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Add HUB-SDK Docs reference section (#7781)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
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Glenn Jocher 2024-01-27 00:21:31 +01:00 • committed by GitHub
parent 5941128835
commit ee88882874
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25 changed files with 142 additions and 47 deletions
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6
ultralytics/models/sam/amg.py
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@ -35,9 +35,11 @@ def calculate_stability_score(masks: torch.Tensor, mask_threshold: float, thresh
The stability score is the IoU between the binary masks obtained by thresholding the predicted mask logits at high
and low values.
Notes:
- One mask is always contained inside the other.
- Save memory by preventing unnecessary cast to torch.int64
"""
# One mask is always contained inside the other.
# Save memory by preventing unnecessary cast to torch.int64
intersections = (masks > (mask_threshold + threshold_offset)).sum(-1, dtype=torch.int16).sum(-1, dtype=torch.int32)
unions = (masks > (mask_threshold - threshold_offset)).sum(-1, dtype=torch.int16).sum(-1, dtype=torch.int32)
return intersections / unions

8
ultralytics/models/yolo/segment/val.py
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@ -215,8 +215,12 @@ class SegmentationValidator(DetectionValidator):
self.plot_masks.clear()
def pred_to_json(self, predn, filename, pred_masks):
"""Save one JSON result."""
# Example result = {"image_id": 42, "category_id": 18, "bbox": [258.15, 41.29, 348.26, 243.78], "score": 0.236}
"""
Save one JSON result.
Examples:
>>> result = {"image_id": 42, "category_id": 18, "bbox": [258.15, 41.29, 348.26, 243.78], "score": 0.236}
"""
from pycocotools.mask import encode # noqa
def single_encode(x):