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Functions1,124 in github.com/FoundationVision/ByteTrack

↓ 3 callersFunctionjoint_stracks
(tlista, tlistb)
tutorials/transtrack/mot_online/byte_tracker.py:304
↓ 3 callersFunctionjoint_stracks
(tlista, tlistb)
tutorials/fairmot/byte_tracker.py:353
↓ 3 callersFunctionjoint_stracks
(tlista, tlistb)
tutorials/fairmot/tracker.py:415
↓ 3 callersFunctionjoint_stracks
(tlista, tlistb)
tutorials/ctracker/byte_tracker.py:293
↓ 3 callersFunctionjoint_stracks
(tlista, tlistb)
tutorials/motr/byte_tracker.py:289
↓ 3 callersMethodmark_lost
(self)
tutorials/ctracker/mot_online/basetrack.py:48
↓ 3 callersFunctionmkdir_if_missing
(d)
tools/interpolation.py:9
↓ 3 callersMethodnext
(self)
yolox/data/data_prefetcher.py:40
↓ 3 callersFunctionplot_tracking
(image, tlwhs, obj_ids, scores=None, frame_id=0, fps=0., ids2=None)
yolox/utils/visualize.py:52
↓ 3 callersMethodpost_process
(self, dets, meta)
tutorials/fairmot/tracker.py:206
↓ 3 callersMethodre_activate
(self, new_track, frame_id, new_id=False)
tutorials/qdtrack/tracker_reid_motion.py:76
↓ 3 callersMethodre_activate
(self, new_track, frame_id, new_id=False)
tutorials/jde/tracker.py:72
↓ 3 callersMethodre_activate
(self, new_track, frame_id, new_id=False)
tutorials/cstrack/tracker.py:80
↓ 3 callersMethodre_activate
(self, new_track, frame_id, new_id=False)
tutorials/fairmot/tracker.py:86
↓ 3 callersFunctionread_results
(filename, data_type: str, is_gt=False, is_ignore=False)
yolox/tracking_utils/io.py:33
↓ 3 callersFunctionread_results
(filename, data_type: str, is_gt=False, is_ignore=False)
yolox/evaluators/evaluation.py:117
↓ 3 callersFunctionrun_each_dataset
(model_dir, retinanet, dataset_path, subset, cur_dataset)
tutorials/ctracker/test.py:135
↓ 3 callersMethodsave_ckpt
(self, ckpt_name, update_best_ckpt=False)
yolox/core/trainer.py:315
↓ 3 callersMethodset_feature
(self, feature)
yolox/motdt_tracker/motdt_tracker.py:43
↓ 3 callersMethodtic
(self)
yolox/tracking_utils/timer.py:15
↓ 3 callersMethodto_tlwh
Get current position in bounding box format `(top left x, top left y, width, height)`. Returns ------- ndarray
yolox/deepsort_tracker/track.py:80
↓ 3 callersMethodto_xyah
Convert bounding box to format `(center x, center y, aspect ratio, height)`, where the aspect ratio is `width / height`.
yolox/deepsort_tracker/detection.py:39
↓ 3 callersFunctionunzip_objs
(objs)
yolox/tracking_utils/io.py:109
↓ 3 callersFunctionunzip_objs
(objs)
yolox/evaluators/evaluation.py:193
↓ 3 callersMethodupdate
Processes the image frame and finds bounding box(detections). Associates the detection with corresponding tracklets and also hand
tutorials/jde/byte_tracker.py:158
↓ 3 callersMethodupdate
(self, dt_instances: Instances)
tutorials/motr/eval.py:171
↓ 3 callersMethodupdate_features
(self, feat)
tutorials/qdtrack/tracker_reid_motion.py:33
↓ 3 callersMethodupdate_features
(self, feat)
tutorials/jde/tracker.py:30
↓ 3 callersMethodupdate_features
(self, feat)
tutorials/cstrack/tracker.py:39
↓ 3 callersMethodupdate_features
(self, feat)
tutorials/fairmot/tracker.py:42
↓ 2 callersMethod__init__
(self, n_parts=8)
yolox/motdt_tracker/reid_model.py:201
↓ 2 callersMethod__init__
(self, input_dimension, mosaic=True)
yolox/data/datasets/datasets_wrapper.py:70
↓ 2 callersMethod__init__
Initializes the model. Parameters: backbone: torch module of the backbone to be used. See backbone.py transformer: to
tutorials/motr/motr.py:369
↓ 2 callersMethod__init__
Initializes the model. Parameters: backbone: torch module of the backbone to be used. See backbone.py transformer: to
tutorials/motr/motr_det.py:369
↓ 2 callersMethod__set_input_dim
This function randomly changes the the input dimension of the dataset.
