37

for i in range(idx):
       #Get the IOUs of all boxes that come after the one we are looking at the loop
        try:
           ious = bounding_box_iou(image_pred_class[i].unsqueeze(0), image_pred_class[i+1:])
        except ValueError:
           break
        except IndexError:
           break
        #Zero out all the detections that have IoU > treshhold
        iou_mask = (ious < nms_conf).float().unsqueeze(1)
        image_pred_class[i+1:] *= iou_mask
                
        #Remove the non-zero entries
        non_zero_ind = torch.nonzero(image_pred_class[:,4]).squeeze()
        image_pred_class = image_pred_class[non_zero_ind].view(-1,7)