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Functions169 in github.com/chibohe/text_recognition_toolbox

⨍ Functions 169◇ Types & classes 59
↓ 14 callersMethod__init__
(self, flags)
networks/SATRN.py:31
↓ 12 callersMethodencode
(self, src)
networks/SATRN.py:68
↓ 6 callersMethoddecode
(self, memory, tgt)
networks/SATRN.py:71
↓ 5 callersMethod__init__
(self, flags)
networks/DAN.py:21
↓ 5 callersMethod__init__
(self, flags)
networks/SAR.py:22
↓ 5 callersMethod__init__
(self, flags)
networks/FAN.py:20
↓ 5 callersMethod__init__
(self, input_channel, output_channel, num_iterations, kernel_size, pad)
networks/GRCNN.py:77
↓ 5 callersMethod_make_layer
(self, planes, block, stride, num_layer)
networks/DAN.py:101
↓ 5 callersFunctionclones
Produce N identical layers.
networks/SATRN.py:85
↓ 5 callersMethodget
(self)
flags.py:34
↓ 4 callersMethod_make_layer
(self, block, planes, blocks)
networks/SAR.py:116
↓ 4 callersMethod_make_layer
(self, block, planes, blocks)
networks/FAN.py:188
↓ 3 callersMethod__init__
(self, flags)
networks/CRNN.py:19
↓ 3 callersFunctionbuild_config
()
program.py:44
↓ 3 callersFunctioncreate_module
(module_str)
utils.py:67
↓ 3 callersFunctionsave_checkpoint
(checkpoint_path, model, optimizer, **kwargs)
utils.py:38
↓ 2 callersMethod_char_one_hot
(self, input_char, onehot_dim)
networks/DAN.py:269
↓ 2 callersMethod_char_one_hot
(self, input_char, onehot_dim)
networks/SAR.py:176
↓ 2 callersMethod_char_one_hot
(self, input_char, onehot_dim)
networks/FAN.py:50
↓ 2 callersMethod_conv3x3
(self, inplanes, planes)
networks/FAN.py:129
↓ 2 callersMethodapply
(self, img)
dataset.py:395
↓ 2 callersFunctionbuild_data_loader
(flags=None, mode=None)
program.py:61
↓ 2 callersFunctionbuild_device
(flags)
program.py:98
↓ 2 callersFunctionbuild_model
(flags)
program.py:53
↓ 2 callersFunctionbuild_optimizer
(flags, model)
program.py:71
↓ 2 callersFunctionbuild_pretrained_weights
(flags, model, optimizer)
program.py:84
↓ 2 callersMethoddecode
convert text-index into text-label.
character.py:73
↓ 2 callersFunctionget_characters
(dict_path)
utils.py:172
↓ 2 callersFunctionhierarchical_dataset
select_data='/' contains all sub-directory of root directory
dataset.py:136
↓ 2 callersMethodtrain
(self)
trainer.py:46
↓ 2 callersFunctionwriteCache
(env, cache)
tools/create_lmdb_dataset.py:22
↓ 1 callersMethodIwantshapes
(self)
networks/DAN.py:164
↓ 1 callersMethod__init__
(self, params, reduction='mean')
loss.py:13
↓ 1 callersFunctionattention
(query, key, value, dropout=None)
networks/SATRN.py:267
↓ 1 callersFunctionbuild_loss
(flags)
program.py:113
↓ 1 callersFunctionbuild_trainer
(model, optimizer, loss, train_loader, val_loader, \ device, flags, global_state)
program.py:119
↓ 1 callersFunctioncheckImageIsValid
(imageBin)
tools/create_lmdb_dataset.py:11
↓ 1 callersFunctiondict_to_namedtuple
(d)
flags.py:12
↓ 1 callersMethodevaluate
(self)
trainer.py:117
↓ 1 callersMethodget_batch
(self)
dataset.py:94
↓ 1 callersFunctioninitial_logger
ARGS log_file_path: string, path to the logging file
utils.py:47
↓ 1 callersFunctionload_checkpoint
(_model, pretrained_weights, to_use_device, _optimizer=None)
utils.py:17
↓ 1 callersFunctionmain
()
train.py:29
↓ 1 callersMethodparse_args
(self, argv=None)
program.py:37
↓ 1 callersMethodpredict
(self, image_tensor)
predict.py:74
↓ 1 callersMethodpreprocess
(self, image)
predict.py:46
Method__call__
(self, image)
predict.py:88
Method__call__
(self, predictions, labels)
utils.py:86
Method__call__
(self, img)
dataset.py:311
Method__call__
(self, img)
