MCPcopy Create free account

hub / github.com/SahilChachra/Video-Analytics-Dashboard / functions

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

↓ 151 callersMethodinfo
(self, verbose=False, img_size=640)
yolov5/models/yolo.py:228
↓ 34 callersFunctioncolorstr
(*input)
yolov5/utils/general.py:508
↓ 26 callersFunctiontime_sync
()
yolov5/utils/torch_utils.py:101
↓ 22 callersMethodrun
Loop through the registered actions and fire all callbacks Args: hook The name of the hook to check, defaults to all
yolov5/utils/callbacks.py:65
↓ 21 callersMethod__init__
(self, c1, c2, n=1, shortcut=True, g=1, e=0.5)
yolov5/models/common.py:129
↓ 21 callersMethodsave
(self, save_dir='runs/detect/exp')
yolov5/models/common.py:632
↓ 18 callersFunctioncheck_requirements
(requirements=ROOT / 'requirements.txt', exclude=(), install=True)
yolov5/utils/general.py:283
↓ 18 callersMethodplot
(self, normalize=True, save_dir='', names=())
yolov5/utils/metrics.py:174
↓ 18 callersMethodtolist
(self)
yolov5/models/common.py:654
↓ 13 callersMethod__init__
(self, w=None)
yolov5/models/tf.py:39
↓ 13 callersMethodlog
save the metrics to the logging dictionary arguments: log_dict (Dict) -- metrics/media to be logged in current step
yolov5/utils/loggers/wandb/wandb_utils.py:496
↓ 13 callersFunctionselect_device
(device='', batch_size=0, newline=True)
yolov5/utils/torch_utils.py:70
↓ 12 callersFunction_create
Creates or loads a YOLOv5 model Arguments: name (str): model name 'yolov5s' or path 'path/to/best.pt' pretrained (bool): load pre
yolov5/hubconf.py:14
↓ 12 callersFunctionincrement_path
(path, exist_ok=False, sep='', mkdir=False)
yolov5/utils/general.py:864
↓ 11 callersFunctionfile_size
(path)
yolov5/utils/general.py:223
↓ 11 callersMethodrectangle
(self, xy, fill=None, outline=None, width=1)
yolov5/utils/plots.py:119
↓ 11 callersFunctionxyxy2xywh
(x)
yolov5/utils/general.py:572
↓ 8 callersFunctionxywh2xyxy
(x)
yolov5/utils/general.py:582
↓ 7 callersFunctionprint_args
(name, opt)
yolov5/utils/general.py:162
↓ 7 callersFunctionscale_coords
(img1_shape, coords, img0_shape, ratio_pad=None)
yolov5/utils/general.py:648
↓ 7 callersMethodupdate
(self, model)
yolov5/utils/torch_utils.py:315
↓ 6 callersFunctioncheck_dataset
(data, autodownload=True)
yolov5/utils/general.py:395
↓ 6 callersFunctioncheck_img_size
(imgsz, s=32, floor=0)
yolov5/utils/general.py:319
↓ 6 callersFunctioncheck_version
(current='0.0.0', minimum='0.0.0', name='version ', pinned=False, hard=False, verbose=False)
yolov5/utils/general.py:270
↓ 6 callersFunctionde_parallel
(model)
yolov5/utils/torch_utils.py:165
↓ 6 callersFunctionemojis
(str='')
yolov5/utils/general.py:218
↓ 6 callersFunctionfitness
(x)
yolov5/utils/metrics.py:15
↓ 6 callersFunctionletterbox
(im, new_shape=(640, 640), color=(114, 114, 114), auto=True, scaleFill=False, scaleup=True, stride=32)
yolov5/utils/augmentations.py:91
↓ 5 callersFunctioncheck_file
(file, suffix='')
yolov5/utils/general.py:361
↓ 5 callersFunctioncheck_yaml
(file, suffix=('.yaml', '.yml'))
yolov5/utils/general.py:356
↓ 5 callersMethoddisplay
(self, pprint=False, show=False, save=False, crop=False, render=False, save_dir=Path(''))
yolov5/models/common.py:585
↓ 5 callersFunctionimg2label_paths
(img_paths)
yolov5/utils/datasets.py:372
↓ 5 callersMethodis_confirmed
Returns True if this track is confirmed.
