How can I get noun scores and verb scores?

[anamanzano]

Hi! So I was wondering if it's possible to get verb scores and noun scores from the action recognition scores. I was using margin probability to obtain the results, but I don't get anything that makes sense. Maybe I have to normalize the results? Or is something that I can not get from action scores?
Thank you!

[anamanzano]

Does this code make sense?

 with torch.no_grad():
       prediction = model(video_input.to(device), input_type="video")

       # Get the predicted classes (action scores)
       pred_class_all = prediction.topk(k=3806)
       class_indices = pred_class_all.indices
       class_scores = pred_class_all.values


   pred_class_names_all = []
   for indices, score in zip(class_indices[0], class_scores[0]):
       pred_class_names_all.append((epic_id_to_action[int(indices)], score))

   verbs = []
   nouns = []
   verb_scores = []
   noun_scores = []
   dic_verbs = {}
   dic_nouns = {}
   
   for pred, score in pred_class_names_all:
       verb, noun = pred.split()
       verbs.append(verb)
       nouns.append(noun)
       verb_scores.append(score)
       noun_scores.append(score)
     
   # Split the predictions into verbs and nouns and store in separate dictionaries
   verb_scores_dict = {}
   noun_scores_dict = {}
   
   for pred, score in pred_class_names_all:
       verb, noun = pred.split()
       
       if verb in verb_scores_dict:
         verb_scores_dict[verb] += score
       else:
         verb_scores_dict[verb] = score
       
       if noun in noun_scores_dict:
         noun_scores_dict[noun] += score
       else:
         noun_scores_dict[noun] = score

Thank you!