yolox/data/samplers.py:33
↓ 2 callersFunction_find_free_port
Find an available port of current machine / node.
yolox/core/launch.py:25
↓ 2 callersMethod_forward_single_image
(self, samples, track_instances: Instances)
tutorials/motr/motr.py:487
↓ 2 callersMethod_forward_single_image
(self, samples, track_instances: Instances)
tutorials/motr/motr_det.py:487
↓ 2 callersFunction_get_clones
(module, N)
tutorials/motr/motr.py:364
↓ 2 callersFunction_get_clones
(module, N)
tutorials/motr/motr_det.py:364
↓ 2 callersMethod_make_embedding
(self, filters_list, in_filters)
yolox/models/yolo_fpn.py:41
↓ 2 callersFunction_pad_to_largest_tensor
Returns: list[int]: size of the tensor, on each rank Tensor: padded tensor that has the max size
yolox/utils/dist.py:126
↓ 2 callersFunction_serialize_to_tensor
(data, group)
yolox/utils/dist.py:108
↓ 2 callersMethodbbox_overlaps_py
determine overlaps between boxes and query_boxes :param boxes: n * 4 bounding boxes :param query_boxes: k * 4 bounding boxes
tutorials/trades/tracker.py:266
↓ 2 callersFunctionbox_candidates
(box1, box2, wh_thr=2, ar_thr=20, area_thr=0.2)
yolox/data/data_augment.py:39
↓ 2 callersMethodchange_input_dim
This function will compute a new size and update it on the next mini_batch. Args: multiple (int or tuple, optional): values to mu
yolox/data/dataloading.py:123
↓ 2 callersMethodclear
(self)
yolox/utils/metric.py:94
↓ 2 callersFunctionconvert_bbox_to_z
Takes a bounding box in the form [x1,y1,x2,y2] and returns z in the form [x,y,s,r] where x,y is the centre of the box and s is the scale/area a
yolox/sort_tracker/sort.py:55
↓ 2 callersFunctionconvert_x_to_bbox
Takes a bounding box in the centre form [x,y,s,r] and returns it in the form [x1,y1,x2,y2] where x1,y1 is the top left and x2,y2 is the bottom
yolox/sort_tracker/sort.py:70
↓ 2 callersFunctiondraw_bboxes
(ori_img, bbox, identities=None, offset=(0, 0), cvt_color=False)
tutorials/motr/eval.py:97
↓ 2 callersFunctioneval_mota
(data_root, txt_path)
tools/interpolation.py:14
↓ 2 callersMethodgating_distance
Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If
yolox/tracker/kalman_filter.py:228
↓ 2 callersMethodgating_distance
Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If
tutorials/centertrack/mot_online/kalman_filter.py:227
↓ 2 callersMethodgating_distance
Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If
tutorials/trades/mot_online/kalman_filter.py:210
↓ 2 callersMethodgating_distance
Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If
tutorials/qdtrack/mot_online/kalman_filter.py:227
↓ 2 callersMethodgating_distance
Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If
tutorials/transtrack/mot_online/kalman_filter.py:228
↓ 2 callersMethodgating_distance
Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If
tutorials/ctracker/mot_online/kalman_filter.py:227
↓ 2 callersMethodgating_distance
Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If
tutorials/motr/mot_online/kalman_filter.py:210
↓ 2 callersFunctionget_args_parser
()
tutorials/transtrack/main_track.py:33
↓ 2 callersMethodget_assignments
( self, batch_idx, num_gt, total_num_anchors, gt_bboxes_per_image,
yolox/models/yolo_head.py:437
↓ 2 callersFunctionget_exp_by_file
(exp_file)
yolox/exp/build.py:10
↓ 2 callersMethodget_filtered_meter
(self, filter_key="time")
yolox/utils/metric.py:109
↓ 2 callersFunctiongreedy_assignment
(dist, thresh=1e16)
tutorials/centertrack/tracker.py:189
↓ 2 callersFunctiongreedy_assignment
(dist, thresh=1e16)
tutorials/trades/tracker.py:290
