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Functions75 in github.com/Jeff-Zilence/Explain_Metric_Learning

↓ 20 callersMethodimshow_convert
convert the heatmap for imshow
Face_Verification/demo.py:75
↓ 20 callersMethodimshow_convert
convert the heatmap for imshow
Image_Retrieval/demo.py:76
↓ 16 callersMethodimshow_convert
convert the heatmap for imshow
Geo-localization/demo.py:63
↓ 13 callersMethodconv_layer
(self, x, kernel_dim, input_dim, output_dim, trainable, activated, name='layer_conv', activ
Geo-localization/Model/models.py:57
↓ 12 callersMethodimshow_convert
convert the heatmap for imshow
Person_Re-identification/demo.py:76
↓ 4 callersMethodGradCAM
(self, map, size = (112, 112))
Face_Verification/demo.py:82
↓ 4 callersMethodGradCAM
(self, map, size = (224, 224))
Image_Retrieval/demo.py:83
↓ 4 callersMethodGradCAM
(self, sess, cost , target, feed_dict, size)
Geo-localization/demo.py:71
↓ 4 callersMethod__init__
(self, block, layers, use_se=True)
Face_Verification/Model/models.py:143
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1)
Face_Verification/Model/models.py:170
↓ 4 callersFunctionconv3x3
3x3 convolution with padding
Face_Verification/Model/models.py:9
↓ 4 callersMethodmaxpool_layer
(self, x, name)
Geo-localization/Model/models.py:72
↓ 2 callersMethodGradCAM
(self, map, size = (256, 128))
Person_Re-identification/demo.py:83
↓ 2 callersMethodOverall_map
Only for Flatten architecture, you may check the code of other applications for the implementation of GAP and GMP.
Face_Verification/demo.py:111
↓ 2 callersMethodOverall_map
Only for GAP architecture, you may check the code of other applications for the implementation of GMP and flattened feature.
Person_Re-identification/demo.py:112
↓ 2 callersMethodOverall_map
Only for GMP architecture, you may check the code of other applications for the implementation of GAP and flattened feature.
Image_Retrieval/demo.py:112
↓ 2 callersMethodOverall_map
Only for GAP architecture, you may check the code of other applications for the implementation of GMP and flattened feature.
Geo-localization/demo.py:100
↓ 2 callersMethodPoint_Specific
Generate the point-specific activation map
Face_Verification/demo.py:174
↓ 2 callersMethodPoint_Specific
Generate the point-specific activation map
Person_Re-identification/demo.py:159
↓ 2 callersMethodPoint_Specific
Generate the point-specific activation map
Image_Retrieval/demo.py:146
↓ 2 callersMethodPoint_Specific
Generate the point-specific activation map
Geo-localization/demo.py:132
↓ 2 callersMethodRGradCAM
(self, map, size = (112, 112))
Face_Verification/demo.py:96
↓ 2 callersMethodRGradCAM
(self, map, size = (224, 224))
Image_Retrieval/demo.py:97
↓ 2 callersMethodbuild
(self, x)
Geo-localization/Model/models.py:79
↓ 2 callersMethodconv2d
(self, x, W)
Geo-localization/Model/models.py:47
↓ 2 callersFunctionfc_layer
(x, input_dim, output_dim, trainable, name='fc_layer', activation_fn=tf.nn.relu,reuse = tf.AU
Geo-localization/Model/models.py:28
↓ 2 callersMethodread
(self, path)
Face_Verification/demo.py:15
↓ 2 callersMethodread
(self, path)
Person_Re-identification/demo.py:15
↓ 2 callersMethodread
(self, path)
Image_Retrieval/demo.py:15
↓ 2 callersMethodread
(self, path, size)
Geo-localization/demo.py:20
↓ 2 callersFunctionresnet152
()
Face_Verification/Model/models.py:209
↓ 1 callersFunctionSiamese_network
(x_sat, x_grd)
Geo-localization/Model/models.py:5
↓ 1 callersMethod__init__
(self, class_num)
Person_Re-identification/Model/model.py:54
↓ 1 callersMethod__init__
(self, in_dim, out_dim, dropout=None, normalized=True)
Image_Retrieval/Model/BN_Inception.py:8
↓ 1 callersFunctiondemo
()
Face_Verification/demo.py:364
↓ 1 callersFunctiondemo
()
Person_Re-identification/demo.py:290
↓ 1 callersFunctiondemo
()
Image_Retrieval/demo.py:329
↓ 1 callersFunctiondemo
()
Geo-localization/demo.py:274
↓ 1 callersMethoddemo
generate activation map with different methods.
