Clamping in bbox2dist about ultralytics HOT 1 OPEN

@thawro hello,

Thank you for your question and for checking the existing issues and discussions beforehand! 😊

The clamping in the bbox2dist function is designed to ensure that the calculated distances (left, top, right, bottom) remain within a valid range. Specifically, the distances are clamped to a maximum value of reg_max - 0.01. This serves a couple of purposes:

1. Stability: Clamping helps prevent excessively large distance values, which could destabilize the training process or lead to numerical issues.
2. Bounding Box Constraints: By ensuring the distances do not exceed reg_max, we maintain the bounding box predictions within a reasonable range relative to the anchor points. This is crucial for the model's ability to learn accurate object localization.

Here's the relevant code snippet for reference:

def bbox2dist(anchor_points, bbox, reg_max):
    """Transform bbox(xyxy) to dist(ltrb)."""
    x1y1, x2y2 = bbox.chunk(2, -1)
    return torch.cat((anchor_points - x1y1, x2y2 - anchor_points), -1).clamp_(0, reg_max - 0.01)  # dist (lt, rb)

If you have any further questions or need additional clarification, feel free to ask!

from ultralytics.