In YOLOv5 I am running object detection on a custom-trained model in a python notebook – and I can easily get the results in the tensor format or pandas format by using results.pandas().xyxy[0] or results.xyxy[0]. However, often the confidence for the class of each detection is not quite 100%, which implies that the model also calculates the confidence that a given detection is any other class. Is there a way to access this?

In YOLOv5 I am running object detection on a custom-trained model in a python notebook – and I can easily get the results in the tensor format or pandas format by using results.pandas().xyxy[0] or results.xyxy[0]. However, often the confidence for the class of each detection is not quite 100%, which implies that the model also calculates the confidence that a given detection is any other class. Is there a way to access this?