Functions — github.com/Tushar-N/interaction-hotspots

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Functions113 in github.com/Tushar-N/interaction-hotspots

⨍ Functions 113◇ Types & classes 24

↓ 5 callersMethodpool

(self, frame_feats)

models/rnn.py:75

↓ 4 callersMethod_make_layer

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

models/backbones.py:70

↓ 4 callersFunctiondefault_mean_std

()

utils/util.py:8

↓ 3 callersMethodget_hidden_state

(self, B, device)

models/rnn.py:47

↓ 3 callersMethodload_state_dict

(self, state_dict)

models/intcam.py:15

↓ 2 callersMethod__init__

(self, root, rgb_or_det)

data/epic.py:15

↓ 2 callersMethod__init__

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

models/backbones.py:15

↓ 2 callersFunction_unnorm

(t)

utils/util.py:23

↓ 2 callersMethodflatten_apply

(self, tensor, module)

models/rnn.py:53

↓ 2 callersFunctiongenerate

(images)

data/hotspot_dataset.py:134

↓ 2 callersMethodgenerate_cams

(self, inputs, classes, **kwargs)

models/intcam.py:43

↓ 2 callersFunctiongenerate_heatmaps

(annots, kernel_size, out_file, transpose)

data/hotspot_dataset.py:132

↓ 2 callersMethodinit_hm_loader

(self)

data/hotspot_dataset.py:174

↓ 2 callersMethodload_static_image

(self, entry)

data/opra.py:50

↓ 2 callersMethodmake_dict

(self, preds)

utils/evaluation.py:107

↓ 2 callersFunctionresize_tensor

(tensor, sz)

viz.py:27

↓ 1 callersFunctionAUC_Judd

(saliency_map, fixation_map, jitter=True)

utils/evaluation.py:66

↓ 1 callersFunctionKLD

(map1, map2, eps = 1e-12)

utils/evaluation.py:54

↓ 1 callersFunctionSIM

(map1, map2, eps=1e-12)

utils/evaluation.py:60

↓ 1 callersMethod__init__

(self, root, split, std_norm=True)

data/opra.py:70

↓ 1 callersMethodanticipation_loss

(self, frame_feats, lstm_feats, batch)

models/rnn.py:82

↓ 1 callersMethodbackward_for_target_grad

(self, output, activations, target_grad)

models/intcam.py:19

↓ 1 callersMethodbatch_interp

(self, inp, sz)

utils/evaluation.py:145

↓ 1 callersFunctionblur

(tensor, sz, Z)

viz.py:31

↓ 1 callersMethodcheckpoint

(self, fl)

utils/evaluation.py:46

↓ 1 callersMethoddata_sampler

(self)

data/hotspot_dataset.py:38

↓ 1 callersMethodembed_clip

(self, frame_feats, **kwargs)

models/rnn.py:63

↓ 1 callersMethodevaluate

(self, preds)

utils/evaluation.py:153

↓ 1 callersFunctionexpand_box

(img, box, expand)

data/epic.py:29

↓ 1 callersFunctiongenerate_color_map

(hmaps, colors, sz)

viz.py:58

↓ 1 callersFunctiongenerate_gt

(dset)

eval.py:20

↓ 1 callersFunctiongenerate_heatmaps

(dset, load, batch_size)

eval.py:50

↓ 1 callersMethodgenerate_output_activation

(self, inputs, **kwargs)

models/intcam.py:27

↓ 1 callersMethodic_classifier

(self, frame_feats, **kwargs)

models/rnn.py:151

↓ 1 callersMethodic_features

(self, image, **kwargs)

models/rnn.py:147

↓ 1 callersMethodinit_backbone

data/hotspot_dataset.py:182

↓ 1 callersMethodload_frame

(self, frame)

data/hotspot_dataset.py:29

↓ 1 callersMethodload_image

(self, entry)

data/opra.py:83

↓ 1 callersMethodload_image_heatmap

(self, entry)

data/hotspot_dataset.py:178

↓ 1 callersFunctionmakeGaussian

(size, fwhm=3, center=None)

utils/evaluation.py:10

↓ 1 callersFunctionoverlay_colored_heatmaps

(uimg, hmaps, viz_idx, colors, sz)

