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Functions408 in github.com/Thmen/EGVSR

⨍ Functions 408◇ Types & classes 85
↓ 11 callersMethodforward
(self, in0, in1)
codes/official_metrics/LPIPSmodels/networks_basic.py:233
↓ 9 callersFunctionbackward_warp
Backward warp `x` according to `flow` Both x and flow are pytorch tensor in shape `nchw` and `n2hw` Reference: https://
codes/utils/net_utils.py:50
↓ 9 callersFunctiondefine_criterion
(criterion_opt)
codes/models/optim/__init__.py:5
↓ 8 callersMethodsave
(self, current_iter)
codes/models/vsr_model.py:143
↓ 7 callersMethodparse_lmdb_key
(key)
codes/data/base_dataset.py:58
↓ 6 callersMethod__init__
(self, in_nc)
codes/models/networks/tecogan_nets_bk.py:17
↓ 6 callersMethod__init__
(self, in_nc)
codes/models/networks/egvsr_nets.py:16
↓ 6 callersMethod__init__
(self, in_nc)
codes/models/networks/tecogan_nets.py:18
↓ 6 callersFunctionappend
(loss_dict, loss_name, loss_value)
scripts/monitor_training.py:12
↓ 6 callersFunctiondefine_generator
(opt)
codes/models/networks/__init__.py:3
↓ 6 callersMethodforward_sequence
Parameters: :param lr_data: lr data in shape ntchw
codes/models/networks/egvsr_nets.py:206
↓ 6 callersMethodload_network
(self, net, load_path)
codes/models/base_model.py:88
↓ 6 callersFunctionoptical_flow_warp
Arguments image_ref: reference images tensor, (b, c, h, w) image_optical_flow: optical flow to image_ref (b, 2, h, w)
codes/models/networks/sofvsr_nets.py:20
↓ 6 callersMethodread_lmdb_frame
(env, key, size)
codes/data/base_dataset.py:66
↓ 6 callersFunctionspace_to_depth
Equivalent to tf.space_to_depth()
codes/utils/net_utils.py:36
↓ 5 callersMethod__init__
(self, pnet_type='vgg', pnet_rand=False, pnet_tune=False, use_dropout=True, spatial=False, version='0.1', lpip
codes/metrics/LPIPS/models/networks_basic.py:28
↓ 5 callersMethod__init__
(self, pnet_type='vgg', pnet_rand=False, use_gpu=True)
codes/official_metrics/LPIPSmodels/networks_basic.py:22
↓ 5 callersFunctionfloat32_to_uint8
Convert np.float32 array to np.uint8 Parameters: :param input: np.float32, (NT)CHW, [0, 1] :return: np.uint8, (NT)CH
codes/utils/data_utils.py:77
↓ 5 callersMethodforward
(self, in0, in1, retPerLayer=None)
codes/metrics/LPIPS/models/networks_basic.py:152
↓ 4 callersMethod__init__
(self, nDenselayer, channels, growth)
codes/models/networks/sofvsr_nets.py:60
↓ 4 callersFunction_rgb2ycbcr
(img, maxVal=255)
codes/official_metrics/metrics.py:37
↓ 4 callersFunctioncreate_dataloader
(opt, dataset_idx='train')
codes/data/__init__.py:10
↓ 4 callersFunctioncrop_8x8
( img )
codes/official_metrics/metrics.py:77
↓ 4 callersMethodinfer_sequence
Parameters: :param lr_data: torch.FloatTensor in shape tchw :param device: torch.device
codes/models/networks/egvsr_nets.py:259
↓ 4 callersMethodpad_sequence
Parameters: :param lr_data: tensor in shape tchw
codes/models/base_model.py:91
↓ 4 callersFunctionto_uint8
(x, vmin, vmax)
codes/official_metrics/metrics.py:58
↓ 3 callersMethod__init__
(self, requires_grad=False, pretrained=True)
codes/metrics/LPIPS/models/pretrained_networks.py:98
↓ 3 callersMethod__init__
(self, scale, channel, depth)
codes/models/networks/vespcn_nets.py:48
↓ 3 callersMethod__init__
(self, reduction='mean')
codes/models/optim/losses.py:21
↓ 3 callersMethod__init__
(self, requires_grad=False, pretrained=True)
codes/official_metrics/LPIPSmodels/pretrained_networks.py:98
↓ 3 callersMethodcompute_sequence_metrics
(self, seq, true_seq_dir, pred_seq_dir, pred_seq=None)
codes/metrics/metric_calculator.py:150