Face_Verification/demo.py:199
↓ 1 callersMethoddemo
generate activation map with different methods.
Person_Re-identification/demo.py:184
↓ 1 callersMethoddemo
Generate activation map with different methods. The model is based on global maximum pooling and trained with L2 normalizatio
Image_Retrieval/demo.py:171
↓ 1 callersMethoddemo
generate activation map with different methods.
Geo-localization/demo.py:157
↓ 1 callersMethodfeatures
(self, input)
Image_Retrieval/Model/BN_Inception.py:267
↓ 1 callersMethodget_embed
The code is for situations where two models are different. Since the models of two streams are the same in this case,
Face_Verification/demo.py:43
↓ 1 callersMethodget_embed
The code is for situations where two models are different. Since the models of two streams are the same in this case,
Person_Re-identification/demo.py:44
↓ 1 callersMethodget_embed
The code is for situations where two models are different. Since the models of two streams are the same in this case,
Image_Retrieval/demo.py:45
↓ 1 callersMethodget_input_from_path
load two images from paths
Face_Verification/demo.py:22
↓ 1 callersMethodget_input_from_path
load two images from paths
Person_Re-identification/demo.py:23
↓ 1 callersMethodget_input_from_path
load two images from paths
Image_Retrieval/demo.py:24
↓ 1 callersMethodget_input_from_path
load two images from paths sat denotes satallite (Aerial view) and grd denotes ground (Street view)
Geo-localization/demo.py:28
↓ 1 callersMethodload_model
Load the trained model, you may change the path of model here. Get the cosine similarity and parameters of fc layer
Geo-localization/demo.py:38
↓ 1 callersMethodmax_pool_2x2
(self, x)
Geo-localization/Model/models.py:51
MethodRGradCAM
(self, map, size = (256, 128))
Person_Re-identification/demo.py:97
MethodRGradCAM
(self, sess, cost , target, feed_dict, size)
Geo-localization/demo.py:85
Method__init__
(self)
Face_Verification/demo.py:11
Method__init__
(self, inplanes, planes, stride=1, downsample=None)
Face_Verification/Model/models.py:17
Method__init__
(self, inplanes, planes, stride=1, downsample=None)
Face_Verification/Model/models.py:49
Method__init__
(self, channel, reduction=16)
Face_Verification/Model/models.py:86
Method__init__
(self, inplanes, planes, stride=1, downsample=None, use_se=True)
Face_Verification/Model/models.py:106
Method__init__
(self)
Person_Re-identification/demo.py:11
Method__init__
(self, in_dim, class_num)
Person_Re-identification/Model/model.py:32
Method__init__
(self)
Image_Retrieval/demo.py:11
Method__init__
(self, dim=512)
Image_Retrieval/Model/BN_Inception.py:28
Method__init__
(self, mode='CVUSA')
Geo-localization/demo.py:12
Methodforward
(self, x)
Face_Verification/Model/models.py:27
Methodforward
(self, x)
Face_Verification/Model/models.py:62
Methodforward
(self, x)
Face_Verification/Model/models.py:96
Methodforward
(self, x)
Face_Verification/Model/models.py:120
Methodforward
(self, x, with_feature =False)
Face_Verification/Model/models.py:187
Methodforward
(self, x)
Person_Re-identification/Model/model.py:45
Methodforward
(self, x, with_feature = False)
Person_Re-identification/Model/model.py:73
Methodforward
(self, x)
Image_Retrieval/Model/BN_Inception.py:15
Methodforward
(self, x, with_feature = False)
Image_Retrieval/Model/BN_Inception.py:503
Functionweights_init_classifier
(m)
Person_Re-identification/Model/model.py:22
Functionweights_init_kaiming
(m)
Person_Re-identification/Model/model.py:7