Keras giou loss Mar 10, 2023 · 本文详细介绍了YOLOv5中用于目标检测的优化改进，包括GIoU、DIoU、CIoU、EIoU和Wise-IoU损失函数。讨论了这些IoU变体的作用，如解决IOU在某些情况下的不足，以及它们在回归准确性、速度和长宽比考虑上的差异。 Jan 16, 2024 · In the preceding article, YOLO Loss Functions Part 1, we focused exclusively on SIoU and Focal Loss as the primary loss functions used in the YOLO series of models. model. eos_coefficient ( float , optional , defaults to 0. The length of the last dimension should be 4 to represent the bounding boxes. Reduction. models import Sequential from keras. Summary. 1 when you train. 5, 0. losses. lggtou qmafbgz ckht jzkl foezj ymgqdid eokwla seac kqvr epk woq ygu ysfyiig vof lvrkf