Functions — github.com/WinstonJQ/YOLOv5-ROS

hub / github.com/WinstonJQ/YOLOv5-ROS / functions

Functions575 in github.com/WinstonJQ/YOLOv5-ROS

⨍ Functions 575◇ Types & classes 97 ↳ Endpoints 1

↓ 163 callersMethodinfo

(self, verbose=False, img_size=640)

src/yolov5/models/yolo.py:131

↓ 45 callersFunctioncolorstr

(*input)

src/yolov5/utils/general.py:632

↓ 34 callersMethodrun

Loop through the registered actions and fire all callbacks on main thread Args: hook: The name of the hook to check, def

src/yolov5/utils/callbacks.py:60

↓ 25 callersFunctioncheck_requirements

(requirements=ROOT / 'requirements.txt', exclude=(), install=True, cmds='')

src/yolov5/utils/general.py:345

↓ 24 callersMethod__init__

(self, c1, c2, n=1, shortcut=True, g=1, e=0.5)

src/yolov5/models/common.py:151

↓ 22 callersMethodsave

(self, labels=True, save_dir='runs/detect/exp')

src/yolov5/models/common.py:750

↓ 22 callersMethodtime

(self)

src/yolov5/utils/general.py:158

↓ 20 callersFunctionselect_device

(device='', batch_size=0, newline=True)

src/yolov5/utils/torch_utils.py:107

↓ 19 callersMethodtolist

(self)

src/yolov5/models/common.py:772

↓ 17 callersMethod__init__

(self, w=None)

src/yolov5/models/tf.py:40

↓ 15 callersMethodfrom_numpy

(self, x)

src/yolov5/models/common.py:550

↓ 15 callersMethodlog

save the metrics to the logging dictionary arguments: log_dict (Dict) -- metrics/media to be logged in current step

src/yolov5/utils/loggers/wandb/wandb_utils.py:515

↓ 14 callersFunctioncheck_version

(current='0.0.0', minimum='0.0.0', name='version ', pinned=False, hard=False, verbose=False)

src/yolov5/utils/general.py:332

↓ 14 callersMethodplot

(self, normalize=True, save_dir='', names=())

src/yolov5/utils/metrics.py:190

↓ 13 callersFunctionscale_coords

(img1_shape, coords, img0_shape, ratio_pad=None)

src/yolov5/utils/general.py:773

↓ 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

src/yolov5/hubconf.py:14

↓ 12 callersFunctionincrement_path

(path, exist_ok=False, sep='', mkdir=False)

src/yolov5/utils/general.py:997

↓ 12 callersMethodupdate

(self, model)

src/yolov5/utils/torch_utils.py:416

↓ 11 callersFunctioncheck_img_size

(imgsz, s=32, floor=0)

src/yolov5/utils/general.py:379

↓ 11 callersFunctionprint_args

(args: Optional[dict] = None, show_file=True, show_func=False)

src/yolov5/utils/general.py:204

↓ 9 callersMethodbox_label

(self, box, label='', color=(128, 128, 128), txt_color=(255, 255, 255))

src/yolov5/utils/plots.py:85

↓ 9 callersFunctionxywh2xyxy

(x)

src/yolov5/utils/general.py:706

↓ 9 callersFunctionxyxy2xywh

(x)

src/yolov5/utils/general.py:696

↓ 8 callersFunctioncheck_file

(file, suffix='')

src/yolov5/utils/general.py:422

↓ 8 callersFunctionletterbox

(im, new_shape=(640, 640), color=(114, 114, 114), auto=True, scaleFill=False, scaleup=True, stride=32)

src/yolov5/utils/augmentations.py:110

↓ 8 callersFunctionnon_max_suppression

Non-Maximum Suppression (NMS) on inference results to reject overlapping bounding boxes Returns: list of detections, on (n,6) tensor per

src/yolov5/utils/general.py:801

↓ 8 callersMethodresult

(self)

src/yolov5/utils/plots.py:127

↓ 8 callersMethodspin

Main loop to process queued images.

