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42 lines
1.4 KiB
42 lines
1.4 KiB
# Ultralytics YOLO 🚀, AGPL-3.0 license |
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from copy import copy |
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from ultralytics.models import yolo |
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from ultralytics.nn.tasks import OBBModel |
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from ultralytics.utils import DEFAULT_CFG, RANK |
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class OBBTrainer(yolo.detect.DetectionTrainer): |
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""" |
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A class extending the DetectionTrainer class for training based on an Oriented Bounding Box (OBB) model. |
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Example: |
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```python |
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from ultralytics.models.yolo.obb import OBBTrainer |
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args = dict(model='yolov8n-seg.pt', data='coco8-seg.yaml', epochs=3) |
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trainer = OBBTrainer(overrides=args) |
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trainer.train() |
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``` |
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""" |
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def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None): |
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"""Initialize a OBBTrainer object with given arguments.""" |
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if overrides is None: |
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overrides = {} |
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overrides["task"] = "obb" |
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super().__init__(cfg, overrides, _callbacks) |
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def get_model(self, cfg=None, weights=None, verbose=True): |
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"""Return OBBModel initialized with specified config and weights.""" |
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model = OBBModel(cfg, ch=3, nc=self.data["nc"], verbose=verbose and RANK == -1) |
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if weights: |
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model.load(weights) |
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return model |
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def get_validator(self): |
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"""Return an instance of OBBValidator for validation of YOLO model.""" |
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self.loss_names = "box_loss", "cls_loss", "dfl_loss" |
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return yolo.obb.OBBValidator(self.test_loader, save_dir=self.save_dir, args=copy(self.args))
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