↓ 3 callersFunctiondefine_lr_schedule
(schedule_opt, optimizer)
codes/models/optim/__init__.py:39
↓ 3 callersFunctiondefine_model
(opt)
codes/models/__init__.py:19
↓ 3 callersMethodforward
Function computes the distance between image patches in0 and in1 INPUTS in0, in1 - torch.Tensor object of shape Nx3xXxY - image p
codes/metrics/LPIPS/models/dist_model.py:105
↓ 3 callersMethodforward
Function computes the distance between image patches in0 and in1 INPUTS in0, in1 - torch.Tensor object of shape Nx3xXxY - image p
codes/official_metrics/LPIPSmodels/dist_model.py:111
↓ 3 callersMethodforward_pair
(self,in1,in2,retPerLayer=False)
codes/official_metrics/LPIPSmodels/dist_model.py:105
↓ 3 callersFunctionget_upsampling_func
(scale=4, degradation='BI')
codes/utils/net_utils.py:86
↓ 3 callersMethodinfer
Function of inference Parameters: :param lr_data: a rgb video sequence with shape thwc :return: a rgb vi
codes/models/vsr_model.py:121
↓ 3 callersMethodinit_lmdb
(seq_dir)
codes/data/base_dataset.py:52
↓ 3 callersMethodsave_network
(self, network, path, network_label, epoch_label)
codes/metrics/LPIPS/models/base_model.py:37
↓ 3 callersMethodsave_network
(self, net, net_label, current_iter)
codes/models/base_model.py:79
↓ 2 callersMethod__init__
(self, mode='bilinear', padding_mode='zeros', normalize=False)
codes/utils/motion.py:61
↓ 2 callersFunctioncheck_lmdb
(dataset, lmdb_dir, display=True)
scripts/create_lmdb.py:79
↓ 2 callersMethoddisplay_results
(self)
codes/metrics/metric_calculator.py:84
↓ 2 callersMethodgenerate_dummy_input
(self, lr_size)
codes/models/networks/egvsr_nets.py:163
↓ 2 callersMethodget_averaged_results
(self)
codes/metrics/metric_calculator.py:71
↓ 2 callersFunctionim2tensor
(image, imtype=np.uint8, cent=1., factor=255./2.)
codes/metrics/LPIPS/models/__init__.py:113
↓ 2 callersFunctionim2tensor
(image, imtype=np.uint8, cent=1., factor=255./2.)
codes/official_metrics/LPIPSmodels/util.py:142
↓ 2 callersMethodinitialize
INPUTS model - ['net-lin'] for linearly calibrated network ['net'] for off-the-shelf network
codes/metrics/LPIPS/models/dist_model.py:28
↓ 2 callersFunctionlistPNGinDir
(dirpath)
codes/official_metrics/metrics.py:28
↓ 2 callersFunctionmkdir
(path)
codes/official_metrics/LPIPSmodels/util.py:250
↓ 2 callersFunctionnormalize_blob
(in_feat,eps=1e-10)
codes/official_metrics/LPIPSmodels/util.py:61
↓ 2 callersFunctionnormalize_tensor
(in_feat,eps=1e-10)
codes/official_metrics/LPIPSmodels/util.py:72
↓ 2 callersFunctionnp2tensor
(np_obj)
codes/metrics/LPIPS/models/__init__.py:67
↓ 2 callersFunctionnp2tensor
(np_obj)
codes/official_metrics/LPIPSmodels/util.py:93
↓ 2 callersFunctionparse_json
(json_file)
scripts/monitor_training.py:74
↓ 2 callersFunctionparse_log
(log_file)
scripts/monitor_training.py:23
↓ 2 callersFunctionplot_curve
(ax, iter, value, style='-', alpha=1.0, label='', color='seagreen', start_iter=0, end_iter=-1,
scripts/monitor_training.py:87
↓ 2 callersFunctionplot_loss_curves
(loss_dict, ax, loss_type, start_iter=0, end_iter=-1, smooth=0)
scripts/monitor_training.py:106
↓ 2 callersFunctionplot_metric_curves
currently only support to plot average results
scripts/monitor_training.py:121
↓ 2 callersMethodreset_per_sequence
(self)
codes/metrics/metric_calculator.py:64
↓ 2 callersFunctionretrieve_files
retrive files with specific suffix under dir and sub-dirs recursively
codes/utils/base_utils.py:44
↓ 2 callersMethodsave
(self, label)
codes/metrics/LPIPS/models/base_model.py:33
↓ 2 callersMethodsave