dataset.py:326
Method__call__
(self, batch)
dataset.py:346
Method__getitem__
(self, index)
dataset.py:219
Method__getitem__
(self, index)
dataset.py:285
Method__init__
(self, params)
loss.py:29
Method__init__
(self, config_file)
flags.py:28
Method__init__
(self)
predict.py:27
Method__init__
文本识别相关指标计算类 :param converter: 用于label转换的转换器
utils.py:78
Method__init__
Modulate the data ratio in the batch. For example, when select_data is "MJ-ST" and batch_ratio is "0.5-0.5", the 50% of the b
dataset.py:29
Method__init__
(self, root, characters, params)
dataset.py:164
Method__init__
(self, root, params)
dataset.py:266
Method__init__
(self, size, interpolation=Image.BICUBIC)
dataset.py:306
Method__init__
(self, max_size, PAD_type='right')
dataset.py:320
Method__init__
(self, imgH=32, imgW=100, keep_ratio_with_pad=False, data_augment=False)
dataset.py:340
Method__init__
(self)
dataset.py:392
Method__init__
(self)
program.py:32
Method__init__
(self, flags)
character.py:15
Method__init__
(self, flags)
character.py:93
Method__init__
(self, device, model, optimizer, loss, val_loader, \ train_loader, flags, global_state)
trainer.py:27
Method__init__
(self, inplanes)
networks/CRNN.py:42
Method__init__
(self)
networks/CRNN.py:72
Method__init__
(self, num_inputs, num_hiddens)
networks/CRNN.py:83
Method__init__
(self, inplanes, planes, stride=1, downsample=None)
networks/DAN.py:53
Method__init__
(self, inplanes, block, strides, layers, compress_layer=True)
networks/DAN.py:81
Method__init__
(self, input_shape, block, strides, layers, compress_layer=True)
networks/DAN.py:155
Method__init__
(self, scales, maxT, depth, num_channel)
networks/DAN.py:172
Method__init__
(self, nclass, nchannel, dropout = 0.3)
networks/DAN.py:258
Method__init__
(self, inplanes, planes, downsample=None)
networks/SAR.py:48
Method__init__
(self, in_channel, out_channel, block, layers)
networks/SAR.py:76
Method__init__
(self, input_size, hidden_size)
networks/SAR.py:145
Method__init__
(self, input_size, en_hidden_size, de_hidden_size, num_classes)
networks/SAR.py:166
Method__init__
(self, input_size, en_hidden_size, de_hidden_size)
networks/SAR.py:212
Method__init__
(self, d_model, vocab)
networks/SATRN.py:77
Method__init__
(self, layer, N)
networks/SATRN.py:92
Method__init__
(self, features, eps=1e-6)
networks/SATRN.py:106
Method__init__
(self, size, dropout)
networks/SATRN.py:123
Method__init__
(self, size, self_attn, feed_forward, dropout)
networks/SATRN.py:135
Method__init__
(self, layer, N)
networks/SATRN.py:150
Method__init__
(self, size, self_attn, src_attn, feed_forward, dropout)
networks/SATRN.py:163
Method__init__
(self, in_channels, out_channels)
networks/SATRN.py:180
Method__init__
(self, d_model, dropout, max_len=5000)
networks/SATRN.py:200
Method__init__
(self, d_model, dropout, max_len=1000)
networks/SATRN.py:221
Method__init__
(self, h, d_model, dropout=0.1)
networks/SATRN.py:279
Method__init__
(self, in_channels, inter_channels, out_channels)
networks/SATRN.py:309
Method__init__
(self, d_model, d_ff, dropout=0.1)
networks/SATRN.py:333
Method__init__
(self, vocab, d_model)
networks/SATRN.py:345
Method__init__
(self, input_size, hidden_size, num_classes)
networks/FAN.py:42
Method__init__
(self)
networks/FAN.py:87
Method__init__
(self, input_size, hidden_size, num_embeddings)
networks/FAN.py:98
Method__init__
(self, inplanes, planes, downsample=None)
networks/FAN.py:120
Method__init__
(self, input_channel, output_channel, block, layers)
networks/FAN.py:153
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