You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello, I want to use my own datasets to train a YOLO-World detector. But there is a question, for example, dataset_A has car/person in images, but only 'car' is labeled; datset_B also has car/person in images, but only 'person' is labeled. Thus, how can I put dataset_A and B to train YOLO-World simultaneously, the unlabeled objects won't affect the learning ?
Because this is an ovd detector, the distribution of its train data is very wide (like Flickr/GQA/Object365). Some categories in Flickr, must not be labeled in obj365. So I have this question.
The text was updated successfully, but these errors were encountered:
Hello, I want to use my own datasets to train a YOLO-World detector. But there is a question, for example, dataset_A has car/person in images, but only 'car' is labeled; datset_B also has car/person in images, but only 'person' is labeled. Thus, how can I put dataset_A and B to train YOLO-World simultaneously, the unlabeled objects won't affect the learning ?
Because this is an ovd detector, the distribution of its train data is very wide (like Flickr/GQA/Object365). Some categories in Flickr, must not be labeled in obj365. So I have this question.
The text was updated successfully, but these errors were encountered: