Feat/inference slicer segmentation #1178
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SkalskiP
requested changes
May 13, 2024
| from supervision.utils.image import crop_image | ||
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| def move_detections(detections: Detections, offset: np.array) -> Detections: | ||
| def move_detections( | ||
| detections: Detections, offset: np.ndarray, image_shape: np.ndarray |
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Argument image_shape is called resolution_wh in most places in supervision. Let's keep it this way.
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Also, I think it should be Optional.
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Also please add |
SkalskiP
requested changes
May 13, 2024
supervision/detection/utils.py
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| def move_masks( | ||
| masks: np.ndarray, | ||
| offset: np.ndarray, | ||
| desired_shape: Optional[Union[Tuple[int, int, int], Tuple[int, int]]] = None, |
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Why not just resolution_wh?
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Yeah, sounds good, will change it
SkalskiP
reviewed
May 13, 2024
SkalskiP
approved these changes
May 13, 2024
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Description
Prerequisites:
This allows the slicer to merge segmentation masks.
Previously it would fail when attempting to stack slices of different sizes, as there'd be no attempts to move & pad the slices. The result is that each mask would be of size(slice), rather than size(image).
Type of change
Please delete options that are not relevant.
How has this change been tested, please provide a testcase or example of how you tested the change?
Same notebook as for prior PR.
馃摀 Google Colab
Any specific deployment considerations
NONE.Docs