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Functions528 in github.com/cavalleria/cavaface

⨍ Functions 528◇ Types & classes 126↳ Endpoints 4
Method__init__
( self, in_channels, out_channels, kernel_size, stride, bn_eps, expansion )
backbone/proxylessnas.py:37
Method__init__
( self, in_channels, out_channels, kernel_size, stride, bn_eps
backbone/proxylessnas.py:102
Method__init__
( self, probability=0.5, sl=0.02, sh=0.4, r1=0.3, mean=[0.4914, 0.4822, 0.4465] )
dataset/utils.py:23
Method__init__
( self, p=0.5, scale=(0.02, 0.4), ratio=(0.4, 1 / 0.4), value=(0, 255)
dataset/utils.py:105
Method__init__
(self, root_dir, transform)
dataset/datasets.py:14
Method__init__
(self, root_dir, transform, Train=True)
dataset/datasets.py:133
Method__init__
(self, classes)
dataset/datasets.py:175
Method__init__
(self, n=2, m=9)
dataset/randaugment.py:176
Method__init__
(self, in_features, out_features)
head/metrics.py:20
Method__init__
(self, in_features, out_features, s=64.0, m_arc=0.50, m_am=0.0)
head/metrics.py:52
Method__init__
( self, in_features, out_features, s=64.0, m2=0.30, m3=0.2, easy_margin=False )
head/metrics.py:101
Method__init__
(self, in_features, out_features, s=64.0, m=0.35)
head/metrics.py:150
Method__init__
(self, in_features, out_features, m=4.0)
head/metrics.py:238
Method__init__
(self, in_features, out_features, m=0.35, s=30.0)
head/metrics.py:319
Method__init__
(self, in_features, out_features, m=0.5, s=64.0)
head/metrics.py:359
Method__init__
( self, in_features, out_features, scale=64, margin=0.5, easy_margin=False )
head/metrics.py:416
Method__init__
( self, in_features, out_features, xtype="MV-AM", s=32.0, m=0.
head/metrics.py:481
Method__init__
(self, in_features, out_features, s=64.0, m=0.45)
head/metrics.py:553
Method__init__
(self, in_features, out_features, s=6.0, m=0.5)
head/metrics.py:594
Method__init__
(self, in_features, out_features, m=0.25, gamma=256)
head/metrics.py:626
Method__init__
( self, in_features, out_features, bias=True, dim=None, m=0.5,
head/metrics_parallel.py:10
Method__init__
(self, args)
evaluation/eval_ijbc.py:37
Method__init__
(self, args)
evaluation/eval_megaface.py:24
Method__init__
(self)
evaluation/evaluate_service.py:196
Method__init__
(self, n_splits = 2, shuffle = False)
evaluation/utils/io.py:303
Method__init__
(self, *functions, **kwargs)
evaluation/utils/pytorch_memlab/line_profiler.py:49
Method__init__
(self, model=None)
evaluation/utils/pytorch_memlab/mem_reporter.py:24
Method__init__
(self)
evaluation/utils/pytorch_memlab/courtesy.py:11
Method__init__
(self, args, dtype="fp32")
evaluation/infer/citrus_pytorch_infer.py:23
Method__init__
(self, out_q, write_func, tasks)
evaluation/infer/citrus_base_infer.py:60
Method__init__
(self, net, fwd_func, in_q, out_q, image_shape, is_flip)
evaluation/infer/citrus_base_infer.py:131
Method__init__
(self, args, dtype="fp32")
evaluation/infer/citrus_base_infer.py:260
Method__init__
(self, save_rate=2)
loss/loss.py:21
Method__init__
(self, classes, smoothing=0.1, dim=-1)
loss/loss.py:49
Method__init__
( self, weight=None, size_average=None, ignore_index=-100, reduce=None
loss/loss.py:64
Method__init__
(self)
util/verification.py:226
Method__init__
:param optimizer:inner optimizer :param k (int): number of lookahead steps :param alpha(float): linear interpolation factor.
