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Functions89 in github.com/Koldim2001/TrafficAnalyzer

↓ 5 callersMethodupdate_image
(self, image: np.array)
nodes/FlaskServerVideoNode.py:49
↓ 4 callersMethodprocess
(self, frame_element: FrameElement, fps_counter=None)
nodes/ShowNode.py:46
↓ 4 callersMethodprocess
(self, frame_element: FrameElement)
nodes/TrackerInfoUpdateNode.py:26
↓ 4 callersMethodprocess
(self, frame_element: FrameElement)
nodes/CalcStatisticsNode.py:25
↓ 4 callersMethodprocess
(self, frame_element: FrameElement)
nodes/VideoSaverNode.py:21
↓ 4 callersMethodprocess
(self, frame_element: FrameElement)
nodes/DetectionTrackingNodes.py:39
↓ 4 callersMethodprocess
(self, frame_element: FrameElement)
nodes/KafkaProducerNode.py:29
↓ 4 callersMethodprocess
(self)
nodes/VideoReader.py:48
↓ 4 callersMethodtlwh_to_xyah
Convert bounding box to format `(center x, center y, aspect ratio, height)`, where the aspect ratio is `width / height`.
byte_tracker/byte_tracker_model.py:118
↓ 4 callersMethodupdate
Update a matched track :type new_track: STrack :type frame_id: int :type update_feature: bool :return:
byte_tracker/byte_tracker_model.py:73
↓ 3 callersFunctionjoint_stracks
(tlista, tlistb)
byte_tracker/byte_tracker_model.py:311
↓ 2 callersMethodgating_distance
Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If
byte_tracker/utils/kalman_filter.py:228
↓ 2 callersFunctionious
Compute cost based on IoU :type atlbrs: list[tlbr] | np.ndarray :type atlbrs: list[tlbr] | np.ndarray :rtype ious np.ndarray
byte_tracker/utils/matching.py:53
↓ 2 callersMethodmark_removed
(self)
byte_tracker/utils/basetrack.py:51
↓ 2 callersMethodnext_id
()
byte_tracker/utils/basetrack.py:35
↓ 2 callersMethodproject
Project state distribution to measurement space. Parameters ---------- mean : ndarray The state's mean vector (8
byte_tracker/utils/kalman_filter.py:126
↓ 2 callersMethodre_activate
(self, new_track, frame_id, new_id=False)
byte_tracker/byte_tracker_model.py:60
↓ 2 callersMethodrun
(self)
nodes/FlaskServerVideoNode.py:52
↓ 2 callersFunctionsub_stracks
(tlista, tlistb)
byte_tracker/byte_tracker_model.py:325
↓ 2 callersMethodtlbr_to_tlwh
(tlbr)
byte_tracker/byte_tracker_model.py:132
↓ 2 callersMethodtlwh_to_tlbr
(tlwh)
byte_tracker/byte_tracker_model.py:139
↓ 2 callersMethodto_xyah
(self)
byte_tracker/byte_tracker_model.py:127
↓ 2 callersMethodupdate
(self, timestamp)
elements/TrackElement.py:16
↓ 1 callersMethod_gen
(self)
nodes/FlaskServerVideoNode.py:39
↓ 1 callersMethod_get_results_dor_tracker
(self, results)
nodes/DetectionTrackingNodes.py:80
↓ 1 callersMethod_init_cv2_writer
Инициализирует cv2.VideoWriter для записи файла в нужном разрешении file_extention: Args: frame_width (int): ширина кадра записыв
nodes/VideoSaverNode.py:47
↓ 1 callersMethod_overlay_transparent_mask
(self, img, points, mask_color=(0, 255, 255), alpha=0.3)
nodes/ShowNode.py:276
↓ 1 callersMethodactivate
Start a new tracklet
byte_tracker/byte_tracker_model.py:46
↓ 1 callersMethodcalc_FPS
Производит рассчет FPS по нескольким кадрам видео. Returns: float: значение FPS.
