Shortcuts

mmdet.core.anchor.utils 源代码

# Copyright (c) OpenMMLab. All rights reserved.
import torch


[文档]def images_to_levels(target, num_levels): """Convert targets by image to targets by feature level. [target_img0, target_img1] -> [target_level0, target_level1, ...] """ target = torch.stack(target, 0) level_targets = [] start = 0 for n in num_levels: end = start + n # level_targets.append(target[:, start:end].squeeze(0)) level_targets.append(target[:, start:end]) start = end return level_targets
[文档]def anchor_inside_flags(flat_anchors, valid_flags, img_shape, allowed_border=0): """Check whether the anchors are inside the border. Args: flat_anchors (torch.Tensor): Flatten anchors, shape (n, 4). valid_flags (torch.Tensor): An existing valid flags of anchors. img_shape (tuple(int)): Shape of current image. allowed_border (int, optional): The border to allow the valid anchor. Defaults to 0. Returns: torch.Tensor: Flags indicating whether the anchors are inside a \ valid range. """ img_h, img_w = img_shape[:2] if allowed_border >= 0: inside_flags = valid_flags & \ (flat_anchors[:, 0] >= -allowed_border) & \ (flat_anchors[:, 1] >= -allowed_border) & \ (flat_anchors[:, 2] < img_w + allowed_border) & \ (flat_anchors[:, 3] < img_h + allowed_border) else: inside_flags = valid_flags return inside_flags
[文档]def calc_region(bbox, ratio, featmap_size=None): """Calculate a proportional bbox region. The bbox center are fixed and the new h' and w' is h * ratio and w * ratio. Args: bbox (Tensor): Bboxes to calculate regions, shape (n, 4). ratio (float): Ratio of the output region. featmap_size (tuple): Feature map size used for clipping the boundary. Returns: tuple: x1, y1, x2, y2 """ x1 = torch.round((1 - ratio) * bbox[0] + ratio * bbox[2]).long() y1 = torch.round((1 - ratio) * bbox[1] + ratio * bbox[3]).long() x2 = torch.round(ratio * bbox[0] + (1 - ratio) * bbox[2]).long() y2 = torch.round(ratio * bbox[1] + (1 - ratio) * bbox[3]).long() if featmap_size is not None: x1 = x1.clamp(min=0, max=featmap_size[1]) y1 = y1.clamp(min=0, max=featmap_size[0]) x2 = x2.clamp(min=0, max=featmap_size[1]) y2 = y2.clamp(min=0, max=featmap_size[0]) return (x1, y1, x2, y2)
Read the Docs v: v2.25.1
Versions
latest
stable
v2.25.1
v2.25.0
v2.24.1
v2.24.0
v2.23.0
v2.22.0
v2.21.0
v2.20.0
v2.19.1
v2.19.0
v2.18.1
v2.18.0
v2.17.0
v2.16.0
v2.15.1
v2.15.0
v2.14.0
Downloads
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.