src/detect_new.py:129

↓ 7 callersFunctioncheck_dataset

(data, autodownload=True)

src/yolov5/utils/general.py:460

↓ 7 callersFunctioncheck_yaml

(file, suffix=('.yaml', '.yml'))

src/yolov5/utils/general.py:417

↓ 7 callersMethodrectangle

(self, xy, fill=None, outline=None, width=1)

src/yolov5/utils/plots.py:116

↓ 7 callersMethodwarmup

(self, imgsz=(1, 3, 640, 640))

src/yolov5/models/common.py:553

↓ 6 callersFunctionattempt_load

(weights, device=None, inplace=True, fuse=True)

src/yolov5/models/experimental.py:73

↓ 6 callersFunctionde_parallel

(model)

src/yolov5/utils/torch_utils.py:206

↓ 6 callersFunctionfitness

(x)

src/yolov5/utils/metrics.py:17

↓ 6 callersFunctionimg2label_paths

(img_paths)

src/yolov5/utils/dataloaders.py:373

↓ 6 callersFunctiontorch_distributed_zero_first

(local_rank: int)

src/yolov5/utils/torch_utils.py:88

↓ 5 callersMethoddisplay

(self, pprint=False, show=False, save=False, crop=False, render=False, labels=True, save_dir=Path(''))

src/yolov5/models/common.py:700

↓ 5 callersMethodlog_asset

(self, asset_path, **kwargs)

src/yolov5/utils/loggers/comet/__init__.py:195

↓ 5 callersFunctionmake_divisible

(x, divisor)

src/yolov5/utils/general.py:615

↓ 5 callersMethodpredict

(self, inputs, tf_nms=False, agnostic_nms=False,

src/yolov5/models/tf.py:421

↓ 5 callersFunctionremove_prefix

(from_string, prefix=WANDB_ARTIFACT_PREFIX)

src/yolov5/utils/loggers/wandb/wandb_utils.py:32

↓ 5 callersFunctiontime_sync

()

src/yolov5/utils/torch_utils.py:143

↓ 5 callersFunctionyaml_save

(file='data.yaml', data={})

src/yolov5/utils/general.py:554

↓ 4 callersFunctionattempt_download

(file, repo='ultralytics/yolov5', release='v6.2')

src/yolov5/utils/downloads.py:65

↓ 4 callersFunctionautopad

(k, p=None, d=1)

src/yolov5/models/common.py:31

↓ 4 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:

src/yolov5/utils/metrics.py:270

↓ 4 callersFunctionis_colab

()

src/yolov5/utils/general.py:71

↓ 4 callersMethodlog_parameters

(self, log_dict, **kwargs)

src/yolov5/utils/loggers/comet/__init__.py:192

↓ 4 callersFunctionmetric

(k)

src/yolov5/utils/autoanchor.py:37

↓ 3 callersMethod_forward_once

(self, x, profile=False, visualize=False)

src/yolov5/models/yolo.py:95

↓ 3 callersMethodbackward

(ctx, grad_output)

src/yolov5/utils/activations.py:43

↓ 3 callersFunctioncheck_font

(font=FONT, progress=False)

src/yolov5/utils/general.py:450

↓ 3 callersFunctioncheck_online

()

src/yolov5/utils/general.py:280

↓ 3 callersFunctioncheck_suffix

(file='yolov5s.pt', suffix=('.pt',), msg='')

src/yolov5/utils/general.py:406

↓ 3 callersFunctionclassify_transforms

(size=224)

src/yolov5/utils/augmentations.py:346

↓ 3 callersFunctionclip_coords

(boxes, shape)

src/yolov5/utils/general.py:789

↓ 3 callersFunctioncreate_classification_dataloader

(path, imgsz=224, batch_size=16,

src/yolov5/utils/dataloaders.py:1105

↓ 3 callersFunctioncreate_dataloader

(path, imgsz, batch_size, stride,

src/yolov5/utils/dataloaders.py:102

↓ 3 callersFunctionemojis

(str='')

src/yolov5/utils/general.py:251

↓ 3 callersFunctionexport_onnx

(model, im, file, opset, train, dynamic, simplify, prefix=colorstr('ONNX:'))

src/yolov5/export.py:129

↓ 3 callersFunctionfile_size

(path)

src/yolov5/utils/general.py:268

↓ 3 callersFunctionis_ascii

(s='')

src/yolov5/utils/general.py:60

↓ 3 callersMethodload_image

(self, i)

src/yolov5/utils/dataloaders.py:641

↓ 3 callersMethodlog_metrics

(self, log_dict, **kwargs)

src/yolov5/utils/loggers/comet/__init__.py:189

↓ 3 callersFunctionparse_opt

()

src/yolov5/utils/benchmarks.py:138

↓ 3 callersFunctionparse_opt

(known=False)

