#find the highest value corresponding to every query
obj_scores[index] = verb_query #total 9 verb query put to the object_score query
index += 1
thres = np.sort(obj_scores.numpy())[::-1][topN]
keep = obj_scores > thres
print(keep)
out_sub_boxes = outputs['pred_sub_boxes']
out_obj_boxes = outputs['pred_obj_boxes']
What does keep = obj_scores > thres mean? And are my annotations right?
Hi, the mentioned codes are for visualization, where we only select the human-object pairs with top-3 confidences for visualization. Your annotations are right.
for verb_score in verbscores: #64 query corresponding to verb class_
verb_query = np.sum(np.sort(verb_score.numpy())[::-1][:topN])
#find the highest value corresponding to every query obj_scores[index] = verb_query #total 9 verb query put to the object_score query index += 1 thres = np.sort(obj_scores.numpy())[::-1][topN] keep = obj_scores > thres print(keep) out_sub_boxes = outputs['pred_sub_boxes'] out_obj_boxes = outputs['pred_obj_boxes'] What does keep = obj_scores > thres mean? And are my annotations right?