Python mmdet.core.bbox_mapping() Examples
The following are 21
code examples of mmdet.core.bbox_mapping().
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Example #1
| Source File: rpn.py From mmdetection with Apache License 2.0 | 6 votes |
|
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()
Example #2
| Source File: rpn.py From AugFPN with Apache License 2.0 | 5 votes |
|
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()
Example #3
| Source File: point_rend_roi_head.py From mmdetection with Apache License 2.0 | 5 votes |
|
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
Example #4
| Source File: rpn.py From ttfnet with Apache License 2.0 | 5 votes |
|
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()
Example #5
| Source File: rpn.py From CenterNet with Apache License 2.0 | 5 votes |
|
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()
Example #6
| Source File: rpn.py From hrnet with MIT License | 5 votes |
|
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()
Example #7
| Source File: rpn.py From kaggle-imaterialist with MIT License | 5 votes |
|
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()
Example #8
| Source File: rpn.py From Feature-Selective-Anchor-Free-Module-for-Single-Shot-Object-Detection with Apache License 2.0 | 5 votes |
|
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()
Example #9
| Source File: rpn.py From Cascade-RPN with Apache License 2.0 | 5 votes |
|
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()
Example #10
| Source File: rpn.py From FoveaBox with Apache License 2.0 | 5 votes |
|
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()
Example #11
| Source File: rpn.py From Libra_R-CNN with Apache License 2.0 | 5 votes |
|
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()
Example #12
| Source File: rpn.py From Reasoning-RCNN with Apache License 2.0 | 5 votes |
|
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()
Example #13
| Source File: rpn.py From IoU-Uniform-R-CNN with Apache License 2.0 | 5 votes |
|
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()
Example #14
| Source File: rpn.py From RDSNet with Apache License 2.0 | 5 votes |
|
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()
Example #15
| Source File: rpn.py From Grid-R-CNN with Apache License 2.0 | 5 votes |
|
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()
Example #16
| Source File: rpn.py From kaggle-kuzushiji-recognition with MIT License | 5 votes |
|
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()
Example #17
| Source File: rpn.py From PolarMask with Apache License 2.0 | 5 votes |
|
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()
Example #18
| Source File: rpn.py From mmdetection_with_SENet154 with Apache License 2.0 | 5 votes |
|
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()
Example #19
| Source File: rpn.py From mmdetection-annotated with Apache License 2.0 | 5 votes |
|
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()
Example #20
| Source File: rpn.py From GCNet with Apache License 2.0 | 5 votes |
|
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()
Example #21
| Source File: rpn.py From AerialDetection with Apache License 2.0 | 5 votes |
|
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()
