MCPcopy Create free account

hub / github.com/SamvitJ/ReXCam / functions

Functions335 in github.com/SamvitJ/ReXCam

⨍ Functions 335◇ Types & classes 116
↓ 35 callersMethodupdate
(self, val, n=1)
utils.py:33
↓ 12 callersMethod__init__
(self, stem_filters, num_filters=42)
models/NASNet.py:166
↓ 11 callersFunctionwrite_json
(obj, fpath)
utils.py:87
↓ 10 callersMethod__init__
(self)
models/InceptionV4.py:62
↓ 10 callersFunctionmkdir_if_missing
(directory)
utils.py:11
↓ 9 callersFunctionread_json
(fpath)
utils.py:82
↓ 8 callersMethod__init__
(self, num_classes, loss={'xent'}, nchannels=[128, 256, 384], feat_dim=512, learn_region=True, use_gpu=True, *
models/HACNN.py:191
↓ 8 callersMethod__init__
Parameters ---------- block (nn.Module): Bottleneck class. - For SENet154: SEBottleneck - For SE-ResN
models/SEResNet.py:210
↓ 8 callersMethodclose
(self)
utils.py:77
↓ 7 callersMethod__init__
(self, scale=1.0, noReLU=False)
models/InceptionResNetV2.py:211
↓ 6 callersMethod__init__
(self)
models/MuDeep.py:120
↓ 6 callersMethod__init__
(self, in_channels, out_channels)
models/Xception.py:32
↓ 6 callersFunctionevaluate
(distmat, q_pids, g_pids, q_camids, g_camids, max_rank=50, use_metric_cuhk03=False, img_names=None, g_
eval_metrics.py:149
↓ 6 callersMethodfeatures
(self, x)
models/SEResNet.py:348
↓ 6 callersFunctioninitialize_pretrained_model
(model, num_classes, settings)
models/SEResNet.py:370
↓ 6 callersFunctionsave_checkpoint
(state, is_best, fpath='checkpoint.pth.tar')
utils.py:39
↓ 5 callersMethod__init__
(self, num_classes, small=False, num_init_features=64, k_r=96, groups=32, b=False, k_sec=(3,
models/DPN.py:320
↓ 5 callersFunctioninit_optim
(optim, params, lr, weight_decay)
optimizers.py:5
↓ 4 callersFunctionDeepSupervision
Args: criterion: loss function xs: tuple of inputs y: ground truth
losses.py:15
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, groups, reduction, stride=1, downsample_kernel_size=1, downs
models/SEResNet.py:328
↓ 3 callersMethod__init__
(self, weight_ring=1.)
losses.py:152
↓ 3 callersMethod__init__
(self, in_c, out_c, k, s=1, p=0)
models/SqueezeNet.py:21
↓ 3 callersMethod_process_data
(self, dirnames, cam1=True, cam2=True)
data_manager.py:1241
↓ 3 callersMethod_process_data
(self, names, meta_data, home_dir=None, relabel=False, min_seq_len=0)
data_manager.py:1369
↓ 3 callersMethod_process_data
(self, dirnames, cam1=True, cam2=True)
data_manager.py:1549
↓ 3 callersMethod_process_data
(self, dirnames, cam1=True, cam2=True)
data_manager.py:1649
↓ 3 callersMethod_process_dir
(self, dir_path, relabel=False)
data_manager.py:79
↓ 3 callersMethod_process_dir
(self, dir_path, relabel=False)
data_manager.py:426
↓ 3 callersMethod_process_dir
(self, dir_path, list_path)
data_manager.py:514
↓ 3 callersMethod_process_dir
(self, dir_path, json_path, relabel)
data_manager.py:1754
↓ 3 callersMethodforward_prepare
(self, input)
models/ResNeXt.py:22
↓ 3 callersMethodstn
Perform spatial transform x: (batch, channel, height, width) theta: (batch, 2, 3)
models/HACNN.py:251
↓ 3 callersMethodtransform_theta
Transform theta to include (s_w, s_h), resulting in (batch, 2, 3)
models/HACNN.py:260
↓ 2 callersMethod__init__
(self, in_channels, out_channels, stride, num_groups)
models/ShuffleNet.py:27
↓ 2 callersMethod__init__
(self, num_classes, loss={'xent'}, **kwargs)
models/ResNet.py:11
↓ 2 callersMethod__init__
(self, in_c, out_c, k, s=1, p=0, g=1)
models/MobileNet.py:23
↓ 2 callersMethod__init__
(self, fn, *args)
models/ResNeXt.py:18
↓ 2 callersMethod_get_names
(self, fpath)
data_manager.py:1361
↓ 2 callersFunctionadaptive_avgmax_pool2d
Selectable global pooling function with dynamic input kernel size
models/DPN.py:444
↓ 2 callersFunctioncheck_exit_retry
(f_rate, camid, s_lower_b, s_upper_b, fallback_times, exit_times, cam_check)
train_img_model_xent.py:266