viz.py:86

↓ 1 callersFunctionpost_process

(hmaps, sz)

viz.py:40

↓ 1 callersMethodsample

(self, clip)

data/hotspot_dataset.py:48

↓ 1 callersFunctionsave

(epoch)

train.py:37

↓ 1 callersMethodscore

(self, pred, gt)

utils/evaluation.py:117

↓ 1 callersMethodselect_inactive_instances

(self, entry)

data/hotspot_dataset.py:34

↓ 1 callersFunctiontrain

(epoch)

train.py:43

↓ 1 callersMethodtrain

(self, mode)

models/backbones.py:113

↓ 1 callersMethodtrain_transform

(self, image, heatmap)

utils/util.py:95

↓ 1 callersMethodval_transform

(self, image, heatmap)

utils/util.py:128

↓ 1 callersFunctionvisualize

(path, viz_verbs, colors, sz=256)

viz.py:101

Method__call__

(self, image, heatmap)

utils/util.py:151

Method__call__

(self, img_group)

utils/gtransforms.py:14

Method__call__

(self, img_group)

utils/gtransforms.py:24

Method__call__

(self, img_group)

utils/gtransforms.py:47

Method__call__

(self, img_group)

utils/gtransforms.py:51

Method__call__

(self, img_group)

utils/gtransforms.py:60

Method__call__

(self, tensor)

utils/gtransforms.py:69

Method__call__

(self, tensor)

utils/gtransforms.py:79

data/hotspot_dataset.py:160

Method__getitem__

(self, index)

data/hotspot_dataset.py:61

Method__getitem__

(self, index)

data/hotspot_dataset.py:185

Method__init__

(self, N)

utils/evaluation.py:22

Method__init__

(self, gt, res=28, log=None)

utils/evaluation.py:102

Method__init__

(self, split, std_norm=True)

utils/util.py:90

Method__init__

(self, size, interpolation=Image.BILINEAR)

utils/gtransforms.py:11

Method__init__

(self, size)

utils/gtransforms.py:18

Method__init__

(self, size)

utils/gtransforms.py:44

Method__init__

(self)

utils/gtransforms.py:57

Method__init__

(self, mean, std)

utils/gtransforms.py:65

Method__init__

(self, max_len)

utils/gtransforms.py:76

(self, root, split, max_len, sample_rate=10)

data/epic.py:81

Method__init__

(self, root, split, std_norm=True)

data/epic.py:126

Method__init__

(self, root, split, max_len, sample_rate=1)

data/opra.py:15

Method__init__

(self, root, split, max_len, sample_rate)

data/hotspot_dataset.py:13

Method__init__

(self, hf)

data/hotspot_dataset.py:155

Method__init__

(self, root, split, hm_file, std_norm=True)

data/hotspot_dataset.py:167

Method__init__

(self, block, layers, strides=[1,2,2,2], dilations=[1,1,1,1])

models/backbones.py:51

Method__init__

(self, block, layers, strides=[1,2,2,2], dilations=[1,1,1,1], pretrained=None)

models/backbones.py:100

Method__init__

(self, model, out_sz=224)

models/intcam.py:6

Method__init__

(self, num_classes, max_len, hidden_size, pool_fn='L2', ant_loss=None)

data/hotspot_dataset.py:82

Method__len__

(self)

data/hotspot_dataset.py:195

Functionbatch_cuda

(batch)

utils/util.py:16

Functionclip_transform

(split, max_len)

utils/util.py:59

Functioncompute_heatmap

Compute the heatmap from annotated points. Args: points: The annotated points. image_size: The size of the image. k_ratio:

data/hotspot_dataset.py:89

Methodconstant

(self, fill=0, sz=7, **kwargs)

utils/evaluation.py:42

Functionconv3x3

3x3 convolution with padding

models/backbones.py:7

Functiondefault_transform

models/backbones.py:126

models/backbones.py:27

Methodforward

(self, x)

models/backbones.py:87

Methodforward

(self, x)

models/backbones.py:116

Methodforward

(self, batch, **kwargs)

models/rnn.py:122

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