ultralytics 8.0.239 Ultralytics Actions and hub-sdk adoption (#7431)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Burhan <62214284+Burhan-Q@users.noreply.github.com>
Co-authored-by: Kayzwer <68285002+Kayzwer@users.noreply.github.com>
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Glenn Jocher 2024-01-10 03:16:08 +01:00 committed by GitHub
parent e795277391
commit fe27db2f6e
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139 changed files with 6870 additions and 5125 deletions

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@ -23,17 +23,19 @@ class SegmentationPredictor(DetectionPredictor):
def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
"""Initializes the SegmentationPredictor with the provided configuration, overrides, and callbacks."""
super().__init__(cfg, overrides, _callbacks)
self.args.task = 'segment'
self.args.task = "segment"
def postprocess(self, preds, img, orig_imgs):
"""Applies non-max suppression and processes detections for each image in an input batch."""
p = ops.non_max_suppression(preds[0],
self.args.conf,
self.args.iou,
agnostic=self.args.agnostic_nms,
max_det=self.args.max_det,
nc=len(self.model.names),
classes=self.args.classes)
p = ops.non_max_suppression(
preds[0],
self.args.conf,
self.args.iou,
agnostic=self.args.agnostic_nms,
max_det=self.args.max_det,
nc=len(self.model.names),
classes=self.args.classes,
)
if not isinstance(orig_imgs, list): # input images are a torch.Tensor, not a list
orig_imgs = ops.convert_torch2numpy_batch(orig_imgs)