↓ 2 callersFunctionhflip
(image, target)
tutorials/motr/transforms.py:219
↓ 2 callersMethodincrement_age
(self)
yolox/deepsort_tracker/track.py:105
↓ 2 callersMethodinference
(self, img, timer)
tools/demo_track.py:147
↓ 2 callersMethodinitiate
Create track from unassociated measurement. Parameters ---------- measurement : ndarray Bounding box coordinates
tutorials/qdtrack/mot_online/kalman_filter.py:54
↓ 2 callersFunctioniou_distance
Compute cost based on IoU :type atracks: list[STrack] :type btracks: list[STrack] :rtype cost_matrix np.ndarray
tutorials/transtrack/mot_online/matching.py:73
↓ 2 callersFunctionious
Compute cost based on IoU :type atlbrs: list[tlbr] | np.ndarray :type atlbrs: list[tlbr] | np.ndarray :rtype ious np.ndarray
yolox/tracker/matching.py:53
↓ 2 callersFunctionis_parallel
check if model is in parallel mode.
yolox/utils/ema.py:11
↓ 2 callersFunctionmake_transforms_for_mot17
(image_set, args=None)
tutorials/motr/joint.py:202
↓ 2 callersMethodmark_lost
(self)
tutorials/qdtrack/mot_online/basetrack.py:48
↓ 2 callersMethodmark_missed
Mark this track as missed (no association at the current time step).
yolox/deepsort_tracker/track.py:139
↓ 2 callersMethodmark_removed
(self)
yolox/motdt_tracker/basetrack.py:52
↓ 2 callersMethodmark_removed
(self)
yolox/tracker/basetrack.py:51
↓ 2 callersMethodmark_removed
(self)
tutorials/centertrack/mot_online/basetrack.py:51
↓ 2 callersMethodmark_removed
(self)
tutorials/trades/mot_online/basetrack.py:51
↓ 2 callersMethodmark_removed
(self)
tutorials/transtrack/mot_online/basetrack.py:51
↓ 2 callersMethodnext_id
()
yolox/motdt_tracker/basetrack.py:36
↓ 2 callersMethodnext_id
()
yolox/tracker/basetrack.py:35
↓ 2 callersMethodnext_id
()
tutorials/centertrack/mot_online/basetrack.py:35
↓ 2 callersMethodnext_id
()
tutorials/trades/mot_online/basetrack.py:35
↓ 2 callersMethodnext_id
()
tutorials/transtrack/mot_online/basetrack.py:35
↓ 2 callersFunctionpad
(image, target, padding)
tutorials/motr/transforms.py:295
↓ 2 callersMethodpredict
(self)
yolox/motdt_tracker/motdt_tracker.py:52
↓ 2 callersMethodpreload
(self)
yolox/data/data_prefetcher.py:28
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8 d
yolox/deepsort_tracker/kalman_filter.py:114
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8
yolox/motdt_tracker/kalman_filter.py:126
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8
yolox/tracker/kalman_filter.py:126
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8
tutorials/centertrack/mot_online/kalman_filter.py:125
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8 d
tutorials/trades/mot_online/kalman_filter.py:114
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8
tutorials/qdtrack/mot_online/kalman_filter.py:125
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8
tutorials/transtrack/mot_online/kalman_filter.py:126
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8
tutorials/ctracker/mot_online/kalman_filter.py:125
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8 d
tutorials/motr/mot_online/kalman_filter.py:114
↓ 2 callersFunctionrandom_shift
(image, target, region, sizes)
tutorials/motr/transforms.py:102
↓ 2 callersMethodre_activate
(self, new_track, frame_id, new_id=False)
yolox/tracker/byte_tracker.py:59
↓ 2 callersMethodre_activate
(self, new_track, frame_id, new_id=False)
tutorials/centertrack/byte_tracker.py:59
↓ 2 callersMethodre_activate
(self, new_track, frame_id, new_id=False)
tutorials/trades/byte_tracker.py:60
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