Source code for mmdet.models.detectors.trident_faster_rcnn

from ..builder import DETECTORS
from .faster_rcnn import FasterRCNN

[docs]@DETECTORS.register_module() class TridentFasterRCNN(FasterRCNN): """Implementation of `TridentNet <>`_""" def __init__(self, backbone, rpn_head, roi_head, train_cfg, test_cfg, neck=None, pretrained=None, init_cfg=None): super(TridentFasterRCNN, self).__init__( backbone=backbone, neck=neck, rpn_head=rpn_head, roi_head=roi_head, train_cfg=train_cfg, test_cfg=test_cfg, pretrained=pretrained, init_cfg=init_cfg) assert self.backbone.num_branch == self.roi_head.num_branch assert self.backbone.test_branch_idx == self.roi_head.test_branch_idx self.num_branch = self.backbone.num_branch self.test_branch_idx = self.backbone.test_branch_idx
[docs] def simple_test(self, img, img_metas, proposals=None, rescale=False): """Test without augmentation.""" assert self.with_bbox, 'Bbox head must be implemented.' x = self.extract_feat(img) if proposals is None: num_branch = (self.num_branch if self.test_branch_idx == -1 else 1) trident_img_metas = img_metas * num_branch proposal_list = self.rpn_head.simple_test_rpn(x, trident_img_metas) else: proposal_list = proposals return self.roi_head.simple_test( x, proposal_list, trident_img_metas, rescale=rescale)
[docs] def aug_test(self, imgs, img_metas, rescale=False): """Test with augmentations. If rescale is False, then returned bboxes and masks will fit the scale of imgs[0]. """ x = self.extract_feats(imgs) num_branch = (self.num_branch if self.test_branch_idx == -1 else 1) trident_img_metas = [img_metas * num_branch for img_metas in img_metas] proposal_list = self.rpn_head.aug_test_rpn(x, trident_img_metas) return self.roi_head.aug_test( x, proposal_list, img_metas, rescale=rescale)
[docs] def forward_train(self, img, img_metas, gt_bboxes, gt_labels, **kwargs): """make copies of img and gts to fit multi-branch.""" trident_gt_bboxes = tuple(gt_bboxes * self.num_branch) trident_gt_labels = tuple(gt_labels * self.num_branch) trident_img_metas = tuple(img_metas * self.num_branch) return super(TridentFasterRCNN, self).forward_train(img, trident_img_metas, trident_gt_bboxes, trident_gt_labels)