optimizer/optimizer.py:14
Method__init__
( self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8, weight_
optimizer/optimizer.py:115
Method__init__
( self, params, lr=1e-3, # lr alpha=0.5, k=6, N_sma_threshhol
optimizer/optimizer.py:238
Method__init__
( self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8, weight_
optimizer/optimizer.py:418
Method__init__
( self, optimizer, batches, epochs, base_lr, target_lr=0,
optimizer/lr_scheduler.py:36
Method__len__
(self)
dataset/datasets.py:60
Method__len__
(self)
dataset/datasets.py:122
Method__len__
(self)
dataset/datasets.py:170
Method__len__
(self)
dataset/datasets.py:188
Method__repr__
(self)
backbone/common.py:165
Method__repr__
(self)
head/metrics.py:176
Method__repr__
(self)
head/metrics.py:289
Method__setstate__
(self, state)
optimizer/optimizer.py:306
Method_backup_and_load_cache
Useful for performing evaluation on the slow weights (which typically generalize better)
optimizer/optimizer.py:60
Function_cal_self_similarity
(pairs)
evaluation/utils/io.py:188
Function_cal_similarity
(probe, gallery)
evaluation/utils/io.py:124
Method_channel_view
(self, x)
optimizer/optimizer.py:440
Method_channel_view
(self, x)
optimizer/optimizer.py:561
Method_clear_and_load_backup
(self)
optimizer/optimizer.py:70
Function_create_model
(variant)
backbone/hrnet.py:862
Method_layer_view
(self, x)
optimizer/optimizer.py:443
Method_layer_view
(self, x)
optimizer/optimizer.py:564
Method_load_from_state_dict
( self, state_dict, prefix, local_metadata, strict, missing_ke
backbone/common.py:545
Function_load_image_bin
(path, image_shape)
evaluation/utils/io.py:269
Method_load_model
(self)
evaluation/infer/citrus_pytorch_infer.py:26
Function_merge_results
(args, net, test_type=None)
evaluation/utils/io.py:40
Function_rank_accuracy
(preds, labels)
evaluation/utils/io.py:245
Function_read_image
(image_path, gray=False)
evaluation/utils/io.py:90
Method_read_templates
(self, file_list)
evaluation/eval_ijbc.py:198
Method_save_to_state_dict
overwrite save method
backbone/common.py:571
Function_write_result_to_file
(outfilename, result_list)
evaluation/utils/io.py:78
Functionaccuracy
Computes the precision@k for the specified values of k
util/verification.py:242
Functionalive
()
evaluation/evaluate_service.py:44
Functionbn_hook
(self, input, output)
util/flops_counter.py:74
Methodcalc_flops
(self, x)
backbone/common.py:174
Functioncalculate_val
Copy from [insightface](https://github.com/deepinsight/insightface) :param thresholds: :param embeddings1: :param embeddings2: :p
util/verification.py:121
Methodclear
(self)
evaluation/eval_megaface.py:451
Functionconv_hook
(self, input, output)
util/flops_counter.py:39
Functiondensenet
Create DenseNet model with specific parameters.
backbone/densenet.py:142
Functiondwconv5x5_block
5x5 depthwise version of the standard convolution block.
backbone/common.py:816
Functionefficientnet
Create EfficientNet model with specific parameters.
backbone/efficientnet.py:385
Functioneval_func
()
evaluation/evaluate_service.py:49
Functionevaluate
(embeddings, actual_issame, nrof_folds=10, pca = 0)
evaluation/utils/io.py:425
Functionevaluate_with_uncertainty
( embeddings, uncertaintys, actual_issame, nrof_folds=10, mls=True )
util/verification.py:182
Methodextra_repr
(self)
backbone/common.py:575
Methodextra_repr
(self)
head/metrics_parallel.py:92
Methodextract_embedding
(self, net)
evaluation/eval_megaface.py:156
Functionforward
(net, blob)
evaluation/utils/pytorch_tool.py:31
Methodforward
(self, inputs)
backbone/resnest.py:27
Methodforward
(self, x)
backbone/resnest.py:132
Methodforward
(self, x)
backbone/resnest.py:485
Methodforward
(self, x)
backbone/ghostnet.py:61
Methodforward
(self, x)
backbone/ghostnet.py:79
Methodforward
(self, x)
backbone/ghostnet.py:117
Methodforward
(self, x)
backbone/ghostnet.py:185
Methodforward
(self, x)
backbone/ghostnet.py:302
Methodforward
(self, x)
backbone/resnet_irse.py:140
Methodforward
(self, x)
backbone/hrnet.py:354
Methodforward
(self, x)
backbone/hrnet.py:392
Methodforward
(self, x)
backbone/hrnet.py:583
Methodforward
(self, x)
backbone/hrnet.py:857
Methodforward
(self, x)
backbone/densenet.py:47
Methodforward
(self, x)
backbone/densenet.py:77
Methodforward
(self, x)
backbone/densenet.py:135
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