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Functions533 in github.com/SahilChachra/Video-Analytics-Dashboard

Methodprint
(self)
yolov5/utils/metrics.py:197
Functionprofile_idetection
(start=0, stop=0, labels=(), save_dir='')
yolov5/utils/plots.py:439
Functionprune
(model, amount=0.3)
yolov5/utils/torch_utils.py:196
Functionread_mot_results
(filename, is_gt, is_ignore)
deep_sort_pytorch/utils/io.py:84
Methodrender
(self)
yolov5/models/common.py:640
Functionreplicate
(im, labels)
yolov5/utils/augmentations.py:74
Functionrun
(**kwargs)
yolov5/train.py:632
Methodsave_summary
(summary, filename)
deep_sort_pytorch/utils/evaluation.py:99
Methodschedule_output_by_frames
saves as the number of frames quota increases higher. :param frames_quota: :param frame_counter: :param output_dir:
deep_sort_pytorch/utils/json_logger.py:358
Methodschedule_output_by_time
Notes: Creates folder and then periodically stores the jsons on that address. Args: output_dir (str): the di
deep_sort_pytorch/utils/json_logger.py:326
Methodset_start
(self)
deep_sort_pytorch/utils/json_logger.py:323
Methodset_top_k
(self, value)
deep_sort_pytorch/utils/json_logger.py:182
Functiontik_tok
keep track of time for each process. Args: func: Returns:
deep_sort_pytorch/utils/tools.py:21
Methodto_tlbr
Convert bounding box to format `(min x, min y, max x, max y)`, i.e., `(top left, bottom right)`.
deep_sort_pytorch/deep_sort/sort/detection.py:34
Methodto_tlbr
Get current position in bounding box format `(min x, miny, max x, max y)`. Returns ------- ndarray The bo
deep_sort_pytorch/deep_sort/sort/track.py:98
Methodtp_fp
(self)
yolov5/utils/metrics.py:168
Functiontry_except
(func)
yolov5/utils/general.py:146
Methodupdate
Run Kalman filter correction step. Parameters ---------- mean : ndarray The predicted state's mean vector (8 dime
deep_sort_pytorch/deep_sort/sort/kalman_filter.py:154
Methodupdate
Perform measurement update and track management. Parameters ---------- detections : List[deep_sort.detection.Detection]
deep_sort_pytorch/deep_sort/sort/tracker.py:63
Functionverify_image_label
(args)
yolov5/utils/datasets.py:886
Functionwh_iou
(wh1, wh2)
yolov5/utils/metrics.py:293
Methodwrap_frozen_graph
(gd, inputs, outputs)
yolov5/models/common.py:368
Functionwrite_results
(filename, results, data_type)
deep_sort_pytorch/utils/io.py:8
Functionyolov5l
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:88
Functionyolov5l6
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:113
Functionyolov5m
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:83
Functionyolov5m6
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:108
Functionyolov5n
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:73
Functionyolov5n6
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:98
Functionyolov5s
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:78
Functionyolov5s6
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:103
Functionyolov5x
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:93
Functionyolov5x6
(pretrained=True, channels=3, classes=80, autoshape=True, verbose=True, device=None)
yolov5/hubconf.py:118
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