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| """Segment data model for detected objects.""" | |
| from __future__ import annotations | |
| from dataclasses import dataclass, field | |
| import numpy as np | |
| class Segment: | |
| """A detected object segment in an image.""" | |
| id: int | |
| mask: np.ndarray # (H, W) boolean mask | |
| bbox: list[int] # [x1, y1, x2, y2] | |
| area: int | |
| confidence: float = 0.0 | |
| saliency_score: float = 0.0 | |
| def width(self) -> int: | |
| return self.bbox[2] - self.bbox[0] | |
| def height(self) -> int: | |
| return self.bbox[3] - self.bbox[1] | |
| def center(self) -> tuple[int, int]: | |
| cx = (self.bbox[0] + self.bbox[2]) // 2 | |
| cy = (self.bbox[1] + self.bbox[3]) // 2 | |
| return cx, cy | |