MCPcopy Create free account

hub / github.com/ZPdesu/Barbershop / functions

Functions391 in github.com/ZPdesu/Barbershop

⨍ Functions 391◇ Types & classes 93
↓ 15 callersMethod__init__
(self, kernel, pad, upsample_factor=1)
models/stylegan2/model.py:78
↓ 11 callersMethodsave
(self, path, label)
losses/lpips/dist_model.py:195
↓ 9 callersMethodbackward
(ctx, grad_output)
models/stylegan2/op/upfirdn2d.py:127
↓ 9 callersFunctionbroadcast_to
models/face_parsing/modules/src/inplace_abn_cpu.cpp:17
↓ 9 callersMethodstep
(self, closure=None)
models/optimizer/ClampOptimizer.py:15
↓ 9 callersMethodzero_grad
(self)
models/optimizer/ClampOptimizer.py:27
↓ 6 callersMethod__init__
(self, n_classes, *args, **kwargs)
models/face_parsing/model.py:237
↓ 5 callersMethod__init__
( self, pnet_type="vgg", pnet_rand=False, pnet_tune=False, use_dropout
losses/masked_lpips/networks_basic.py:42
↓ 5 callersMethod__init__
(self, pnet_type='vgg', pnet_rand=False, pnet_tune=False, use_dropout=True, spatial=False, version='0.1', lpip
losses/lpips/networks_basic.py:28
↓ 5 callersMethodcreate_down_seg
(self, latent_in)
models/Alignment.py:205
↓ 5 callersFunctionload_FS_latent
(latent_path, device)
utils/data_utils.py:57
↓ 4 callersFunctioncreate_layer_basic
(in_chan, out_chan, bnum, stride=1)
models/face_parsing/resnet.py:51
↓ 4 callersMethodcross_entropy_loss
(self, down_seg, target_mask)
losses/align_loss.py:27
↓ 4 callersFunctioncuda_unsqueeze
(li_variables=None, device='cuda')
utils/data_utils.py:31
↓ 4 callersMethodforward
(self, in0, in1, retPerLayer=None)
losses/masked_lpips/networks_basic.py:280
↓ 4 callersMethodforward
(self, in0, in1, retPerLayer=None)
losses/lpips/networks_basic.py:152
↓ 4 callersFunctionreduce_sum
models/face_parsing/modules/src/inplace_abn_cpu.cpp:8
↓ 4 callersMethodsetup_align_optimizer
(self, latent_path=None)
models/Alignment.py:184
↓ 3 callersMethod__init__
(self, requires_grad=False, pretrained=True)
losses/masked_lpips/pretrained_networks.py:105
↓ 3 callersMethod__init__
(self, requires_grad=False, pretrained=True)
losses/lpips/pretrained_networks.py:98
↓ 3 callersMethoddilate_erosion
(self, free_mask, device, dilate_erosion=5)
models/Alignment.py:216
↓ 3 callersFunctiondownload_weight
(weight_path)
utils/model_utils.py:15
↓ 3 callersMethodforward
Function computes the distance between image patches in0 and in1 INPUTS in0, in1 - torch.Tensor object of shape Nx3xXxY - image pa
losses/masked_lpips/dist_model.py:145
↓ 3 callersMethodforward
Function computes the distance between image patches in0 and in1 INPUTS in0, in1 - torch.Tensor object of shape Nx3xXxY - image p
losses/lpips/dist_model.py:109
↓ 3 callersFunctionmake_kernel
(k)
models/stylegan2/model.py:24
↓ 3 callersMethodsave_network
(self, network, path, network_label, epoch_label)
losses/masked_lpips/base_model.py:39
↓ 3 callersMethodsave_network
(self, network, path, network_label, epoch_label)
losses/lpips/base_model.py:38
↓ 3 callersFunctionupfirdn2d
(input, kernel, up=1, down=1, pad=(0, 0))
models/stylegan2/op/upfirdn2d.py:145
↓ 2 callersMethod__init__
(self)
losses/style/vgg_activations.py:51
↓ 2 callersFunction_act_backward
(ctx, x, dx)
models/face_parsing/modules/functions.py:68
↓ 2 callersFunction_act_forward