src/yolov5/classify/train.py:269

↓ 3 callersFunctionplot_images

(images, targets, paths=None, fname='images.jpg', names=None, max_size=1920, max_subplots=16)

src/yolov5/utils/plots.py:192

↓ 3 callersFunctionplot_mc_curve

(px, py, save_dir=Path('mc_curve.png'), names=(), xlabel='Confidence', ylabel='Metric')

src/yolov5/utils/metrics.py:348

↓ 3 callersFunctionprint_results

(k, verbose=True)

src/yolov5/utils/autoanchor.py:99

↓ 3 callersFunctionrandom_perspective

(im, targets=(), segments=(), degrees=10,

src/yolov5/utils/augmentations.py:143

↓ 3 callersFunctionrun

( data, weights=None, # model.pt path(s) batch_size=32, # batch size imgsz=6

src/yolov5/val.py:98

↓ 3 callersFunctionstrip_optimizer

(f='best.pt', s='')

src/yolov5/utils/general.py:906

↓ 3 callersMethodtext

(self, xy, text, txt_color=(255, 255, 255), anchor='top')

src/yolov5/utils/plots.py:120

↓ 3 callersFunctiontrain

(opt, device)

src/yolov5/classify/train.py:55

↓ 3 callersFunctionxywhn2xyxy

(x, w=640, h=640, padw=0, padh=0)

src/yolov5/utils/general.py:716

↓ 3 callersFunctionyaml_load

(file='data.yaml')

src/yolov5/utils/general.py:548

↓ 2 callersMethod__init__

(self, loss_fcn, gamma=1.5, alpha=0.25)

src/yolov5/utils/loss.py:37

↓ 2 callersMethod__init__

(self, path, img_size=640, stride=32, auto=True, transforms=None, vid_stride=1)

src/yolov5/utils/dataloaders.py:190

↓ 2 callersMethod__init__

(self, half=False)

src/yolov5/utils/augmentations.py:387

↓ 2 callersMethod__init__

(self, c1, k=3)

src/yolov5/utils/activations.py:55

↓ 2 callersMethod__init__

(self, nc=80, anchors=(), ch=(), inplace=True)

src/yolov5/models/yolo.py:43

↓ 2 callersMethod__init__

(self, n, weight=False)

src/yolov5/models/experimental.py:16

↓ 2 callersMethod_new_video

(self, path)

src/yolov5/utils/dataloaders.py:266

↓ 2 callersFunctionactivations

(act=nn.SiLU)

src/yolov5/models/tf.py:508

↓ 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

src/yolov5/utils/loggers/wandb/wandb_utils.py:573

↓ 2 callersFunctionamp_allclose

(model, im)

src/yolov5/utils/general.py:524

↓ 2 callersFunctionanchor_fitness

(k)

src/yolov5/utils/autoanchor.py:95

↓ 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

src/yolov5/utils/metrics.py:291

↓ 2 callersFunctionbox_area

(box)

src/yolov5/utils/metrics.py:265

↓ 2 callersFunctioncheck_anchor_order

(m)

src/yolov5/utils/autoanchor.py:19

↓ 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

src/yolov5/utils/loggers/wandb/wandb_utils.py:198

↓ 2 callersFunctioncheck_git_status

(repo='ultralytics/yolov5', branch='master')

src/yolov5/utils/general.py:301

↓ 2 callersFunctioncheck_imshow

()

src/yolov5/utils/general.py:391

↓ 2 callersFunctioncheck_wandb_dataset

(data_file)

src/yolov5/utils/loggers/wandb/wandb_utils.py:43

↓ 2 callersFunctioncopy_attr

(a, b, include=(), exclude=())

src/yolov5/utils/torch_utils.py:308

↓ 2 callersMethodcreate_dataset_table

Create and return W&B artifact containing W&B Table of the dataset. arguments: dataset -- instance of LoadImagesAndLabels cl

src/yolov5/utils/loggers/wandb/wandb_utils.py:398

↓ 2 callersFunctiondownload

(url, dir='.', unzip=True, delete=True, curl=False, threads=1, retry=3)

src/yolov5/utils/general.py:566

↓ 2 callersMethoddownload_dataset_artifact

download the model checkpoint artifact if the path starts with WANDB_ARTIFACT_PREFIX arguments: path -- path of the dataset

src/yolov5/utils/loggers/wandb/wandb_utils.py:267

↓ 2 callersFunctiondownload_model_checkpoint

(opt, experiment)

src/yolov5/utils/loggers/comet/comet_utils.py:19

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