utils_local/utils.py:35
↓ 1 callersMethodinitiate
Create track from unassociated measurement. Parameters ---------- measurement : ndarray Bounding box coordinates
byte_tracker/utils/kalman_filter.py:55
↓ 1 callersFunctionintersects_central_point
Функция определяет присутвие центральной точки bbox в области полигонов дорог Args: tracked_xyxy: координаты bbox polygons: слов
utils_local/utils.py:53
↓ 1 callersFunctioniou_distance
Compute cost based on IoU :type atracks: list[STrack] :type btracks: list[STrack] :rtype cost_matrix np.ndarray
byte_tracker/utils/matching.py:73
↓ 1 callersFunctionmain
(config)
main_stream_optimized_v2.py:88
↓ 1 callersFunctionmain
(config)
main_optimized.py:100
↓ 1 callersFunctionmain
(config)
main_stream_optimized.py:83
↓ 1 callersFunctionmain
(config)
main.py:14
↓ 1 callersMethodmark_lost
(self)
byte_tracker/utils/basetrack.py:48
↓ 1 callersMethodmulti_predict
(stracks)
byte_tracker/byte_tracker_model.py:34
↓ 1 callersMethodpredict
(self)
byte_tracker/byte_tracker_model.py:27
↓ 1 callersFunctionproc_proceessor
(queue_in: Queue, config: dict, frame_process: Process)
main_stream_optimized_v2.py:41
↓ 1 callersFunctionremove_duplicate_stracks
(stracksa, stracksb)
byte_tracker/byte_tracker_model.py:336
Method__call__
(self, *args)
nodes/FlaskServerVideoNode.py:14
Method__init__
(self, tlwh, score, class_name)
byte_tracker/byte_tracker_model.py:15
Method__init__
(self, fps, first_track_thresh, second_track_thresh, match_thresh, track_buffer, resize_width_height, mot20=Fa
byte_tracker/byte_tracker_model.py:149
Method__init__
(self)
byte_tracker/utils/kalman_filter.py:40
Method__init__
Счетчик FPS по ограниченным участкам видео (скользящему окну). Args: calc_time_perion_N_frames (int): количество фреймов окна под
utils_local/utils.py:26
Method__init__
(self, config)
nodes/ShowNode.py:13
Method__init__
(self, config: dict)
nodes/TrackerInfoUpdateNode.py:14
Method__init__
(self, config: dict)
nodes/CalcStatisticsNode.py:12
Method__init__
(self, config: dict)
nodes/VideoSaverNode.py:15
Method__init__
(self, config)
nodes/DetectionTrackingNodes.py:14
Method__init__
(self, config)
nodes/KafkaProducerNode.py:12
Method__init__
(self, action)
nodes/FlaskServerVideoNode.py:11
Method__init__
(self, config)
nodes/FlaskServerVideoNode.py:22
Method__init__
(self, config: dict)
nodes/VideoReader.py:17
Method__init__
( self, source: str, frame: np.ndarray, timestamp: float, frame_num: f
elements/FrameElement.py:6
Method__init__
( self, id: int, timestamp_first: float, start_road: int | None = None, )
elements/TrackElement.py:3
Method__init__
"Элемент конца видеопотока. Используется для возможности остановить все активные процессы в main_optimized.py по окончанию кадров. A
elements/VideoEndBreakElement.py:7
Method__repr__
(self)
byte_tracker/byte_tracker_model.py:144
Method_index
(self)
nodes/FlaskServerVideoNode.py:36
Function_indices_to_matches
(cost_matrix, indices, thresh)
byte_tracker/utils/matching.py:28
Method_update_page
(self)
nodes/FlaskServerVideoNode.py:46
Methodactivate
(self, *args)
byte_tracker/utils/basetrack.py:39
Functionembedding_distance
:param tracks: list[STrack] :param detections: list[BaseTrack] :param metric: :return: cost_matrix np.ndarray
byte_tracker/utils/matching.py:113
Methodend_frame
(self)
byte_tracker/utils/basetrack.py:31
Functionexec_and_print_status
(*args, **kwargs)
utils_local/utils.py:10
Functionfuse_iou
(cost_matrix, tracks, detections)
byte_tracker/utils/matching.py:159
Functionfuse_motion
(kf, cost_matrix, tracks, detections, only_position=False, lambda_=0.98)
byte_tracker/utils/matching.py:145
Functionfuse_score
(cost_matrix, detections)
byte_tracker/utils/matching.py:173
Functiongate_cost_matrix
(kf, cost_matrix, tracks, detections, only_position=False)
byte_tracker/utils/matching.py:132
Functionlinear_assignment
(cost_matrix, thresh)
byte_tracker/utils/matching.py:39
Functionmerge_matches
(m1, m2, shape)
byte_tracker/utils/matching.py:11
Methodmulti_predict
Run Kalman filter prediction step (Vectorized version). Parameters ---------- mean : ndarray The Nx8 dimensional m
byte_tracker/utils/kalman_filter.py:155
Methodpredict
Run Kalman filter prediction step. Parameters ---------- mean : ndarray The 8 dimensional mean vector of the obje
byte_tracker/utils/kalman_filter.py:88
Methodpredict
(self)
byte_tracker/utils/basetrack.py:42
Functionproc_frame_reader
(queue_out: Queue, config: dict, time_sleep_start: int)
main_stream_optimized_v2.py:21
Functionproc_frame_reader
(queue_out: Queue, config: dict, time_sleep_start: int)
main_stream_optimized.py:21
Functionproc_frame_reader_and_detection
(queue_out: Queue, config: dict, time_sleep_start: int)
main_optimized.py:20
Functionproc_proceessor
(queue_in: Queue, config: dict)
main_stream_optimized.py:41
Functionproc_show_node
(queue_in: Queue, config: dict)
main_optimized.py:68
Functionproc_tracker_update_and_calc
(queue_in: Queue, queue_out: Queue, config: dict)
main_optimized.py:41
Functionprofile_time
(func)
utils_local/utils.py:9
Methodstop_server
(self)
nodes/FlaskServerVideoNode.py:56
Methodtlbr
Convert bounding box to format `(min x, min y, max x, max y)`, i.e., `(top left, bottom right)`.
byte_tracker/byte_tracker_model.py:108
Methodtlwh
Get current position in bounding box format `(top left x, top left y, width, height)`.
byte_tracker/byte_tracker_model.py:95
Methodupdate
(self, output_results, xyxy=True)
byte_tracker/byte_tracker_model.py:170
Methodupdate
Run Kalman filter correction step. Parameters ---------- mean : ndarray The predicted state's mean vector (8 dime
byte_tracker/utils/kalman_filter.py:194
Methodupdate
(self, *args, **kwargs)
byte_tracker/utils/basetrack.py:45
Functionv_iou_distance
Compute cost based on IoU :type atracks: list[STrack] :type btracks: list[STrack] :rtype cost_matrix np.ndarray
byte_tracker/utils/matching.py:93