deep_sort_pytorch/deep_sort/sort/track.py:163
↓ 5 callersFunctionmake_divisible
(x, divisor)
yolov5/utils/general.py:491
↓ 5 callersFunctionnon_max_suppression
Runs Non-Maximum Suppression (NMS) on inference results Returns: list of detections, on (n,6) tensor per image [xyxy, conf, cls]
yolov5/utils/general.py:676
↓ 5 callersMethodpredict
(self, inputs, tf_nms=False, agnostic_nms=False, topk_per_class=100, topk_all=100, iou_thres=0.45,
yolov5/models/tf.py:340
↓ 5 callersFunctionremove_prefix
(from_string, prefix=WANDB_ARTIFACT_PREFIX)
yolov5/utils/loggers/wandb/wandb_utils.py:32
↓ 4 callersFunctionattempt_download
(file, repo='ultralytics/yolov5')
yolov5/utils/downloads.py:43
↓ 4 callersFunctionattempt_load
(weights, map_location=None, inplace=True, fuse=True)
yolov5/models/experimental.py:90
↓ 4 callersFunctionmake_layers
(c_in, c_out, repeat_times, is_downsample=False)
deep_sort_pytorch/deep_sort/deep/model.py:44
↓ 4 callersFunctionmetric
(k)
yolov5/utils/autoanchor.py:35
↓ 4 callersFunctionsave_one_box
(xyxy, im, file='image.jpg', gain=1.02, pad=10, square=False, BGR=False, save=True)
yolov5/utils/plots.py:470
↓ 4 callersFunctionstrip_optimizer
(f='best.pt', s='')
yolov5/utils/general.py:770
↓ 4 callersMethodupdate
Perform Kalman filter measurement update step and update the feature cache. Parameters ---------- kf : kalman_filter.
deep_sort_pytorch/deep_sort/sort/track.py:129
↓ 3 callersMethod__init__
(self, n, weight=False)
yolov5/models/experimental.py:31
↓ 3 callersFunctionautopad
(k, p=None)
yolov5/models/common.py:31
↓ 3 callersMethodbackward
(ctx, grad_output)
yolov5/utils/activations.py:40
↓ 3 callersFunctionbox_iou
Return intersection-over-union (Jaccard index) of boxes. Both sets of boxes are expected to be in (x1, y1, x2, y2) format. Arguments:
yolov5/utils/metrics.py:244
↓ 3 callersMethodbox_label
(self, box, label='', color=(128, 128, 128), txt_color=(255, 255, 255))
yolov5/utils/plots.py:94
↓ 3 callersFunctioncheck_suffix
(file='yolov5s.pt', suffix=('.pt',), msg='')
yolov5/utils/general.py:345
↓ 3 callersFunctionclip_coords
(boxes, shape)
yolov5/utils/general.py:664
↓ 3 callersFunctioncreate_dataloader
(path, imgsz, batch_size, stride, single_cls=False, hyp=None, augment=False, cache=False, pad=0.0,
yolov5/utils/datasets.py:94
↓ 3 callersFunctiondetect
(weights=ROOT / 'yolov5s.pt', # model.pt path(s) source=ROOT / 'yolov5/data/images', # file/dir/URL/
deep_list.py:49
↓ 3 callersFunctionexport_onnx
(model, im, file, opset, train, dynamic, simplify, prefix=colorstr('ONNX:'))
yolov5/export.py:112
↓ 3 callersMethodframe_exists
Args: frame_id (int): Returns: bool: true if frame_id is recognized
deep_sort_pytorch/utils/json_logger.py:185
↓ 3 callersFunctionis_docker
()
yolov5/utils/general.py:188
↓ 3 callersMethodload_image
(self, i)
yolov5/utils/datasets.py:627
↓ 3 callersFunctionmake_layers
(c_in, c_out, repeat_times, is_downsample=False)
deep_sort_pytorch/deep_sort/deep/original_model.py:44
↓ 3 callersMethodmerge_from_file
(self, config_file)
deep_sort_pytorch/utils/parser.py:22
↓ 3 callersFunctionparse_opt
(known=False)
yolov5/train.py:454
↓ 3 callersFunctionplot_mc_curve
(px, py, save_dir='mc_curve.png', names=(), xlabel='Confidence', ylabel='Metric')
yolov5/utils/metrics.py:324
↓ 3 callersFunctionprint_results
(k, verbose=True)
yolov5/utils/autoanchor.py:97
↓ 3 callersFunctionrandom_perspective
(im, targets=(), segments=(), degrees=10, translate=.1, scale=.1, shear=10, perspective=0.0,
yolov5/utils/augmentations.py:124
↓ 3 callersFunctionread_results
(filename, data_type: str, is_gt=False, is_ignore=False)
deep_sort_pytorch/utils/io.py:57
↓ 3 callersFunctionrun
(data, weights=None, # model.pt path(s) batch_size=32, # batch size imgsz=640, # in
yolov5/val.py:96
↓ 3 callersFunctionset_logging
(name=None, verbose=VERBOSE)
yolov5/utils/general.py:75
↓ 3 callersMethodto_tlwh
Get current position in bounding box format `(top left x, top left y, width, height)`. Returns ------- ndarray
deep_sort_pytorch/deep_sort/sort/track.py:83
↓ 3 callersMethodto_xyah
Convert bounding box to format `(center x, center y, aspect ratio, height)`, where the aspect ratio is `width / height`.
