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Functions455 in github.com/NVlabs/few-shot-vid2vid

⨍ Functions 455◇ Types & classes 95
↓ 39 callersFunctionconv
(batchNorm, in_planes, out_planes, kernel_size=3, stride=1)
models/networks/flownet2_pytorch/networks/submodules.py:7
↓ 25 callersMethodlog
(self, string)
models/networks/flownet2_pytorch/utils/tools.py:42
↓ 18 callersFunctionpredict_flow
(in_planes)
models/networks/flownet2_pytorch/networks/submodules.py:31
↓ 15 callersFunctionmake_dataset
(dir, recursive=False, read_cache=False, write_cache=False)
data/image_folder.py:33
↓ 14 callersFunctiondeconv
(in_planes, out_planes)
models/networks/flownet2_pytorch/networks/submodules.py:34
↓ 13 callersMethodnorm
(self, t)
models/flownet.py:82
↓ 13 callersMethodsave
(self)
util/html.py:59
↓ 13 callersMethodsum
(self, x)
models/networks/base_network.py:132
↓ 13 callersMethodvis_print
(opt, message)
util/visualizer.py:208
↓ 12 callersMethodconcat_frame
(self, A, Ai, n=100)
data/base_dataset.py:54
↓ 12 callersMethodread_data
(self, path, lmdb=None, data_type='img')
data/base_dataset.py:29
↓ 10 callersMethodreshape
(self, tensors, for_temporal=False)
models/base_model.py:120
↓ 9 callersFunctionactvn
(x)
models/networks/architecture.py:15
↓ 7 callersMethodloss
(self, input, target_is_real, weight=None, reduce_dim=True, for_discriminator=True)
models/networks/loss.py:49
↓ 7 callersFunctionmake_grouped_dataset
(dir)
data/image_folder.py:63
↓ 7 callersFunctionparse_flownets
(modules, weights, biases, param_prefix='net2_')
models/networks/flownet2_pytorch/utils/param_utils.py:51
↓ 7 callersMethodreshape_weight
(self, x, weight_size)
models/networks/base_network.py:154
↓ 6 callersMethod__init__
(self, args, is_cropped = False, root = '', dstype = 'clean', replicates = 1)
models/networks/flownet2_pytorch/datasets.py:31
↓ 6 callersFunctionbatch_conv
(x, weight, bias=None, stride=1, group_size=-1)
models/networks/base_network.py:56
↓ 6 callersMethodget
(self)
models/networks/sync_batchnorm/comm.py:32
↓ 6 callersFunctionget_keypoint_array
(keypoint_dict)
data/preprocess/util/util.py:13
↓ 6 callersMethodget_optimizer
(self, params, for_discriminator=False)
models/base_model.py:39
↓ 6 callersFunctionget_rank
()
util/distributed.py:29
↓ 6 callersFunctioni_conv
(batchNorm, in_planes, out_planes, kernel_size=3, stride=1, bias = True)
models/networks/flownet2_pytorch/networks/submodules.py:20
↓ 6 callersFunctionremove_frame
(args, video_idx='', start=0, end=None)
data/preprocess/util/util.py:29
↓ 5 callersMethod__init__
(self, *args, hidden_nc=0, norm='', ks=1, params_free=False, **kwargs)
models/networks/architecture.py:51
↓ 5 callersMethod__init__
(self, args=None, batchNorm=False, div_flow = 20.)
models/networks/flownet2_pytorch/models.py:24
↓ 5 callersFunction_unsqueeze_ft
add new dementions at the front and the tail
models/networks/sync_batchnorm/batchnorm.py:29
↓ 5 callersMethodadd_images
(self, ims, txts, links, width=512, height=0)
util/html.py:44
↓ 5 callersMethodcrop
(self, img, coords)
data/base_dataset.py:47
↓ 5 callersFunctionget_transform
(opt, params, method=Image.BICUBIC, normalize=True, toTensor=True, color_aug=False)
data/base_dataset.py:128
↓ 5 callersFunctionis_master
check if current process is the master
util/distributed.py:55
↓ 5 callersMethodload_network
(self, network, network_label, epoch_label, save_dir='')
models/base_model.py:59
↓ 5 callersFunctionmakedirs
(folder)
data/preprocess/util/util.py:62
↓ 5 callersFunctionparse_flownetc
(modules, weights, biases)
models/networks/flownet2_pytorch/utils/param_utils.py:5
↓ 5 callersMethodsave_network
(self, network, network_label, epoch_label, gpu_ids)
models/base_model.py:51
↓ 5 callersFunctionset_random_seed
Set random seeds for everything. Inputs: seed (int): Random seed.
