FR module.

Feature refine module.

Display and save evaluation results. Args: show (bool): Whether to show the image. Default: True wait_time (float): Value of wait

Convex sort class.

DOTA dataset for detection. Args: ann_file (str): Annotation file path. pipeline (list[dict]): Processing pipeline. versi

Delta XYWHA HBBox coder. this coder encodes bbox (x1, y1, x2, y2) into delta (dx, dy, dw, dh, da) and decodes delta (dx, dy, dw, dh, da)

Delta XYWHA OBBox coder. this coder is used for rotated objects detection (for example on task1 of DOTA dataset). this coder encodes bbox (x

Feature refine class.

Written by hukaixuan19970627. Reference: https://github.com/hukaixuan19970627/OrientedRepPoints_DOTA Rotate img & bbox(n, 8). Args:

Non-Standard pseudo anchor generator that is used to generate valid flags only!

Rotated Refinement RetinaNet.

Standard rotate anchor generator for 2D anchor-based detectors.

Anchor-based head (RPN, RetinaNet, SSD, etc.). Args: num_classes (int): Number of categories excluding the background categor

2D Overlaps (e.g. IoUs, GIoUs) Calculator.

2D Overlaps (e.g. IoUs, GIoUs) Calculator.

2D Overlaps (e.g. IoUs, GIoUs) Calculator.

Args: flip_ratio (float | list[float], optional): The flipping probability. Default: None. direction(str | list[str]

Random sampler. Args: num (int): Number of samples pos_fraction (float): Fraction of positive samples neg_pos_up (int, op

Resize images & rotated bbox Inherit Resize pipeline class to handle rotated bboxes. Args: img_scale (tuple or list[tuple]): Images s

r"""An anchor-based head used in `RetinaNet <https://arxiv.org/pdf/1708.02002.pdf>`_. The head contains two subnetworks. The first classifies

Implementation of `RetinaNet <https://arxiv.org/abs/1708.02002>`_

Rotational Anchor-based refine head. Args: num_classes (int): Number of categories excluding the background category.