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github.com/amazon-science/siam-mot
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Functions
255 in github.com/amazon-science/siam-mot
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Functions
255
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Types & classes
53
Method
__init__
(self, video_file, frame_idxs=None)
demos/video_iterator.py:48
Method
__init__
(self, video_folder, frame_idxs=None)
demos/video_iterator.py:94
Method
__init__
(self, gpu_id=0, track_class=None, vis_generator=None,
demos/demo_inference.py:23
Method
__init__
vis_height is the resolution of output frame
demos/utils/vis_generator.py:12
Method
__init__
(self, fps=None, dump_video=False, out_path=None, file_name=None)
demos/utils/vis_writer.py:12
Method
__len__
(self)
siammot/data/video_dataset.py:76
Method
__len__
(self)
siammot/data/image_dataset.py:182
Method
__len__
(self)
siammot/data/build_inference_data_loader.py:47
Method
__repr__
(self)
siammot/data/adapters/augmentation/build_augmentation.py:79
Method
_eval_det_ap
(self)
siammot/engine/inferencer.py:96
Method
_filter
(self, entity: AnnoEntity, ignored_gt_entities=None)
siammot/data/adapters/handler/data_filtering.py:66
Method
_filter
(self, entity: AnnoEntity, ignored_gt_entities=None)
siammot/data/adapters/handler/data_filtering.py:88
Method
_filter
(self, entity: AnnoEntity, ignored_gt_entities=None)
siammot/data/adapters/handler/data_filtering.py:121
Method
activate_tracks
(self, track_id)
siammot/modelling/track_head/track_utils.py:240
Function
build_dla_fpn_backbone
(cfg)
siammot/modelling/backbone/backbone_ext.py:16
Method
classes
(self)
siammot/data/image_dataset.py:191
Function
dla60_res2net
(dcn_config, feature_only=True, batch_norm=FrozenBatchNorm2d)
siammot/modelling/backbone/dla.py:345
Function
dla_102
(dcn_config, feature_only=True, batch_norm=FrozenBatchNorm2d)
siammot/modelling/backbone/dla.py:357
Function
dla_169
(dcn_config, feature_only=True, batch_norm=FrozenBatchNorm2d)
siammot/modelling/backbone/dla.py:367
Function
dla_34
(dcn_config, feature_only=True, batch_norm=FrozenBatchNorm2d)
siammot/modelling/backbone/dla.py:307
Function
dla_46_c
(dcn_config, feature_only=True, batch_norm=FrozenBatchNorm2d)
siammot/modelling/backbone/dla.py:316
Function
dla_46_xc
(dcn_config, feature_only=True, batch_norm=FrozenBatchNorm2d)
siammot/modelling/backbone/dla.py:325
Function
dla_60
(dcn_config, feature_only=True, batch_norm=FrozenBatchNorm2d)
siammot/modelling/backbone/dla.py:336
Function
evaluate_recall
:param gt: groundtruth entities for a frame :param pred: prediction entities for a frame :param iou_thresh:
siammot/eval/eval_utils.py:8
Method
filter
(self, entity:AnnoEntity, ignored_gt_entities=None)
siammot/data/adapters/handler/data_filtering.py:30
Method
forward
(self, images, targets=None, given_detection=None)
siammot/modelling/rcnn.py:41
Method
forward
(self, features, proposals, targets=None, track_memory=None, given_detection=None)
siammot/modelling/roi_heads.py:21
Method
forward
(self, x, residual=None)
siammot/modelling/backbone/dla.py:43
Method
forward
(self, x, residual=None)
siammot/modelling/backbone/dla.py:87
Method
forward
(self, x, residual=None)
siammot/modelling/backbone/dla.py:143
Method
forward
(self, *x)
siammot/modelling/backbone/dla.py:181
Method
forward
(self, x, residual=None, children=None)
siammot/modelling/backbone/dla.py:225
Method
forward
(self, x)
siammot/modelling/backbone/dla.py:289
Method
forward
The solver is to merge predictions from detection branch as well as from track branch. The goal is to assign an unique track id to bo
siammot/modelling/track_head/track_solver.py:36
Method
forward
(self, features, proposals=None, targets=None, track_memory=None)
siammot/modelling/track_head/track_head.py:18
Method
forward
(self, pred, target, weight=None)
siammot/modelling/track_head/EMM/track_loss.py:34
Method
forward
(self, x, proposals, sr=None)
siammot/modelling/track_head/EMM/feature_extractor.py:34
Method
forward
(self, x)
siammot/modelling/track_head/EMM/feature_extractor.py:62
Method
forward
Arguments: x (list[Tensor]): feature maps for each level boxes (list[BoxList]): boxes to be used to perform the pooli
siammot/modelling/track_head/EMM/sr_pool.py:53
Method
forward
forward functions of the tracker :param features: raw FPN feature maps from feature backbone :param boxes: template bounding
siammot/modelling/track_head/EMM/track_core.py:28
Method
forward
Arguments: features (list[Tensor]): feature-maps from possibly several levels proposals (list[BoxList]): proposal box
siammot/modelling/box_head/box_head.py:23
Method
forward
Arguments: x (tuple[tensor, tensor]): x contains the class logits and the box_regression from the model.
siammot/modelling/box_head/inference.py:46
Method
forward
Arguments: x (list[Tensor]): feature maps for each feature level. Returns: results (tuple[Tensor]): feature m
siammot/operator_patch/fpn_patch.py:29
Method
forward_for_single_feature_map
(self, anchors, objectness, box_regression)
siammot/operator_patch/rpn_patch.py:15
Method
get_im_aspect_ratio
(self)
siammot/data/image_dataset.py:194
Method
get_img_info
(self, index)
siammot/data/image_dataset.py:185
Method
kill_track
Kill a track
siammot/modelling/track_head/track_utils.py:210
Function
make_emm_target_sampler
(cfg, track_utils )
siammot/modelling/track_head/EMM/target_sampler.py:290
Function
make_rpn_postprocessor
(config, rpn_box_coder, is_train)
siammot/operator_patch/rpn_patch.py:63
Method
normalize_regression_outputs
(src_bbox, regression_outputs)
siammot/modelling/track_head/EMM/track_loss.py:109
Method
shuffle_feature_tensor
(x)
siammot/modelling/track_head/track_utils.py:38
Function
split_func
(sample)
siammot/data/ingestion/ingest_mot.py:175
Method
video_len
(self)
demos/video_iterator.py:32
Function
xcorr_fast
group conv2d to calculate cross correlation, fast version
siammot/modelling/track_head/EMM/xcorr.py:26
Function
xcorr_slow
for loop to calculate cross correlation, slow version
siammot/modelling/track_head/EMM/xcorr.py:10
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