwargs.pop("detector", None)
        self.face_model = kwargs.pop("face_model", None)
        self.landmark_model = kwargs.pop("landmark_model", None)
        self.au_model = kwargs.pop("au_model", None)
        self.emotion_model = kwargs.pop("emotion_model", None)
        self.facepose_model = kwargs.pop("facepose_model", None)
        self.identity_model = kwargs.pop("identity_model", None)
        self.features = kwargs.pop("features", None)
        self.sessions = kwargs.pop("sessions", None)

        self.verbose = kwargs.pop("verbose", False)

@ejolly I think we should be trying to automatically figure this out if the columns are not empty or don't exist.

Grace & Luke