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Functions106 in github.com/HighwayWu/ImageInpainting

⨍ Functions 106◇ Types & classes 16
↓ 36 callersFunctionspectral_norm
(module, mode=True)
networks.py:265
↓ 31 callersMethodmean
(self)
util.py:57
↓ 8 callersMethodget_pixel
(self, img, center, x, y)
main.py:50
↓ 4 callersFunctionpostprocess
(img)
main.py:113
↓ 4 callersMethodset_requires_grad
Set requies_grad=Fasle for all the networks to avoid unnecessary computations Parameters: nets (network list) -- a list of netwo
model.py:122
↓ 3 callersMethodbackward
(ctx, grad_output)
attention.py:76
↓ 3 callersFunctioninit_net
(net, init_type='normal', init_gain=0.02, device='')
networks.py:325
↓ 3 callersFunctionmetrics
(real, fake)
main.py:120
↓ 3 callersMethodoptimize_parameters
(self, val=False)
model.py:268
↓ 3 callersMethodset_input
(self, input)
model.py:164
↓ 2 callersFunctionMyUnfold
(input, patch_size, stride)
attention.py:94
↓ 2 callersMethod__init__
(self, tv_loss_weight=1)
losses.py:98
↓ 2 callersMethod__init__
(self)
networks.py:13
↓ 2 callersMethod_tensor_size
(t)
losses.py:111
↓ 2 callersMethodbackward_G
(self, val=False)
model.py:187
↓ 2 callersMethodinitialize
(self, opt)
model.py:137
↓ 2 callersFunctionmkdir
(path)
util.py:294
↓ 1 callersMethod__init__
(self, masks, stop_criteria=0.85)
util.py:34
↓ 1 callersMethod__patch_instance_norm_state_dict
(self, state_dict, module, keys, i=0)
model.py:78
↓ 1 callersMethod_assert_no_grad
(self, variable)
losses.py:66
↓ 1 callersMethod_get_next_indexes
(self)
util.py:61
↓ 1 callersMethod_is_finished
(self)
util.py:46
↓ 1 callersMethod_solve
(self)
util.py:67
↓ 1 callersMethodbackward_D
(self)
model.py:232
↓ 1 callersMethodbackward_D2
(self)
model.py:250
↓ 1 callersFunctioncompute_color
(u,v)
util.py:405
↓ 1 callersFunctioncreate_gMask
(gMask_opts, limit_cnt=1)
util.py:145
↓ 1 callersMethodforward
(self)
model.py:29
↓ 1 callersMethodforward
(self)
model.py:182
↓ 1 callersMethodgather_options
(self, options=None)
options.py:53
↓ 1 callersFunctionget_norm_layer
(norm_type='instance')
networks.py:272
↓ 1 callersMethodget_target_tensor
(self, prediction, target_is_real)
losses.py:32
↓ 1 callersFunctioninit_weights
(net, init_type='normal', gain=0.02)
networks.py:303
↓ 1 callersMethodinitialize
(self, parser)
options.py:10
↓ 1 callersMethodlbp_calculated_pixel
64 | 128 | 1 ---------------- 32 | 0 | 2 ---------------- 16 | 8 | 4
main.py:59
↓ 1 callersMethodload_lbp
(self, img)
main.py:84
↓ 1 callersMethodload_networks
(self, which_epoch)
model.py:89
↓ 1 callersFunctionmake_color_wheel
()
util.py:433
↓ 1 callersMethodparse
(self, options=None)
options.py:87
↓ 1 callersFunctionrandom_walk
(canvas, ini_x, ini_y, length)
util.py:182
↓ 1 callersMethodsave_networks
(self, which_epoch)
model.py:62
↓ 1 callersFunctionspatial_discounting_mask
Generate spatial discounting mask constant. Spatial discounting mask is first introduced in publication: Generative Image Inpainting with
losses.py:72
↓ 1 callersFunctiontest
()
main.py:185
↓ 1 callersFunctiontrain
()
main.py:135
↓ 1 callersFunctionwrapper_gmask
(opt)
util.py:121
Method__call__
(self, prediction, target_is_real)
losses.py:39
Method__getitem__
(self, index)
main.py:29
Method__init__
(self)
options.py:7
Method__init__
(self, gan_type='wgan_gp', target_real_label=1.0, target_fake_label=0.0)
losses.py:10
Method__init__
(self, opt)
losses.py:53
Method__init__
(self, opt)
networks.py:114
Method__init__
(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNorm2d, use_sigmoid=False, use_spectral_norm=True)
networks.py:220
Method__init__
(self, opt)
attention.py:8
Method__init__
(self)
util.py:466
Method__init__
(self, opt)
main.py:21
Method__init__
(self, opt)
main.py:94
Method__iter__
(self)
main.py:106
Method__len__
(self)
main.py:47
Method__len__
(self)
main.py:103
Functioncal_feat_mask
(inMask, nlayers)
util.py:206
Functioncal_flag_given_mask_thred
(mask, patch_size, stride, mask_thred)
util.py:218
Functioncal_gradient_penalty
Calculate the gradient penalty loss, used in WGAN-GP paper https://arxiv.org/abs/1704.00028 Arguments: netD (network) -- disc
util.py:504
Functioncreate_mask
()
util.py:197
Functioncreate_masks
(opt, N=10)
util.py:16
Functioncreate_rand_mask
(opt)
util.py:169
Functiondefine_D
(input_nc, ndf, device='')
networks.py:342
Functiondefine_G
(opt)
networks.py:332
Functiondefine_LBP
(opt)
networks.py:337
Functiondiagnose_network
(net, name='network')
util.py:107
Functionflow_to_image
Transfer flow map to image. Part of code forked from flownet.
util.py:343
Methodforward
(self, input, target)
losses.py:59
Methodforward
(self, x)
losses.py:102
Methodforward
(self, lbp, mask)
networks.py:93
Methodforward
(self, x, lbp, mask, second=False)
networks.py:197
Methodforward
(self, input)
networks.py:261
Methodforward
(self, generated, known, mask)
attention.py:12
Methodforward
(ctx, generated, known, mask, device)
attention.py:20
Methodforward
(self, image)
util.py:483
Methodget_current_losses
(self)
model.py:53
Methodget_image_paths
(self)
model.py:39
Methodget_iou
(self)
util.py:39
Methodget_masks
(self)
util.py:73
Functionget_scheduler
(optimizer, opt)
networks.py:286
Functiongram_matrix
(feat)
util.py:497
Functionhighlight_flow
Convert flow into middlebury color code image.
util.py:377
Functionhist_match
Adjust the pixel values of a grayscale image such that its histogram matches that of a target image Arguments: ----------- s
util.py:298
Functioninfo
Print methods and doc strings. Takes module, class, list, dictionary, or string.
util.py:260
Functioninit_func
(m)
networks.py:304
Methodinitialize
(self, parser)
options.py:102
Methodinitialize
(self, opt)
model.py:17
Functionlambda_rule
(epoch)
networks.py:288
Functionmkdirs
(paths)
util.py:286
Methodname
(self)
model.py:14
Methodoptimize_parameters
(self)
model.py:42
Methodprint_networks
(self, verbose)
model.py:109
Functionprint_numpy
(x, val=True, shp=False)
util.py:276
Methodprint_options
(self, opt)
options.py:67
Functionrm_extra_dim
(image)
util.py:98
Functionsave_image
(image_numpy, image_path)
util.py:256
Methodset_input
(self, input)
model.py:26
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