Functions — github.com/Time-Travel-Rephotography/Time-Travel-Rephotography.github.io

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Functions204 in github.com/Time-Travel-Rephotography/Time-Travel-Rephotography.github.io

⨍ Functions 204◇ Types & classes 60

↓ 15 callersMethod__init__

(self, kernel, pad, upsample_factor=1)

model.py:77

↓ 9 callersFunctionoptional_string

(condition: bool, string: str)

utils/misc.py:5

↓ 6 callersFunctioncalculate_cdf

This method calculates the cumulative distribution function :param array histogram: The values of the histogram :return: normalized_cdf:

tools/match_histogram.py:19

↓ 5 callersMethodload

(self, device: torch.device)

tools/initialize.py:145

↓ 5 callersMethodresize

(img)

utils/optimize.py:211

↓ 5 callersFunctionstem

(path: str)

utils/misc.py:13

↓ 4 callersFunctionmake_image

(tensor)

utils/torch_helpers.py:23

↓ 3 callersMethod__init__

(self, args:Namespace)

models/degrade.py:103

↓ 3 callersMethod__init__

(self, *args, **kwargs)

models/resnet.py:23

↓ 3 callersFunctioncalculate_lookup

This method creates the lookup table :param array src_cdf: The cdf for the source image :param array ref_cdf: The cdf for the reference i

tools/match_histogram.py:35

↓ 3 callersFunctioncreate_perceptual_loss

(args: Namespace)

losses/reconstruction.py:32

↓ 3 callersMethoddevice

(self)

model.py:455

↓ 3 callersFunctioniterable_to_str

(iterable: Iterable)

utils/misc.py:17

↓ 3 callersFunctionmake_kernel

(k)

model.py:23

↓ 3 callersFunctionrv

(im)

tools/match_histogram.py:69

↓ 3 callersFunctionsv

(im)

tools/match_histogram.py:74

↓ 3 callersFunctionupfirdn2d

(input, kernel, up=1, down=1, pad=(0, 0))

op/upfirdn2d.py:144

↓ 2 callersMethod__init__

(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8, weight_decay=0, degenerated_to_sgd=True)

optim/radam.py:8

↓ 2 callersMethod__init__

( self, args: Namespace, target: torch.Tensor, sibling: Option

losses/joint_loss.py:90

↓ 2 callersMethod__init__

( self, lambda_vggface: float = 0.025 / 0.15, lambda_vgg: float = 1, eps: float = 1e-8, cos_dist:

losses/perceptual_loss.py:91

↓ 2 callersMethod__setstate__

(self, state)

optim/radam.py:27

↓ 2 callersFunctionactivation_func

(activation: str)

models/resnet.py:6

↓ 2 callersFunctionconv_norm

(in_channels: int, out_channels: int, conv, norm, *args, **kwargs)

models/resnet.py:77

↓ 2 callersFunctioncreate_color_encoder

(args: Namespace)

tools/initialize.py:73

↓ 2 callersFunctionfused_leaky_relu

(input, bias, negative_slope=0.2, scale=2 ** 0.5)

op/fused_act.py:85

↓ 2 callersMethodget_latent_size

(size)

model.py:461

↓ 2 callersFunctiongram_matrix

(input_)

losses/color_transfer_loss.py:27

↓ 2 callersFunctionnorm_module

(norm: str)

models/resnet.py:15

↓ 2 callersFunctionnormalize

[0, 1] -> [-1, 1]

projector.py:65

↓ 2 callersFunctionresize

(imgs: torch.Tensor, size: int)

tools/initialize.py:101

↓ 2 callersFunctionresize

(t: torch.Tensor, size: int)

utils/torch_helpers.py:17

↓ 2 callersFunctionsave

( path_prefixes: Iterable[str], imgs: torch.Tensor, # BCHW latents: torch.Tensor,

projector.py:78

↓ 1 callersMethod__init__

target: target image

losses/reconstruction.py:37

↓ 1 callersMethodadd_arguments

(parser: ArgumentParser)

tools/initialize.py:41

↓ 1 callersMethodadd_arguments

(cls, parser: ArgumentParser)

utils/projector_arguments.py:24

↓ 1 callersMethodadd_e4e_arguments

(parser: ArgumentParser)

tools/initialize.py:65

↓ 1 callersMethodadd_io_args

(parser: ArgumentParser)

utils/projector_arguments.py:44

↓ 1 callersMethodadd_item

(self, size, path)

tools/data/align_images.py:27

↓ 1 callersMethodadd_preprocess_args

(parser: ArgumentParser)

utils/projector_arguments.py:49

↓ 1 callersMethodadd_stylegan_args

(parser: ArgumentParser)

utils/projector_arguments.py:37

↓ 1 callersMethodbackward

(ctx, grad_output)

op/upfirdn2d.py:126

↓ 1 callersFunctionconvert_to_BW

(im, mode)

tools/match_histogram.py:115

↓ 1 callersFunctioncreate_generator

(args: Namespace, device: torch.device)

projector.py:70

↓ 1 callersFunctioncreate_skin_mask

(anno_dir, mask_dir, skin_thresh=13, include_hair=False)

tools/parse_face.py:11

↓ 1 callersMethoddetect_faces

(self, image, conf_threshold=0)

utils/ffhq_dataset/landmarks_detector.py:47

↓ 1 callersMethoddraw

(img, landmarks)

utils/ffhq_dataset/landmarks_detector.py:23

↓ 1 callersMethodencode_color

Get the color W code

tools/initialize.py:128

↓ 1 callersMethodencode_shape

(self, imgs: torch.Tensor)

