Functions — github.com/WongKinYiu/PyTorch

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Functions262 in github.com/WongKinYiu/PyTorch_YOLOv4

⨍ Functions 262◇ Types & classes 46

↓ 1 callersFunctioninit_torch_seeds

(seed=0)

utils/torch_utils.py:31

↓ 1 callersFunctionkmean_anchors

Creates kmeans-evolved anchors from training dataset Arguments: path: path to dataset *.yaml, or a loaded dataset n:

utils/autoanchor.py:55

↓ 1 callersFunctionlabels_to_class_weights

(labels, nc=80)

utils/general.py:103

↓ 1 callersFunctionlabels_to_image_weights

(labels, nc=80, class_weights=np.ones(80))

utils/general.py:122

↓ 1 callersFunctionload_classes

(path)

test.py:23

↓ 1 callersFunctionload_classes

(path)

detect.py:24

↓ 1 callersFunctionload_classifier

(name='resnet101', n=2)

utils/torch_utils.py:164

↓ 1 callersFunctionmake_divisible

(x, divisor)

utils/general.py:98

↓ 1 callersFunctionoutput_to_target

(output, width, height)

utils/plots.py:89

↓ 1 callersFunctionparse_model_cfg

(path)

utils/parse_config.py:6

↓ 1 callersFunctionplot_evolution

(yaml_file='data/hyp.finetune.yaml')

utils/plots.py:297

↓ 1 callersFunctionplot_labels

(labels, save_dir='')

utils/plots.py:265

↓ 1 callersFunctionplot_results

(start=0, stop=0, bucket='', id=(), labels=(), save_dir='')

utils/plots.py:344

↓ 1 callersFunctionprint_mutation

(hyp, results, yaml_file='hyp_evolved.yaml', bucket='')

utils/general.py:372

↓ 1 callersFunctionsave_weights

(self, path='model.weights', cutoff=-1)

models/models.py:621

↓ 1 callersFunctionscale_coords

(img1_shape, coords, img0_shape, ratio_pad=None)

utils/utils.py:143

↓ 1 callersFunctionsmooth_BCE

(eps=0.1)

utils/loss.py:10

↓ 1 callersFunctionsmooth_BCE

(eps=0.1)

utils/utils.py:368

↓ 1 callersFunctionsparsity

(model)

utils/torch_utils.py:99

↓ 1 callersMethodupdate_attr

(self, model, include=(), exclude=('process_group', 'reducer'))

utils/torch_utils.py:238

Method__getitem__

(self, index)

utils/datasets.py:544

Method__getitem__

(self, index)

utils/datasets.py:827

utils/google_utils.py:99

(self, layers, weight=False)

utils/layers.py:85

Method__init__

(self, in_ch, out_ch, k=(3, 5, 7), stride=1, dilation=1, bias=True, method='equal_params')

utils/layers.py:117

Method__init__

Args: modulation (bool, optional): If True, Modulated Defomable Convolution (Deformable ConvNets v2).

(self, model, decay=0.9999, updates=0)

utils/torch_utils.py:216

Method__init__

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

utils/utils.py:340

Method__init__

(self, *args, **kwargs)

utils/datasets.py:117

Method__init__

(self, sampler)

utils/datasets.py:136

Method__init__

(self, pipe='0', img_size=640)

utils/datasets.py:226

Method__init__

(self, sources='streams.txt', img_size=640)

utils/datasets.py:283

Method__init__

(self, path, img_size=640, batch_size=16, augment=False, hyp=None, rect=False, image_weights=False,

utils/datasets.py:356

Method__init__

(self, path, img_size=640, batch_size=16, augment=False, hyp=None, rect=False, image_weights=False,

utils/datasets.py:639

Method__init__

(self, c1, k=3)

utils/activations.py:66

Method__init__

(self, params, lr=1e-3, betas=(0.9, 0.999), final_lr=0.1, gamma=1e-3, eps=1e-8, weight_decay=

utils/adabound.py:141

Method__init__

(self, anchors, nc, img_size, yolo_index, layers, stride)

models/models.py:261

Method__init__

(self, anchors, nc, img_size, yolo_index, layers, stride)

models/models.py:354

Method__iter__

(self)

utils/datasets.py:125

Method__iter__

(self)

utils/datasets.py:139

Method__iter__

(self)

utils/datasets.py:239

Method__iter__

(self)

utils/datasets.py:328

Method__len__

(self)

utils/datasets.py:122

Method__len__

(self)

utils/datasets.py:221

Method__len__

(self)

utils/datasets.py:278

Method__len__

(self)

utils/datasets.py:351

Method__len__

(self)

utils/datasets.py:535

Method__len__

(self)

utils/datasets.py:818

Method__next__

(self)

utils/datasets.py:178

Method__next__

(self)

utils/datasets.py:243

Method__next__

(self)

utils/datasets.py:332

Method__setstate__

(self, state)

utils/adabound.py:161

Method_set_lr

(module, grad_input, grad_output)

utils/layers.py:216

Functionap_per_class

Compute the average precision, given the recall and precision curves. Source: https://github.com/rafaelpadilla/Object-Detection-Metrics. # Ar

utils/utils.py:167

Functionapply_classifier

(x, model, img, im0)

utils/utils.py:796

Functionattempt_download

(weights)

models/models.py:661

Functionattempt_load

(weights, map_location=None)

utils/google_utils.py:39

utils/activations.py:30

Methodbackward

(ctx, grad_output)

utils/activations.py:54

Functionbutter_lowpass_filtfilt

(data, cutoff=1500, fs=50000, order=5)

utils/plots.py:43

Functioncheck_anchors

(dataset, model, thr=4.0, imgsz=640)

utils/autoanchor.py:21

Functioncheck_git_status

()

utils/utils.py:35

Functioncoco80_to_coco91_class

()

utils/utils.py:91

Functioncoco_class_count

(path='../coco/labels/train2014/')

utils/utils.py:626

Functioncoco_class_weights

()

utils/utils.py:77

Functioncoco_only_people

(path='../coco/labels/train2017/')

utils/utils.py:637

Functioncoco_single_class_labels

(path='../coco/labels/train2014/', label_class=43)

utils/utils.py:676

Methodcollate_fn

(batch)

utils/datasets.py:631

Methodcollate_fn

(batch)

utils/datasets.py:914

(cfg='cfg/yolov3-spp.cfg', weights='weights/yolov3-spp.weights', saveto='converted.weights')

models/models.py:647

Functioncreate_backbone

(f='weights/last.pt')

utils/utils.py:612

Functioncreate_dataloader9

(path, imgsz, batch_size, stride, opt, hyp=None, augment=False, cache=False, pad=0.0, rect=False,

utils/datasets.py:86

Functioncrop_images_random

(path='../images/', scale=0.50)

utils/utils.py:653

Functioncutout

(image, labels)

utils/datasets.py:1235

Functionfind_modules

(model, mclass=nn.Conv2d)

utils/torch_utils.py:94

Functionflatten_recursive

(path='../coco128')

utils/datasets.py:1288

(self, x, augment=False)

utils/google_utils.py:102

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