Functions — github.com/GengDavid/pytorch-cpn

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Functions95 in github.com/GengDavid/pytorch-cpn

⨍ Functions 95 ◇ Types & classes 15

↓ 48 callersMethodappend

(self, numbers)

utils/logger.py:60

↓ 7 callersFunctionim_to_torch

(img)

utils/imutils.py:14

↓ 6 callersFunctionto_numpy

(tensor)

utils/misc.py:9

↓ 5 callersFunctionim_to_numpy

(img)

utils/imutils.py:9

↓ 4 callersMethod_make_layer

(self, block, planes, blocks, stride=1)

networks/resnet.py:119

↓ 4 callersFunctiongauss

(x, a, b, c, d=0)

utils/imutils.py:49

↓ 4 callersFunctiongenerate_heatmap

(heatmap, pt, sigma)

utils/imutils.py:37

↓ 4 callersFunctionisdir

(dirname)

utils/osutils.py:14

↓ 4 callersFunctionisfile

(fname)

utils/osutils.py:11

↓ 4 callersFunctionjoin

(path, *paths)

utils/osutils.py:17

↓ 4 callersFunctionmkdir_p

(dir_path)

utils/osutils.py:4

↓ 3 callersMethodclose

(self)

utils/logger.py:78

↓ 3 callersFunctionget_preds

get predictions from score maps in torch Tensor return type: torch.LongTensor

utils/evaluation.py:11

↓ 3 callersMethodplot

(self, names=None)

utils/logger.py:69

↓ 3 callersFunctiontransform

(pt, center, scale, res, invert=0, rot=0)

utils/transforms.py:107

↓ 2 callersMethod__init__

(self, block, layers, num_classes=1000)

networks/resnet.py:98

↓ 2 callersFunctionadd_pypath

(path)

256.192.model/test_config.py:6

↓ 2 callersFunctionadd_pypath

(path)

384.288.model/test_config.py:6

↓ 2 callersFunctionadjust_learning_rate

Sets the learning rate to the initial LR decayed by schedule

utils/misc.py:58

↓ 2 callersMethodaugmentationCropImage

(self, img, bbox, joints=None)

dataloader/mscocoMulti.py:34

↓ 2 callersFunctioncolor_heatmap

(x)

utils/imutils.py:52

↓ 2 callersFunctionconv3x3

3x3 convolution with padding

networks/resnet.py:19

↓ 2 callersFunctionimshow

(img)

utils/imutils.py:62

↓ 2 callersFunctionsave_model

(state, checkpoint='checkpoint', filename='checkpoint.pth.tar')

utils/misc.py:44

↓ 2 callersMethodset_names

(self, names)

utils/logger.py:46

↓ 2 callersFunctionto_torch

(ndarray)

utils/misc.py:18

↓ 2 callersFunctiontrans_anno

(ori_file, target_file, is_val)

label_transform.py:11

↓ 2 callersMethodupdate

(self, val, n=1)

utils/evaluation.py:108

↓ 1 callersMethod__init__

(self, lateral_channel, out_shape, num_class)

networks/refineNet.py:49

↓ 1 callersMethod_lateral

(self, input_size)

networks/globalNet.py:29

↓ 1 callersMethod_make_layer

(self, input_channel, num, output_shape)

networks/refineNet.py:58

↓ 1 callersMethod_predict

(self, output_shape, num_class)

networks/globalNet.py:47

↓ 1 callersMethod_predict

(self, input_channel, num_class)

networks/refineNet.py:65

↓ 1 callersMethod_upsample

(self)

networks/globalNet.py:38

↓ 1 callersFunctionadd_pypath

(path)

256.192.model/config.py:6

↓ 1 callersFunctionadd_pypath

(path)

384.288.model/config.py:6

↓ 1 callersFunctioncalc_dists

(preds, target, normalize)

utils/evaluation.py:30

↓ 1 callersFunctioncolor_normalize

(x, mean)

utils/transforms.py:11

↓ 1 callersMethoddata_augmentation

(self, img, label, operation)

dataloader/mscocoMulti.py:91

↓ 1 callersFunctiondist_acc

Return percentage below threshold while ignoring values with a -1

utils/evaluation.py:42

↓ 1 callersFunctionfliplr

(x)

utils/transforms.py:68

↓ 1 callersFunctionget_transform

General image processing functions

utils/transforms.py:77

↓ 1 callersFunctionmain

(args)

