HongChuang/ultralytics-ascend
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Start export implementation (#110)

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Glenn Jocher 2022-12-29 14:17:14 +01:00 • committed by GitHub
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6
ultralytics/yolo/v8/segment/train.py
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@ -12,11 +12,9 @@ from ultralytics.yolo.utils.plotting import plot_images, plot_results
from ultralytics.yolo.utils.tal import TaskAlignedAssigner, dist2bbox, make_anchors
from ultralytics.yolo.utils.torch_utils import de_parallel
from ..detect import DetectionTrainer
# BaseTrainer python usage
class SegmentationTrainer(DetectionTrainer):
class SegmentationTrainer(v8.detect.DetectionTrainer):
def load_model(self, model_cfg=None, weights=None, verbose=True):
model = SegmentationModel(model_cfg or weights["model"].yaml, ch=3, nc=self.data["nc"], verbose=verbose)
@ -174,7 +172,7 @@ class SegLoss:
@hydra.main(version_base=None, config_path=str(DEFAULT_CONFIG.parent), config_name=DEFAULT_CONFIG.name)
def train(cfg):
cfg.model = cfg.model or "models/yolov8n-seg.yaml"
cfg.model = cfg.model or "yolov8n-seg.yaml"
cfg.data = cfg.data or "coco128-seg.yaml" # or yolo.ClassificationDataset("mnist")
trainer = SegmentationTrainer(cfg)
trainer.train()