(ctx, x)
models/face_parsing/modules/functions.py:59
↓ 2 callersMethodalign_images
(self, img_path1, img_path2, sign='realistic', align_more_region=False, smooth=5, save_in
models/Alignment.py:221
↓ 2 callersMethodcal_loss
(self, im_dict, latent_in, latent_F=None, F_init=None)
models/Embedding.py:173
↓ 2 callersFunctionconv3x3
3x3 convolution with padding
models/face_parsing/resnet.py:14
↓ 2 callersFunctionconvert_npy_code
(latent)
utils/data_utils.py:46
↓ 2 callersFunctioncount
models/face_parsing/modules/src/inplace_abn_cpu.cpp:29
↓ 2 callersMethodcross_entropy_loss_only_background
(self, down_seg, target_mask)
losses/align_loss.py:41
↓ 2 callersMethodcross_entropy_loss_wo_background
(self, down_seg, target_mask)
losses/align_loss.py:37
↓ 2 callersFunctiondilate_erosion_mask_path
(im_path, seg_net, dilate_erosion=5)
utils/image_utils.py:31
↓ 2 callersFunctiondilate_erosion_mask_tensor
(mask, dilate_erosion=5)
utils/image_utils.py:55
↓ 2 callersFunctionfused_leaky_relu
(input, bias, negative_slope=0.2, scale=2 ** 0.5)
models/stylegan2/op/fused_act.py:85
↓ 2 callersMethodget_features
(self, model, x)
losses/style/style_loss.py:22
↓ 2 callersMethodgram_matrix
:x is an activation tensor
losses/style/style_loss.py:31
↓ 2 callersFunctionim2tensor
(image, imtype=np.uint8, cent=1.0, factor=255.0 / 2.0)
losses/masked_lpips/__init__.py:144
↓ 2 callersFunctionim2tensor
(image, imtype=np.uint8, cent=1., factor=255./2.)
losses/lpips/__init__.py:111
↓ 2 callersFunctioninvert_affine
models/face_parsing/modules/src/inplace_abn_cpu.cpp:37
↓ 2 callersFunctionload_image
(img_path, normalize=True, downsample=False)
utils/image_utils.py:20
↓ 2 callersMethodmask_features
(self, x, mask)
losses/style/style_loss.py:26
↓ 2 callersFunctionnp2tensor
(np_obj)
losses/masked_lpips/__init__.py:92
↓ 2 callersFunctionnp2tensor
(np_obj)
losses/lpips/__init__.py:66
↓ 2 callersFunctionprepare_mask
Make mask similar to x. Mask contains values in [0, 1]. Adjust channels and spatial dimensions.
losses/style/custom_loss.py:54
↓ 2 callersMethodpreprocess_img
(self, img_path)
models/Alignment.py:179
↓ 2 callersMethodsave
(self, label)
losses/masked_lpips/base_model.py:35
↓ 2 callersMethodsave
(self, label)
losses/lpips/base_model.py:34
↓ 2 callersMethodsetup_dataloader
(self, image_path=None)
models/Embedding.py:87
↓ 2 callersFunctionspatial_average
(in_tens, mask=None, keepdim=True)
losses/masked_lpips/networks_basic.py:18
↓ 2 callersFunctionspatial_average
(in_tens, keepdim=True)
losses/lpips/networks_basic.py:17
↓ 2 callersFunctionupsample
(in_tens, out_H=64)
losses/masked_lpips/networks_basic.py:31
↓ 2 callersFunctionupsample
(in_tens, out_H=64)
losses/lpips/networks_basic.py:20
↓ 1 callersMethod__init__
(self)
models/face_parsing/resnet.py:59
↓ 1 callersMethod__init__
(self, module)
models/face_parsing/modules/misc.py:15
↓ 1 callersMethod__init__
Creates an Activated Batch Normalization module Parameters ---------- num_features : int Number of feature channe
models/face_parsing/modules/bn.py:19
↓ 1 callersMethod__init__
(self, requires_grad=False)
losses/vgg_loss.py:6
↓ 1 callersFunction_count_samples
(x)
models/face_parsing/modules/functions.py:51
↓ 1 callersMethod_global_pooling