util/distributed.py:101
↓ 5 callersFunctionuse_valid_labels
(opt, pose)
models/input_process.py:97
↓ 4 callersFunctionEPE
(input_flow, target_flow)
models/networks/flownet2_pytorch/losses.py:11
↓ 4 callersMethod__init__
(self)
models/networks/flownet2_pytorch/losses.py:15
↓ 4 callersMethodbackward
(ctx, grad_output)
models/networks/flownet2_pytorch/networks/resample2d_package/resample2d.py:24
↓ 4 callersMethodcompute_GAN_losses
(self, nets, data_list, for_discriminator, for_temporal=False)
models/loss_collector.py:87
↓ 4 callersMethodcrop_face_region
(self, image, input_label, crop_smaller=0)
models/face_refiner.py:32
↓ 4 callersFunctiondraw_edge
(im, x, y, bw=1, color=(255,255,255), draw_end_points=False)
data/keypoint2img.py:279
↓ 4 callersMethodget_crop_coords
(self, keypoints, crop_size=None, for_ref=False)
data/fewshot_face_dataset.py:191
↓ 4 callersFunctionget_frame_idx
(file_name)
data/preprocess/util/util.py:58
↓ 4 callersMethodget_image
(self, A_path, transform_scaleA, is_label=False)
data/fewshot_street_dataset.py:105
↓ 4 callersFunctionget_world_size
()
util/distributed.py:37
↓ 4 callersMethodinit_weights
(self, init_type='normal', gain=0.02)
models/networks/base_network.py:86
↓ 4 callersFunctioninterp_points
(x, y)
data/keypoint2img.py:299
↓ 4 callersFunctionloss_backward
(opt, losses, optimizer, loss_id)
models/loss_collector.py:217
↓ 4 callersFunctionremove
(file_name)
data/preprocess/util/util.py:68
↓ 4 callersFunctionresample
(image, flow)
models/networks/base_network.py:28
↓ 4 callersFunctiontile_images
Convert to a true list of 16x16 images
util/util.py:108
↓ 3 callersMethod__init__
(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNorm2d, getIntermFeat=False, stride=2)
models/networks/discriminator.py:62
↓ 3 callersMethodadd_header
(self, str)
util/html.py:36
↓ 3 callersFunctioncombine_fg_mask
(fg_mask, ref_fg_mask, has_fg)
models/input_process.py:48
↓ 3 callersFunctionget_face_mask
(pose)
models/input_process.py:83
↓ 3 callersMethodget_face_region
(self, pose, crop_smaller=0)
models/face_refiner.py:53
↓ 3 callersFunctionget_fg_mask
(opt, input_label, has_fg)
models/input_process.py:52
↓ 3 callersMethodget_image
(self, A_path, size, params, crop_coords, input_type, ppl_idx=None, op=None, ref_face_pts=None)
data/fewshot_pose_dataset.py:162
↓ 3 callersFunctionget_img_params
(opt, size)
data/base_dataset.py:62
↓ 3 callersFunctionget_nonspade_norm_layer
(opt, norm_type='instance')
models/networks/normalization.py:54
↓ 3 callersFunctionget_out_channel
(layer)
models/networks/normalization.py:56
↓ 3 callersFunctionget_valid_openpose_keypoints
(keypoint_array)
data/preprocess/util/util.py:22
↓ 3 callersFunctionget_video_params
(opt, n_frames_total, cur_seq_len, index)
data/base_dataset.py:101
↓ 3 callersMethodinitialize
(self, opt)
models/flownet.py:19
↓ 3 callersFunctionis_image_file
(filename)
data/image_folder.py:18
↓ 3 callersMethodload_pretrained_net
(self, net_src, net_dst)
models/networks/base_network.py:117
↓ 3 callersMethodmodify_commandline_options
(parser, is_train)
data/fewshot_face_dataset.py:19
