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Refactor a utility function for bbox conversion

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Summary: This function makes it easier to extend FrameData class with new channels; brushing it up a bit.

Reviewed By: bottler

Differential Revision: D67816470

fbshipit-source-id: 6575415c864d0f539e283889760cd2331bf226a7
This commit is contained in:
Roman Shapovalov 2025-01-06 04:17:57 -08:00 committed by Facebook GitHub Bot
parent 5247f6ad74
commit 89b851e64c
1 changed files with 9 additions and 11 deletions
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20
pytorch3d/implicitron/dataset/utils.py
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@ -134,7 +134,15 @@ T = TypeVar("T", bound=torch.Tensor)
def bbox_xyxy_to_xywh(xyxy: T) -> T: def bbox_xyxy_to_xywh(xyxy: T) -> T:
wh = xyxy[2:] - xyxy[:2] wh = xyxy[2:] - xyxy[:2]
xywh = torch.cat([xyxy[:2], wh]) xywh = torch.cat([xyxy[:2], wh])
return xywh # pyre-ignore return xywh # pyre-ignore[7]
def bbox_xywh_to_xyxy(xywh: T, clamp_size: float | int | None = None) -> T:
wh = xywh[2:]
if clamp_size is not None:
wh = wh.clamp(min=clamp_size)
xyxy = torch.cat([xywh[:2], xywh[:2] + wh])
return xyxy # pyre-ignore[7]
def get_clamp_bbox( def get_clamp_bbox(
@ -180,16 +188,6 @@ def rescale_bbox(
return bbox * rel_size return bbox * rel_size
def bbox_xywh_to_xyxy(
xywh: torch.Tensor, clamp_size: Optional[int] = None
) -> torch.Tensor:
xyxy = xywh.clone()
if clamp_size is not None:
xyxy[2:] = torch.clamp(xyxy[2:], clamp_size)
xyxy[2:] += xyxy[:2]
return xyxy
def get_1d_bounds(arr: np.ndarray) -> Tuple[int, int]: def get_1d_bounds(arr: np.ndarray) -> Tuple[int, int]:
nz = np.flatnonzero(arr) nz = np.flatnonzero(arr)
return nz[0], nz[-1] + 1 return nz[0], nz[-1] + 1