(self, x)
models/face_parsing/modules/deeplab.py:68
↓ 1 callersFunctionalign_face
:param filepath: str :return: list of PIL Images
utils/shape_predictor.py:43
↓ 1 callersMethodbackward
(ctx, dz)
models/face_parsing/modules/functions.py:119
↓ 1 callersFunctionbackward_cpu
models/face_parsing/modules/src/inplace_abn_cpu.cpp:75
↓ 1 callersMethodbackward_train
(self)
losses/masked_lpips/dist_model.py:200
↓ 1 callersMethodbackward_train
(self)
losses/lpips/dist_model.py:162
↓ 1 callersMethodbicubic_kernel
This equation is exactly copied from the website below: https://clouard.users.greyc.fr/Pantheon/experiments/rescaling/index-en.html#b
utils/bicubic.py:7
↓ 1 callersMethodblend_images
(self, img_path1, img_path2, img_path3, sign='realistic')
models/Blending.py:70
↓ 1 callersMethodbuild_PCA_model
(self, PCA_path)
models/Net.py:37
↓ 1 callersMethodcal_l_F
(self, latent_F, F_init)
models/Net.py:98
↓ 1 callersMethodcal_layer_num
(self)
models/Net.py:78
↓ 1 callersMethodcal_p_norm_loss
(self, latent_in)
models/Net.py:91
↓ 1 callersMethodcal_style
(self, model, x, x_hat, mask1=None, mask2=None)
losses/style/style_loss.py:41
↓ 1 callersMethodclamp_weights
(self)
losses/masked_lpips/dist_model.py:163
↓ 1 callersMethodclamp_weights
(self)
losses/lpips/dist_model.py:127
↓ 1 callersMethodcompute_accuracy
d0, d1 are Variables, judge is a Tensor
losses/masked_lpips/dist_model.py:203
↓ 1 callersMethodcompute_accuracy
d0, d1 are Variables, judge is a Tensor
losses/lpips/dist_model.py:165
↓ 1 callersMethodcreate_target_segmentation_mask
(self, img_path1, img_path2, sign, save_intermediate=True)
models/Alignment.py:59
↓ 1 callersFunctioncustom_loss
x, y: [N, C, H, W] Computes L1/L2 loss if include_bkgd is True: use traditional MSE and L1 loss else: mask out backg
losses/style/custom_loss.py:8
↓ 1 callersFunctionedz_eydz_cpu
models/face_parsing/modules/src/inplace_abn_cpu.cpp:66
↓ 1 callersFunctionelu_backward_cpu
models/face_parsing/modules/src/inplace_abn_cpu.cpp:103
↓ 1 callersMethodfit
(self, X)
utils/PCA_utils.py:13
↓ 1 callersMethodforward
(ctx, x, weight, bias, running_mean, running_var, training=True, momentum=0.1, eps=1e-05, acti
models/face_parsing/modules/functions.py:79
↓ 1 callersFunctionforward_cpu
models/face_parsing/modules/src/inplace_abn_cpu.cpp:54
↓ 1 callersMethodforward_train
(self)
losses/masked_lpips/dist_model.py:184
↓ 1 callersMethodforward_train
(self)
losses/lpips/dist_model.py:148
↓ 1 callersMethodget_components
(self)
utils/PCA_utils.py:26
↓ 1 callersFunctionget_landmark
get landmark with dlib :return: np.array shape=(68, 2)
utils/shape_predictor.py:26
↓ 1 callersMethodget_params
(self)
models/face_parsing/model.py:268
↓ 1 callersMethodget_params
(self)
models/face_parsing/resnet.py:90
↓ 1 callersFunctionhair
(image, parsing, part=17, color=[230, 50, 20])
models/face_parsing/makeup.py:26
↓ 1 callersMethodinit_weight
(self)
models/face_parsing/model.py:37
↓ 1 callersMethodinit_weight
(self)
models/face_parsing/model.py:55
↓ 1 callersMethodinit_weight
(self)
models/face_parsing/model.py:91
↓ 1 callersMethodinit_weight
(self)
models/face_parsing/model.py:133
↓ 1 callersMethodinit_weight
(self)
models/face_parsing/model.py:168
next →1–100 of 391, ranked by callers