↓ 3 callersFunctionpick_ref
(refs, ref_idx)
models/networks/base_network.py:40
↓ 3 callersMethodput
(self, result)
models/networks/sync_batchnorm/comm.py:26
↓ 3 callersMethodsave_networks
(self, which_epoch)
models/base_model.py:219
↓ 2 callersFunctionCreateDataLoader
(opt)
data/data_loader.py:8
↓ 2 callersFunctionWrapModel
(opt, model)
models/models.py:40
↓ 2 callersMethod__init__
(self, gan_mode, target_real_label=1.0, target_fake_label=0.0, tensor=torch.FloatTensor, opt=
models/networks/loss.py:18
↓ 2 callersMethod__init__
(self, opt, n_frames_G)
models/networks/generator.py:457
↓ 2 callersMethod_check_input_dim
(self, input)
models/networks/sync_batchnorm/batchnorm.py:184
↓ 2 callersFunction_sum_ft
sum over the first and last dimention
models/networks/sync_batchnorm/batchnorm.py:24
↓ 2 callersFunctionas_numpy
(v)
models/networks/sync_batchnorm/unittest.py:17
↓ 2 callersMethodattention_encode
(self, img, net_name)
models/networks/generator.py:291
↓ 2 callersMethodattention_module
(self, x, label, label_ref, attention=None)
models/networks/generator.py:298
↓ 2 callersFunctioncheck_path_valid
(A_paths, B_paths)
data/image_folder.py:77
↓ 2 callersMethodcompute_flow_and_conf
(self, im1, im2)
models/flownet.py:64
↓ 2 callersMethodcompute_flow_loss
(self, flow, warped_image, tgt_image, flow_gt, flow_conf_gt, fg_mask)
models/loss_collector.py:156
↓ 2 callersMethodcompute_mask_loss
(self, flow_mask, warped_image, tgt_image, fake_image, fake_raw_image)
models/loss_collector.py:190
↓ 2 callersMethodconcat
(self, tensors, dim=0)
models/base_model.py:106
↓ 2 callersMethodconcat_prev
(self, prev, now)
models/vid2vid_model.py:169
↓ 2 callersFunctioncreate_model
(opt, epoch=0)
models/models.py:16
↓ 2 callersMethodcrop_person_region
(self, A_img, crop_coords, pose_pts=None, size=None)
data/fewshot_pose_dataset.py:193
↓ 2 callersMethoddiscriminate
(self, netD, tgt_label, fake_image, tgt_image, ref_image, for_discriminator)
models/loss_collector.py:47
↓ 2 callersFunctiondownload_file_from_google_drive
(id, destination)
scripts/download_gdrive.py:10
↓ 2 callersMethodencode
(self, ref)
models/networks/discriminator.py:184
↓ 2 callersFunctionencode_label
(opt, label_map)
models/input_process.py:25
↓ 2 callersFunctionexecute_replication_callbacks
Execute an replication callback `__data_parallel_replicate__` on each module created by original replication. The callback will be invoked w
models/networks/sync_batchnorm/replicate.py:34
↓ 2 callersFunctionfind_dataset_using_name
(dataset_name)
data/__init__.py:11
↓ 2 callersMethodflowNet_forward
(self, input_A, input_B)
models/flownet.py:52
↓ 2 callersMethodforward
(self, input, label=None, weight=None)
models/networks/architecture.py:53
↓ 2 callersMethodforward_discriminator
(self, tgt_label, tgt_image, ref_labels, ref_images, prevs=[None]*3)
models/vid2vid_model.py:106
↓ 2 callersMethodforward_generator
(self, tgt_label, tgt_image, ref_labels, ref_images, prevs=[None]*3, flow_gt=[None]*2, conf_gt=[None]*2)
models/vid2vid_model.py:62
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