256.192.model/train.py:22

↓ 1 callersFunctionmain

(args)

256.192.model/test.py:29

↓ 1 callersFunctionmain

(args)

384.288.model/train.py:22

↓ 1 callersFunctionmain

(args)

384.288.model/test.py:29

↓ 1 callersFunctionohkm

(loss, top_k)

256.192.model/train.py:86

↓ 1 callersFunctionohkm

(loss, top_k)

384.288.model/train.py:86

↓ 1 callersFunctionplot_overlap

(logger, names=None)

utils/logger.py:14

↓ 1 callersMethodreset

(self)

utils/evaluation.py:102

↓ 1 callersFunctionresize

(img, owidth, oheight)

utils/imutils.py:25

↓ 1 callersFunctionresnet101

Constructs a ResNet-101 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

networks/resnet.py:206

↓ 1 callersFunctionresnet50

Constructs a ResNet-50 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

networks/resnet.py:186

↓ 1 callersFunctionsample_with_heatmap

(inp, out, num_rows=2, parts_to_show=None)

utils/imutils.py:91

↓ 1 callersFunctionsavefig

(fname, dpi=None)

utils/logger.py:10

↓ 1 callersFunctiontrain

(train_loader, model, criterions, optimizer)

256.192.model/train.py:84

↓ 1 callersFunctiontrain

(train_loader, model, criterions, optimizer)

384.288.model/train.py:84

↓ 1 callersFunctiontransform_preds

(coords, center, scale, res)

utils/transforms.py:117

FunctionCPN101

(out_size,num_class,pretrained=True)

networks/network.py:29

FunctionCPN50

(out_size,num_class,pretrained=True)

networks/network.py:24

Method__getitem__

(self, index)

dataloader/mscocoMulti.py:151

Method__init__

(self)

utils/evaluation.py:99

Method__init__

(self, fpath, title=None, resume=False)

utils/logger.py:24

Method__init__

paths is a distionary with {name:filepath} pair

utils/logger.py:84

Method__init__

(self, resnet, output_shape, num_class, pretrained=True)

networks/network.py:10

Method__init__

(self, channel_settings, output_shape, num_class)

networks/globalNet.py:6

Method__init__

(self, inplanes, planes, stride=1, downsample=None)

networks/resnet.py:28

Method__init__

(self, inplanes, planes, stride=1, downsample=None)

networks/resnet.py:60

Method__init__

(self, inplanes, planes, stride=1)

networks/refineNet.py:7

Method__init__

(self, cfg, train=True)

dataloader/mscocoMulti.py:18

Method__len__

(self)

dataloader/mscocoMulti.py:205

Functionaccuracy

Calculate accuracy according to PCK, but uses ground truth heatmap rather than x,y locations First value to be returned is average accuracy a

utils/evaluation.py:49

Functionadd_pypath

(path)

utils/osutils.py:20

Functionbatch_with_heatmap

(inputs, outputs, mean=torch.Tensor([0.5, 0.5, 0.5]), num_rows=2, parts_to_show=None)

utils/imutils.py:126

Functioncopy_log

(filepath = 'checkpoint')

utils/misc.py:40

Functioncrop

(img, center, scale, res, rot=0)

utils/transforms.py:126

Functionfinal_preds

(output, center, scale, res)

utils/evaluation.py:72

Functionflip_back

flip output map

utils/transforms.py:20

Methodforward

(self, x)

networks/network.py:17

Methodforward

(self, x)

networks/globalNet.py:61

Methodforward

(self, x)

networks/resnet.py:38

Methodforward

(self, x)

networks/resnet.py:73

Methodforward

(self, x)

networks/resnet.py:136

Methodforward

(self, x)

networks/refineNet.py:26

Methodforward

(self, x)

networks/refineNet.py:73

Constructs a ResNet-152 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

networks/resnet.py:226

Functionresnet18

Constructs a ResNet-18 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

networks/resnet.py:150

Functionresnet34

Constructs a ResNet-34 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

networks/resnet.py:168

Functionsave_checkpoint

(state, preds, is_best, checkpoint='checkpoint', filename='checkpoint.pth.tar', snapshot=None)

utils/misc.py:27

Functionsave_pred

(preds, checkpoint='checkpoint', filename='preds_valid.mat')

utils/transforms.py:44