(self, label)
codes/official_metrics/LPIPSmodels/base_model.py:36
↓ 2 callersMethodsave_network
(self, network, path, network_label, epoch_label)
codes/official_metrics/LPIPSmodels/base_model.py:40
↓ 2 callersMethodsave_results
(self, model_idx, save_path, override=False)
codes/metrics/metric_calculator.py:104
↓ 2 callersFunctionsetup_json_path
()
codes/utils/base_utils.py:89
↓ 2 callersFunctionsetup_res_dir
()
codes/utils/base_utils.py:81
↓ 2 callersFunctionspatial_average
(in_tens, keepdim=True)
codes/metrics/LPIPS/models/networks_basic.py:17
↓ 2 callersFunctionsplit
(pattern, string)
scripts/monitor_training.py:19
↓ 2 callersFunctionssim
(img_true, img_pred)
codes/official_metrics/metrics.py:72
↓ 2 callersFunctionupsample
(in_tens, out_HW=(64,64))
codes/metrics/LPIPS/models/networks_basic.py:20
↓ 1 callersMethod__init__
(self)
codes/models/networks/base_nets.py:5
↓ 1 callersMethodaugment_sequence
(gt_pats, lr_pats)
codes/data/paired_lmdb_dataset.py:155
↓ 1 callersMethodaugment_sequence
(pats)
codes/data/unpaired_lmdb_dataset.py:109
↓ 1 callersMethodbackward_train
(self)
codes/metrics/LPIPS/models/dist_model.py:158
↓ 1 callersMethodbackward_train
(self)
codes/official_metrics/LPIPSmodels/dist_model.py:201
↓ 1 callersFunctioncalc_gflops_per_batch
Calculate flops of conv weights (support groups_conv & dilated_conv)
codes/metrics/model_summary.py:15
↓ 1 callersMethodcheck_info
(self, gt_keys, lr_keys)
codes/data/base_dataset.py:23
↓ 1 callersMethodclamp_weights
(self)
codes/metrics/LPIPS/models/dist_model.py:123
↓ 1 callersMethodclamp_weights
(self)
codes/official_metrics/LPIPSmodels/dist_model.py:169
↓ 1 callersMethodcompute_LPIPS
(self)
codes/metrics/metric_calculator.py:226
↓ 1 callersMethodcompute_PSNR
(self)
codes/metrics/metric_calculator.py:208
↓ 1 callersMethodcompute_accuracy
d0, d1 are Variables, judge is a Tensor
codes/metrics/LPIPS/models/dist_model.py:161
↓ 1 callersMethodcompute_accuracy
d0, d1 are Variables, judge is a Tensor
codes/official_metrics/LPIPSmodels/dist_model.py:204
↓ 1 callersMethodcompute_frame_metrics
(self)
codes/metrics/metric_calculator.py:189
↓ 1 callersMethodcompute_tOF
(self)
codes/metrics/metric_calculator.py:243
↓ 1 callersMethodconfig_training
(self)
codes/models/vsr_model.py:47
↓ 1 callersFunctioncreate_gif
(image_list, gif_name, dur)
scripts/create_gif_contrast.py:67
↓ 1 callersFunctioncreate_gif
(image_list, gif_name)
scripts/create_gif.py:18
↓ 1 callersFunctioncreate_lmdb
(dataset, raw_dir, lmdb_dir, filter_file='')
scripts/create_lmdb.py:13
↓ 1 callersMethodcrop_sequence
(self, gt_frms, lr_frms)
codes/data/paired_lmdb_dataset.py:132
↓ 1 callersMethodcrop_sequence
(self, frms)
codes/data/unpaired_lmdb_dataset.py:94
↓ 1 callersFunctiondefine_discriminator
(opt)
codes/models/networks/__init__.py:45
↓ 1 callersMethodforward
(self, lr_seq)
codes/models/networks/vespcn_nets.py:79
↓ 1 callersMethodforward
Parameters: :param lr_curr: the current lr data in shape nchw :param lr_prev: the previous lr data in sha
codes/models/networks/tecogan_nets_bk.py:176
↓ 1 callersMethodforward
(self, x)
codes/models/networks/tecogan_nets_bk.py:351
↓ 1 callersMethodforward
(self, x)
codes/models/networks/tecogan_nets_bk.py:479
↓ 1 callersMethodforward
Parameters: :param lr_curr: the current lr data in shape nchw :param lr_prev: the previous lr data in sha
codes/models/networks/egvsr_nets.py:179
↓ 1 callersMethodforward
(self, x)
codes/models/networks/egvsr_nets.py:354
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