First off, the acronym DFL in YOLOv8 actually stands for Distribution Focal Loss rather than Directional Feature Learning. This may have been a source of confusion and I apologize for any misunderstanding. Distribution Focal Loss (DFL) is indeed utilized in YOLOv8. It is a modified version of...
一、概述 (1) 通过YOLOv8-训练流程-正负样本分配的介绍,我们可以知道,经过预处理与筛选的过程得到最终的训练数据: a. 网络输出值:pred_scores[bx8400xcls_num]、pred_bboxes[bx8400x4] b. 训练标签值: target_scores[bx8400xcls_num](one-hot类型),在计算损失时与预测结果pred_scores[bx8400xcls_num],...
In YOLOv8, Binary Cross Entropy (BCE) is used for the classification loss, which does not incorporate the same focus on class imbalance as Focal Losses do. While other loss functions, such as VarifocalLoss, have been explored, they have not been implemented in YOLOv8's default configuration ...
coco_val_dataset = dict( _delete_=True, type='MultiModalDataset', dataset=dict(type='YOLOv5LVISV1Dataset', metainfo=dict(classes=classes), data_root=r'E:\george\Yolo_world_datasets\ExDark', test_mode=True, ann_file=r'annotations/instances_val2017.json', data_prefix=dict(img=r'images/...
yolo_world_l_dual_vlpan_2e-4_80e_8gpus_finetune_coco.py文件,我需要微调 base = ( '../../third_party/mmyolo/configs/yolov8/yolov8_l_syncbn_fast_8xb16-500e_coco.py') custom_imports = dict( imports=['yolo_world'], allow_failed_imports=False) hyper-...