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from typing import Optional, Tuple |
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import torch |
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from torch import Tensor |
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from mmdet.structures.bbox import BaseBoxes |
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def anchor_inside_flags(flat_anchors: Tensor, |
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valid_flags: Tensor, |
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img_shape: Tuple[int], |
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allowed_border: int = 0) -> Tensor: |
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"""Check whether the anchors are inside the border. |
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Args: |
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flat_anchors (torch.Tensor): Flatten anchors, shape (n, 4). |
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valid_flags (torch.Tensor): An existing valid flags of anchors. |
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img_shape (tuple(int)): Shape of current image. |
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allowed_border (int): The border to allow the valid anchor. |
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Defaults to 0. |
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Returns: |
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torch.Tensor: Flags indicating whether the anchors are inside a \ |
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valid range. |
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""" |
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img_h, img_w = img_shape[:2] |
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if allowed_border >= 0: |
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if isinstance(flat_anchors, BaseBoxes): |
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inside_flags = valid_flags & \ |
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flat_anchors.is_inside([img_h, img_w], |
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all_inside=True, |
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allowed_border=allowed_border) |
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else: |
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inside_flags = valid_flags & \ |
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(flat_anchors[:, 0] >= -allowed_border) & \ |
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(flat_anchors[:, 1] >= -allowed_border) & \ |
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(flat_anchors[:, 2] < img_w + allowed_border) & \ |
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(flat_anchors[:, 3] < img_h + allowed_border) |
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else: |
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inside_flags = valid_flags |
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return inside_flags |
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def calc_region(bbox: Tensor, |
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ratio: float, |
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featmap_size: Optional[Tuple] = None) -> Tuple[int]: |
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"""Calculate a proportional bbox region. |
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The bbox center are fixed and the new h' and w' is h * ratio and w * ratio. |
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Args: |
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bbox (Tensor): Bboxes to calculate regions, shape (n, 4). |
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ratio (float): Ratio of the output region. |
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featmap_size (tuple, Optional): Feature map size in (height, width) |
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order used for clipping the boundary. Defaults to None. |
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Returns: |
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tuple: x1, y1, x2, y2 |
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""" |
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x1 = torch.round((1 - ratio) * bbox[0] + ratio * bbox[2]).long() |
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y1 = torch.round((1 - ratio) * bbox[1] + ratio * bbox[3]).long() |
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x2 = torch.round(ratio * bbox[0] + (1 - ratio) * bbox[2]).long() |
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y2 = torch.round(ratio * bbox[1] + (1 - ratio) * bbox[3]).long() |
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if featmap_size is not None: |
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x1 = x1.clamp(min=0, max=featmap_size[1]) |
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y1 = y1.clamp(min=0, max=featmap_size[0]) |
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x2 = x2.clamp(min=0, max=featmap_size[1]) |
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y2 = y2.clamp(min=0, max=featmap_size[0]) |
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return (x1, y1, x2, y2) |
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