官方文档 https://docs.ultralytics.com/zh/usage/simple-utilities/?h=yolo_bbox2segment#convert-coco-into-yolo-format

此版本改动较大

评估指标

script/bug_test.py

self.trainer.train()

def _single_card_training(self, world_size=1):

self.train_loader = self.get_dataloader(self.trainset, batch_size=batch_size, rank=RANK, mode="train")

self.loss, self.loss_items = self.model(batch)

class Segment(Detect):

class SegmentationLoss(DetectionLoss):

def parse_model(model_dict, ch, verbose=True):

self.metrics, self.fitness = self.validate()

x = m(x) # run

支持通过传参改变iou def bbox_iou(box1, box2, xywh=True, GIoU=False, DIoU=False, CIoU=False, EIoU=False, SIoU=False,FineSIoU= False, WIoU=False, Focal=False, pow=1, gamma=0.5, scale=False, eps=1e-7):

preds = self.inference(new_img, *args, **kwargs)

elif m in {Detect, WorldDetect, Segment, Pose, OBB, ImagePoolingAttn, v10Detect}

        plot_pr_curve(x, prec_values, ap, save_dir / f"{prefix}PR_curve.png", names, on_plot=on_plot)
        plot_mc_curve(x, f1_curve, save_dir / f"{prefix}F1_curve.png", names, ylabel="F1", on_plot=on_plot)
        plot_mc_curve(x, p_curve, save_dir / f"{prefix}P_curve.png", names, ylabel="Precision", on_plot=on_plot)
        plot_mc_curve(x, r_curve, save_dir / f"{prefix}R_curve.png", names, ylabel="Recall", on_plot=on_plot)