tools/initialize.py:138

↓ 1 callersFunctionflatten_CHW

(B, C, H, W) -> (B, -1)

losses/color_transfer_loss.py:10

↓ 1 callersMethodforward

(self, latent: torch.Tensor, t: float)

utils/optimize.py:76

↓ 1 callersMethodforward

Args: rgbs: results from the ToRGB layers

losses/joint_loss.py:134

↓ 1 callersMethodget_landmarks

(self, image)

utils/ffhq_dataset/landmarks_detector.py:13

↓ 1 callersMethodget_sizes

(self)

tools/data/align_images.py:32

↓ 1 callersFunctionimage_align

(src_file, dst_file, face_landmarks, resize=True, output_size=1024, transform_size=4096, enable_padding=True)

utils/ffhq_dataset/face_alignment.py:7

↓ 1 callersMethodlog_losses

( writer: SummaryWriter, niters: int, loss_total: torch.Tensor,

utils/optimize.py:174

↓ 1 callersMethodlog_parameters

( writer: SummaryWriter, niters: int, named_parameters: Iterable[Tuple[str

utils/optimize.py:189

↓ 1 callersMethodlog_torgbs

(writer: SummaryWriter, niters: int, rgbs: Iterable[torch.Tensor], prefix: str = "")

utils/optimize.py:225

↓ 1 callersMethodlog_visuals

( cls, writer: SummaryWriter, niters: int, img: torch.Tensor,

utils/optimize.py:198

↓ 1 callersFunctionmain

(args)

projector.py:101

↓ 1 callersFunctionmain

(args)

tools/match_histogram.py:139

↓ 1 callersFunctionmain

(args)

tools/parse_face.py:23

↓ 1 callersFunctionmain

(args)

tools/data/align_images.py:45

↓ 1 callersMethodmake_noise

(self)

model.py:477

↓ 1 callersMethodmake_noise_by_size

(size: int, device: torch.device)

model.py:466

↓ 1 callersFunctionmatch_histograms

This method matches the source image histogram to the reference signal :param image src_image: The original source image :param image

tools/match_histogram.py:55

↓ 1 callersFunctionmatch_skin_histogram

Extract the skin of the input and sibling images. Create a new input image by matching its histogram to the sibling.

tools/match_skin_histogram.py:17

↓ 1 callersMethodnormalize

(noises: Iterable[torch.Tensor])

losses/regularize_noise.py:31

↓ 1 callersMethodoptimize

( cls, generator: torch.nn, criterion: torch.nn, degrade: torc

utils/optimize.py:84

↓ 1 callersMethodparse

(self, args=None, namespace=None)

utils/projector_arguments.py:53

↓ 1 callersFunctionparse_args

()

projector.py:168

↓ 1 callersFunctionparse_args

(args=None, namespace: Optional[Namespace] = None)

tools/match_histogram.py:127

↓ 1 callersFunctionparse_args

(args=None, namespace=None)

tools/parse_face.py:43

↓ 1 callersFunctionparse_args

(args=None, namespace=None)

tools/data/align_images.py:97

↓ 1 callersMethodprint

(args: Namespace)

utils/projector_arguments.py:59

↓ 1 callersFunctionread_images

(paths: str, max_size: Optional[int] = None)

projector.py:46

↓ 1 callersMethodserialize

(self)

tools/data/align_images.py:38

↓ 1 callersFunctionset_random_seed

(seed: int)

projector.py:39

↓ 1 callersMethodsplit_latent

(latent: torch.Tensor, coarse_latent_size: int)

utils/optimize.py:166

↓ 1 callersFunctionstddev

x: (B, -1), assume with mean normalized Retuens: stddev: (B)

losses/color_transfer_loss.py:18

↓ 1 callersMethodstep

(self, closure=None)

optim/radam.py:30

↓ 1 callersMethodto_string

(args: Namespace)

models/degrade.py:24

↓ 1 callersFunctionunpack_bz2

(src_path)

tools/data/align_images.py:17

↓ 1 callersMethodupdate_sibling

(self, sibling: torch.Tensor)

losses/joint_loss.py:165

FunctionPYBIND11_MODULE

op/fused_bias_act.cpp:19

FunctionPYBIND11_MODULE

(self, kernel, factor=2)

model.py:35

Method__init__

(self, kernel, factor=2)

model.py:56

Method__init__

( self, in_channel, out_channel, kernel_size, stride=1, padding=0, bias=True )

model.py:96

Method__init__

( self, in_dim, out_dim, bias=True, bias_init=0, lr_mul=1, activation=None )

model.py:134

Method__init__

(self, negative_slope=0.2)

model.py:171

Method__init__

( self, in_channel, out_channel, kernel_size, style_dim, demod

(self, channel, size=4)

model.py:296

Method__init__

( self, in_channel, out_channel, kernel_size, style_dim, upsam

model.py:309

Method__init__

(self, in_channel, style_dim, upsample=True, blur_kernel=[1, 3, 3, 1])

model.py:346

Method__init__

( self, size, style_dim, n_mlp, channel_multiplier=2, blur_ker

model.py:369

Method__init__

( self, in_channel, out_channel, kernel_size, downsample=False,

model.py:569

Method__init__

(self, in_channel, out_channel, blur_kernel=[1, 3, 3, 1])

model.py:618

Method__init__

(self, size, channel_multiplier=2, blur_kernel=[1, 3, 3, 1])

model.py:639

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