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Functions408 in github.com/Thmen/EGVSR

⨍ Functions 408◇ Types & classes 85
Method__init__
(self, channels_in, channels_out, kernel_size=3)
codes/models/networks/sofvsr_nets.py:47
Method__init__
(self, upscale_factor, is_training)
codes/models/networks/sofvsr_nets.py:78
Method__init__
(self, upscale_factor, is_training)
codes/models/networks/sofvsr_nets.py:151
Method__init__
(self, scale, is_training=False)
codes/models/networks/sofvsr_nets.py:179
Method__init__
(self, optimizer, T_period, restarts=None, weights=None, eta_min=0, last_epoch=-1)
codes/models/optim/lr_schedules.py:11
Method__init__
(self, reduction='mean')
codes/models/optim/losses.py:7
Method__init__
(self, eps=1e-6, reduction='sum')
codes/models/optim/losses.py:38
Method__init__
(self, eps=1e-8)
codes/models/optim/losses.py:57
Method__init__
(self)
codes/official_metrics/metrics.py:95
Method__init__
(self)
codes/official_metrics/LPIPSmodels/base_model.py:10
Method__init__
(self, requires_grad=False, pretrained=True)
codes/official_metrics/LPIPSmodels/pretrained_networks.py:7
Method__init__
(self, requires_grad=False, pretrained=True)
codes/official_metrics/LPIPSmodels/pretrained_networks.py:58
Method__init__
(self, requires_grad=False, pretrained=True, num=18)
codes/official_metrics/LPIPSmodels/pretrained_networks.py:140
Method__init__
(self, frequency=1)
codes/official_metrics/LPIPSmodels/util.py:370
Method__init__
(self, pnet_type='vgg', pnet_rand=False, pnet_tune=False, use_dropout=True, use_gpu=True, spatial=False, versi
codes/official_metrics/LPIPSmodels/networks_basic.py:75
Method__init__
(self, chn_mid=32,use_sigmoid=True)
codes/official_metrics/LPIPSmodels/networks_basic.py:181
Method__init__
(self, use_gpu=True, chn_mid=32)
codes/official_metrics/LPIPSmodels/networks_basic.py:196
Method__init__
(self, chn_in, chn_out=1, use_dropout=False)
codes/official_metrics/LPIPSmodels/networks_basic.py:216
Method__init__
(self, use_gpu=True, colorspace='Lab')
codes/official_metrics/LPIPSmodels/networks_basic.py:226
Method__len__
(self)
codes/data/paired_folder_dataset.py:30
Method__len__
(self)
codes/data/base_dataset.py:17
Method__len__
(self)
codes/data/paired_lmdb_dataset.py:42
Method__len__
(self)
codes/data/unpaired_lmdb_dataset.py:32
Methodaugment_sequence
(**kwargs)
codes/data/base_dataset.py:76
Functionbootstrap
(in_vec,num_samples=100,bootfunc=np.mean)
codes/official_metrics/LPIPSmodels/util.py:34
Functioncanonicalize
Convert data to torch tensor with type float32 Assume data has type np.uint8/np.float32 or torch.uint8/torch.float32, and uint8 data
codes/utils/data_utils.py:87
Methodcompute_dataset_metrics
compute metrics for a dataset, *_dir are the root of dataset, which contains several video clips/folders
codes/metrics/metric_calculator.py:132
Methodconfig_training
(self)
codes/models/base_model.py:27
Methodconfig_training
(self)
codes/models/vsrgan_model.py:55
Methodconvert_output
(d0)
codes/official_metrics/LPIPSmodels/dist_model.py:133
Functioncos_sim
(in0,in1)
codes/official_metrics/LPIPSmodels/util.py:77
Functioncos_sim_blob
(in0,in1)
codes/official_metrics/LPIPSmodels/util.py:65
Functioncreate_kernel
(opt)
codes/utils/data_utils.py:11
Methodcrop_sequence
(self, **kwargs)
codes/data/base_dataset.py:72
Functiondatetime_str
()
codes/official_metrics/LPIPSmodels/util.py:18
Functiondiagnose_network
(net, name='network')
codes/official_metrics/LPIPSmodels/util.py:150
Functiondownsample_worker
(filepath, mode='BD')
scripts/resize_BD_BI.py:26
Functiondssim
(p0, p1, range=255.)
codes/metrics/LPIPS/models/__init__.py:53
Functiondssim
(p0, p1, range=255.)
