本文整理汇总了Python中mmdet.core.bbox_mapping方法的典型用法代码示例。如果您正苦于以下问题：Python core.bbox_mapping方法的具体用法？Python core.bbox_mapping怎么用？Python core.bbox_mapping使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类mmdet.core的用法示例。
在下文中一共展示了core.bbox_mapping方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: aug_test
# 需要导入模块: from mmdet import core [as 别名]
# 或者: from mmdet.core import bbox_mapping [as 别名]
def aug_test(self, imgs, img_metas, rescale=False):
"""Test function with test time augmentation.
Args:
imgs (list[torch.Tensor]): List of multiple images
img_metas (list[dict]): List of image information.
rescale (bool, optional): Whether to rescale the results.
Defaults to False.
Returns:
np.ndarray: proposals
"""
proposal_list = self.rpn_head.aug_test_rpn(
self.extract_feats(imgs), img_metas)
if not rescale:
for proposals, img_meta in zip(proposal_list, img_metas[0]):
img_shape = img_meta['img_shape']
scale_factor = img_meta['scale_factor']
flip = img_meta['flip']
flip_direction = img_meta['flip_direction']
proposals[:, :4] = bbox_mapping(proposals[:, :4], img_shape,
scale_factor, flip,
flip_direction)
# TODO: remove this restriction
return proposal_list[0].cpu().numpy() 示例2: aug_test_mask
# 需要导入模块: from mmdet import core [as 别名]
# 或者: from mmdet.core import bbox_mapping [as 别名]
def aug_test_mask(self, feats, img_metas, det_bboxes, det_labels):
"""Test for mask head with test time augmentation."""
if det_bboxes.shape[0] == 0:
segm_result = [[] for _ in range(self.mask_head.num_classes)]
else:
aug_masks = []
for x, img_meta in zip(feats, img_metas):
img_shape = img_meta[0]['img_shape']
scale_factor = img_meta[0]['scale_factor']
flip = img_meta[0]['flip']
_bboxes = bbox_mapping(det_bboxes[:, :4], img_shape,
scale_factor, flip)
mask_rois = bbox2roi([_bboxes])
mask_results = self._mask_forward(x, mask_rois)
mask_results['mask_pred'] = self._mask_point_forward_test(
x, mask_rois, det_labels, mask_results['mask_pred'],
img_metas)
# convert to numpy array to save memory
aug_masks.append(
mask_results['mask_pred'].sigmoid().cpu().numpy())
merged_masks = merge_aug_masks(aug_masks, img_metas, self.test_cfg)
ori_shape = img_metas[0][0]['ori_shape']
segm_result = self.mask_head.get_seg_masks(
merged_masks,
det_bboxes,
det_labels,
self.test_cfg,
ori_shape,
scale_factor=1.0,
rescale=False)
return segm_result 示例3: aug_test
# 需要导入模块: from mmdet import core [as 别名]
# 或者: from mmdet.core import bbox_mapping [as 别名]
def aug_test(self, imgs, img_metas, rescale=False):
proposal_list = self.aug_test_rpn(
self.extract_feats(imgs), img_metas, self.test_cfg.rpn)
if not rescale:
for proposals, img_meta in zip(proposal_list, img_metas[0]):
img_shape = img_meta['img_shape']
scale_factor = img_meta['scale_factor']
flip = img_meta['flip']
proposals[:, :4] = bbox_mapping(proposals[:, :4], img_shape,
scale_factor, flip)
# TODO: remove this restriction
return proposal_list[0].cpu().numpy()