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ultralytics 8.0.67 Pose speeds, Comet and ClearML updates (#1871)

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Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Victor Sonck <victor.sonck@gmail.com>
Co-authored-by: Danny Kim <dh031200@gmail.com>
This commit is contained in:
Glenn Jocher
2023-04-06 19:07:10 +02:00
committed by GitHub
parent 1cb92d7f42
commit 2725545090
28 changed files with 547 additions and 146 deletions
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4
ultralytics/yolo/v8/classify/train.py
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@ -13,11 +13,11 @@ from ultralytics.yolo.utils.torch_utils import is_parallel, strip_optimizer
class ClassificationTrainer(BaseTrainer):
def __init__(self, cfg=DEFAULT_CFG, overrides=None):
def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
if overrides is None:
overrides = {}
overrides['task'] = 'classify'
super().__init__(cfg, overrides)
super().__init__(cfg, overrides, _callbacks)
def set_model_attributes(self):
self.model.names = self.data['names']

4
ultralytics/yolo/v8/classify/val.py
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@ -8,8 +8,8 @@ from ultralytics.yolo.utils.metrics import ClassifyMetrics
class ClassificationValidator(BaseValidator):
def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None):
super().__init__(dataloader, save_dir, pbar, args)
def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None, _callbacks=None):
super().__init__(dataloader, save_dir, pbar, args, _callbacks)
self.args.task = 'classify'
self.metrics = ClassifyMetrics()

4
ultralytics/yolo/v8/detect/val.py
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@ -18,8 +18,8 @@ from ultralytics.yolo.utils.torch_utils import de_parallel
class DetectionValidator(BaseValidator):
def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None):
super().__init__(dataloader, save_dir, pbar, args)
def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None, _callbacks=None):
super().__init__(dataloader, save_dir, pbar, args, _callbacks)
self.args.task = 'detect'
self.is_coco = False
self.class_map = None

4
ultralytics/yolo/v8/pose/train.py
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@ -20,11 +20,11 @@ from ultralytics.yolo.v8.detect.train import Loss
# BaseTrainer python usage
class PoseTrainer(v8.detect.DetectionTrainer):
def __init__(self, cfg=DEFAULT_CFG, overrides=None):
def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
if overrides is None:
overrides = {}
overrides['task'] = 'pose'
super().__init__(cfg, overrides)
super().__init__(cfg, overrides, _callbacks)
def get_model(self, cfg=None, weights=None, verbose=True):
model = PoseModel(cfg, ch=3, nc=self.data['nc'], data_kpt_shape=self.data['kpt_shape'], verbose=verbose)

4
ultralytics/yolo/v8/pose/val.py
View File

@ -14,8 +14,8 @@ from ultralytics.yolo.v8.detect import DetectionValidator
class PoseValidator(DetectionValidator):
def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None):
super().__init__(dataloader, save_dir, pbar, args)
def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None, _callbacks=None):
super().__init__(dataloader, save_dir, pbar, args, _callbacks)
self.args.task = 'pose'
self.metrics = PoseMetrics(save_dir=self.save_dir)

4
ultralytics/yolo/v8/segment/train.py
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@ -17,11 +17,11 @@ from ultralytics.yolo.v8.detect.train import Loss
# BaseTrainer python usage
class SegmentationTrainer(v8.detect.DetectionTrainer):
def __init__(self, cfg=DEFAULT_CFG, overrides=None):
def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
if overrides is None:
overrides = {}
overrides['task'] = 'segment'
super().__init__(cfg, overrides)
super().__init__(cfg, overrides, _callbacks)
def get_model(self, cfg=None, weights=None, verbose=True):
model = SegmentationModel(cfg, ch=3, nc=self.data['nc'], verbose=verbose and RANK == -1)

4
ultralytics/yolo/v8/segment/val.py
View File

@ -16,8 +16,8 @@ from ultralytics.yolo.v8.detect import DetectionValidator
class SegmentationValidator(DetectionValidator):
def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None):
super().__init__(dataloader, save_dir, pbar, args)
def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None, _callbacks=None):
super().__init__(dataloader, save_dir, pbar, args, _callbacks)
self.args.task = 'segment'
self.metrics = SegmentMetrics(save_dir=self.save_dir)