wangrongsheng / bestyolo

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Important

我正在寻求一个PhD.的就读机会，如果您对我有兴趣可以发邮件给我: [email protected]

I am seeking a PhD. opportunity, if you are interested you can email me: [email protected]

       

王荣胜｜Rongsheng Wang

bestyolo's Issues

[bug]list index out of range

Traceback (most recent call last): File "F:\Deep_learning\BestYOLO\train_AuxOTA.py", line 641, in <module> main(opt) File "F:\Deep_learning\BestYOLO\train_AuxOTA.py", line 530, in main train(opt.hyp, opt, device, callbacks) File "F:\Deep_learning\BestYOLO\train_AuxOTA.py", line 312, in train loss, loss_items = compute_loss_ota(pred, targets.to(device), imgs) # loss scaled by batch_size File "F:\Deep_learning\BestYOLO\utils\loss_AuxOTA.py", line 276, in __call__ pi_aux = p[i+self.nl] IndexError: list index out of range

AttributeError: 'EfficientNet' object has no attribute 'yaml'

@WangRongsheng 你好, I used to your repo and i want to perform a training using my own dataset. I want to use efficientNet instead of darknet in my backbone network. Within the train.py file, I replaced my weights with efficientnet_b0.pt instead of yolov5n.pt. The error mentioned in the title appears. I would be happy if you

runfile('D:/BestYOLO/BestYOLO-main/train.py', wdir='D:/BestYOLO/BestYOLO-main')
Reloaded modules: models, utils, utils.downloads, utils.metrics, utils.general, utils.augmentations, utils.torch_utils, utils.dataloaders, utils.segment, utils.segment.general, utils.plots, models.common, classify.val, models.experimental, utils.autoanchor, models.yolo, utils.loggers.clearml, utils.loggers.clearml.clearml_utils, utils.loggers.wandb, utils.loggers.wandb.wandb_utils, utils.loggers
train: weights=efficientnet_b0.pt, cfg=, data=data\coco128.yaml, hyp=data\hyps\hyp.scratch-low.yaml, epochs=2, batch_size=2, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=runs\train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=3407, local_rank=-1, loss_OTA=False, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
YOLOv5 2023-10-30 Python-3.10.13 torch-2.1.0+cpu CPU

hyperparameters: lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.5, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0
ClearML: run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 in ClearML
Comet: run 'pip install comet_ml' to automatically track and visualize YOLOv5 runs in Comet
TensorBoard: Start with 'tensorboard --logdir runs\train', view at http://localhost:6006/
github: skipping check (not a git repository), for updates see https://github.com/ultralytics/yolov5
Traceback (most recent call last):

File ~.conda\envs\thesis_two\lib\site-packages\spyder_kernels\py3compat.py:356 in compat_exec
exec(code, globals, locals)

File d:\bestyolo\bestyolo-main\train.py:640
main(opt)

File d:\bestyolo\bestyolo-main\train.py:534 in main
train(opt.hyp, opt, device, callbacks)

File d:\bestyolo\bestyolo-main\train.py:125 in train
model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device) # create

File ~.conda\envs\thesis_two\lib\site-packages\torch\nn\modules\module.py:1695 in getattr
raise AttributeError(f"'{type(self).name}' object has no attribute '{name}'")

AttributeError: 'EfficientNet' object has no attribute 'yaml'

about aux loss

为什么aux loss中取的输入为9.13.17 而不是，17，20，23呢

我如果backbone替换成efficientNetV2-s后，还能用.yaml文件里面depth和width参数来控制网络模型的大小吗？

yolov5可以通过修改depth和width参数，从而实现 s m l x四个版本的变化，我想知道的是主干网替换efficientNetV2-s，是否还能这样做？

请问单框多标签的应用有使用文档吗？