deep_sort_pytorch/deep_sort/sort/detection.py:42
↓ 3 callersFunctiontorch_distributed_zero_first
Decorator to make all processes in distributed training wait for each local_master to do something.
yolov5/utils/torch_utils.py:34
↓ 3 callersFunctiontrain
(hyp, # path/to/hyp.yaml or hyp dictionary opt, device, callbacks )
yolov5/train.py:65
↓ 3 callersFunctionunzip_objs
(objs)
deep_sort_pytorch/utils/io.py:126
↓ 3 callersFunctionxywhn2xyxy
(x, w=640, h=640, padw=0, padh=0)
yolov5/utils/general.py:592
↓ 2 callersMethod__init__
(self, loss_fcn, gamma=1.5, alpha=0.25)
yolov5/utils/loss.py:37
↓ 2 callersMethod__init__
(self, c1, k=3)
yolov5/utils/activations.py:52
↓ 2 callersMethod_forward_once
(self, x, profile=False, visualize=False)
yolov5/models/yolo.py:142
↓ 2 callersMethodadd_label
(self, category, confidence)
deep_sort_pytorch/utils/json_logger.py:85
↓ 2 callersFunctionall_logging_disabled
source - https://gist.github.com/simon-weber/7853144 A context manager that will prevent any logging messages triggered during the body from bein
yolov5/utils/loggers/wandb/wandb_utils.py:551
↓ 2 callersFunctionanchor_fitness
(k)
yolov5/utils/autoanchor.py:93
↓ 2 callersMethodbbox_exists
Args: frame_id: bbox_id: Returns: bool: if bbox exists in frame bboxes list
deep_sort_pytorch/utils/json_logger.py:213
↓ 2 callersFunctionbbox_ioa
Returns the intersection over box2 area given box1, box2. Boxes are x1y1x2y2 box1: np.array of shape(4) box2: np.array of shape(n
yolov5/utils/metrics.py:269
↓ 2 callersFunctionbbox_rel
Calculates the relative bounding box from absolute pixel values.
graphs.py:6
↓ 2 callersFunctionbox_area
(box)
yolov5/utils/metrics.py:257
↓ 2 callersFunctioncheck_anchor_order
(m)
yolov5/utils/autoanchor.py:18
↓ 2 callersMethodcheck_and_upload_dataset
Check if the dataset format is compatible and upload it as W&B artifact arguments: opt (namespace)-- Commandline arguments f
yolov5/utils/loggers/wandb/wandb_utils.py:192
↓ 2 callersFunctioncheck_imshow
()
yolov5/utils/general.py:330
↓ 2 callersFunctioncheck_online
()
yolov5/utils/general.py:234
↓ 2 callersFunctioncheck_pil_font
(font=FONT, size=10)
yolov5/utils/plots.py:63
↓ 2 callersFunctioncheck_wandb_dataset
(data_file)
yolov5/utils/loggers/wandb/wandb_utils.py:43
↓ 2 callersFunctioncompute_color_for_labels
Simple function that adds fixed color depending on the class
deep_sort_pytorch/utils/draw.py:7
↓ 2 callersFunctioncopy_attr
(a, b, include=(), exclude=())
yolov5/utils/torch_utils.py:267
↓ 2 callersMethodcreate_dataset_table
Create and return W&B artifact containing W&B Table of the dataset. arguments: dataset -- instance of LoadImagesAndLabels cl
yolov5/utils/loggers/wandb/wandb_utils.py:391
↓ 2 callersMethoddic
(self)
deep_sort_pytorch/utils/json_logger.py:26
↓ 2 callersMethoddownload_dataset_artifact
download the model checkpoint artifact if the path starts with WANDB_ARTIFACT_PREFIX arguments: path -- path of the dataset
yolov5/utils/loggers/wandb/wandb_utils.py:262
↓ 2 callersFunctiondownload_one
(url, dir)
yolov5/utils/general.py:459
↓ 2 callersFunctiondraw_boxes
(img, bbox, identities=None, offset=(0, 0))
graphs.py:27
↓ 2 callersFunctionexif_transpose
Transpose a PIL image accordingly if it has an EXIF Orientation tag. Inplace version of https://github.com/python-pillow/Pillow/blob/master/s
yolov5/utils/datasets.py:68
↓ 2 callersFunctionexport_formats
()
yolov5/export.py:76
↓ 2 callersFunctionget_config
(config_file=None)
deep_sort_pytorch/utils/parser.py:30
↓ 2 callersFunctionget_hash
(paths)
yolov5/utils/datasets.py:45
↓ 2 callersFunctionget_run_info
(run_path)
yolov5/utils/loggers/wandb/wandb_utils.py:59
next →1–100 of 533, ranked by callers