codes/official_metrics/LPIPSmodels/util.py:50
Functionflatten_nested_list
(nested_list)
codes/official_metrics/LPIPSmodels/util.py:379
Methodflush
(self)
codes/official_metrics/metrics.py:102
Methodforward
(self, input)
codes/utils/net_utils.py:136
Methodforward
(self, inputs, u, v=None, gain=1)
codes/utils/motion.py:67
Methodforward
Estimate optical flow from `ref` frame to `target` frame
codes/utils/motion.py:170
Methodforward
Estimate densely optical flow from `ref` to `target` Args: target: frame A ref: frame B gain: a scalar multipli
codes/utils/motion.py:220
Methodforward
(self)
codes/metrics/LPIPS/models/base_model.py:18
Methodforward
Pred and target are Variables. If normalize is True, assumes the images are between [0,1] and then scales them between [-1,+1]
codes/metrics/LPIPS/models/__init__.py:27
Methodforward
(self, X)
codes/metrics/LPIPS/models/pretrained_networks.py:36
Methodforward
(self, X)
codes/metrics/LPIPS/models/pretrained_networks.py:81
Methodforward
(self, X)
codes/metrics/LPIPS/models/pretrained_networks.py:121
Methodforward
(self, X)
codes/metrics/LPIPS/models/pretrained_networks.py:163
Methodforward
(self, in0, in1, retPerLayer=False)
codes/metrics/LPIPS/models/networks_basic.py:64
Methodforward
(self, inp)
codes/metrics/LPIPS/models/networks_basic.py:100
Methodforward
(self,d0,d1,eps=0.1)
codes/metrics/LPIPS/models/networks_basic.py:128
Methodforward
(self, d0, d1, judge)
codes/metrics/LPIPS/models/networks_basic.py:138
Methodforward
(self, in0, in1, retPerLayer=None)
codes/metrics/LPIPS/models/networks_basic.py:169
Methodforward
forward pass for a singe frame
codes/models/networks/base_nets.py:14
Methodforward
forward pass for a singe frame
codes/models/networks/base_nets.py:34
Methodforward
(self, inputs)
codes/models/networks/vespcn_nets.py:26
Methodforward
(self, target, ref)
codes/models/networks/vespcn_nets.py:41
Methodforward
(self, inputs)
codes/models/networks/vespcn_nets.py:60
Methodforward
Compute optical flow from x1 to x2
codes/models/networks/tecogan_nets_bk.py:64
Methodforward
(self, x)
codes/models/networks/tecogan_nets_bk.py:94
Methodforward
lr_curr: the current lr data in shape nchw hr_prev_tran: the previous transformed hr_data in shape n(4*4*c)hw
codes/models/networks/tecogan_nets_bk.py:129
Methodforward
(self, x)
codes/models/networks/tecogan_nets_bk.py:316
Methodforward
Compute optical flow from x1 to x2
codes/models/networks/egvsr_nets.py:63
Methodforward
(self, x)
codes/models/networks/egvsr_nets.py:93
Methodforward
lr_curr: the current lr data in shape nchw hr_prev_tran: the previous transformed hr_data in shape n(4*4*c)hw
codes/models/networks/egvsr_nets.py:132
Methodforward
(self, x)
codes/models/networks/egvsr_nets.py:319
Methodforward
Compute optical flow from x1 to x2
codes/models/networks/tecogan_nets.py:65
Methodforward
(self, x)
codes/models/networks/tecogan_nets.py:95
Methodforward
lr_curr: the current lr data in shape nchw hr_prev_tran: the previous transformed hr_data in shape n(4*4*c)hw
codes/models/networks/tecogan_nets.py:130
Methodforward
(self, x)
codes/models/networks/tecogan_nets.py:322
Methodforward
(self, x)
codes/models/networks/vgg_nets.py:27
Methodforward
(self, x)
codes/models/networks/sofvsr_nets.py:53
Methodforward
(self, x)
codes/models/networks/sofvsr_nets.py:70
Methodforward
(self, x)
codes/models/networks/sofvsr_nets.py:105
Methodforward
(self, x)
codes/models/networks/sofvsr_nets.py:164
Methodforward
:param status: boolean, True/False
codes/models/optim/losses.py:11
Methodforward
:param status: boolean, True/False
codes/models/optim/losses.py:25
Methodforward
(self, x, y)
codes/models/optim/losses.py:43
Methodforward
(self, input, target)
codes/models/optim/losses.py:61
Methodforward
(self)
codes/official_metrics/LPIPSmodels/base_model.py:21
Methodforward
(self, X)
codes/official_metrics/LPIPSmodels/pretrained_networks.py:36
Methodforward
(self, X)
codes/official_metrics/LPIPSmodels/pretrained_networks.py:81
Methodforward
(self, X)
codes/official_metrics/LPIPSmodels/pretrained_networks.py:121
Methodforward
(self, X)
codes/official_metrics/LPIPSmodels/pretrained_networks.py:163
Methodforward
(self, in0, in1, retPerLayer=False)
codes/official_metrics/LPIPSmodels/networks_basic.py:49
Methodforward
(self, in0, in1)
codes/official_metrics/LPIPSmodels/networks_basic.py:130
Methodforward
(self,d0,d1,eps=0.1)
codes/official_metrics/LPIPSmodels/networks_basic.py:192
Methodforward
(self, d0, d1, judge)
codes/official_metrics/LPIPSmodels/networks_basic.py:207
Methodforward
(self, in0, in1)
codes/official_metrics/LPIPSmodels/networks_basic.py:250
Methodforward_sequence
forward pass for a whole sequence (for training)
codes/models/networks/base_nets.py:19
Methodforward_sequence
forward pass for a whole sequence (for training)
codes/models/networks/base_nets.py:39
Methodforward_sequence
Parameters: :param lr_data: lr data in shape ntchw
codes/models/networks/tecogan_nets_bk.py:203
Methodforward_sequence
:param data: should be either hr_data or gt_data :param args_dict: a dict including data/config needed here
codes/models/networks/tecogan_nets_bk.py:360
Methodforward_sequence
(self, data, args_dict)
codes/models/networks/tecogan_nets_bk.py:488
Methodforward_sequence
:param data: should be either hr_data or gt_data :param args_dict: a dict including data/config needed here
codes/models/networks/egvsr_nets.py:363
Methodforward_sequence
(self, data, args_dict)
codes/models/networks/egvsr_nets.py:491
Methodforward_sequence
Parameters: :param lr_data: lr data in shape ntchw
codes/models/networks/tecogan_nets.py:204
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