↓ 2 callersFunctionread_image
Keep reading image until succeed. This can avoid IOError incurred by heavy IO process.
train_img_model_xent.py:244
↓ 2 callersFunctionread_image
Keep reading image until succeed. This can avoid IOError incurred by heavy IO process.
dataset_loader.py:10
↓ 2 callersFunctiontest
(model, queryloader, gallery, use_gpu, ranks=[1, 5, 10, 20])
train_img_model_xent.py:296
↓ 2 callersFunctiontest
(model, queryloader, galleryloader, use_gpu, ranks=[1, 5, 10, 20])
train_img_model_xent_htri.py:258
↓ 2 callersFunctiontest
(model, queryloader, galleryloader, pool, use_gpu, ranks=[1, 5, 10, 20])
train_vid_model_xent_htri.py:245
↓ 2 callersFunctiontest
(model, queryloader, galleryloader, pool, use_gpu, ranks=[1, 5, 10, 20])
train_vid_model_xent.py:229
↓ 2 callersFunctiontest
(model, queryloader, galleryloader, use_gpu, ranks=[1, 5, 10, 20])
train_img_model_ring.py:239
↓ 2 callersFunctiontest
(model, queryloader, galleryloader, use_gpu, ranks=[1, 5, 10, 20])
train_img_model_cent.py:244
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:68
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:191
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:415
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:505
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:621
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:748
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:907
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:1035
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:1190
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:1346
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:1496
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:1644
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
data_manager.py:1743
↓ 1 callersMethod_download_data
(self)
data_manager.py:604
↓ 1 callersMethod_download_data
(self)
data_manager.py:759
↓ 1 callersMethod_download_data
(self)
data_manager.py:1044
↓ 1 callersMethod_download_data
(self)
data_manager.py:1174
↓ 1 callersMethod_download_data
(self)
data_manager.py:1480
↓ 1 callersMethod_extract_file
(self)
data_manager.py:899
↓ 1 callersMethod_make_layer
(self, in_channels, out_channels, num)
models/Xception.py:126
↓ 1 callersMethod_prepare_split
(self)
data_manager.py:630
↓ 1 callersMethod_prepare_split
(self)
data_manager.py:776
↓ 1 callersMethod_prepare_split
Image name format: 0001001.png, where first four digits represent identity and last four digits represent cameras. Camera 1&2 are con
data_manager.py:914
↓ 1 callersMethod_prepare_split
(self)
data_manager.py:1061
↓ 1 callersMethod_prepare_split
(self)
data_manager.py:1199
↓ 1 callersMethod_prepare_split
(self)
data_manager.py:1505
↓ 1 callersMethod_preprocess
This function is a bit complex and ugly, what it does is 1. Extract data from cuhk-03.mat and save as png images. 2. Create 2
data_manager.py:204
↓ 1 callersFunctioneval_cuhk03
Evaluation with cuhk03 metric Key: one image for each gallery identity is randomly sampled for each query identity. Random sampling is perform
eval_metrics.py:7
↓ 1 callersFunctioneval_market1501
Evaluation with market1501 metric Key: for each query identity, its gallery images from the same camera view are discarded.
eval_metrics.py:75
↓ 1 callersMethodfeatures
(self, input)
models/NASNet.py:597
↓ 1 callersMethodfeatures
(self, input)
models/InceptionResNetV2.py:346
↓ 1 callersFunctioninceptionv4
(num_classes=1000, pretrained='imagenet')
models/InceptionV4.py:318
↓ 1 callersMethodinit_params
Load ImageNet pretrained weights
models/DPN.py:387
↓ 1 callersMethodinit_params
Load ImageNet pretrained weights
models/NASNet.py:588
↓ 1 callersMethodinit_params
(self)
models/HACNN.py:154
↓ 1 callersMethodinit_params
Load ImageNet pretrained weights
models/InceptionResNetV2.py:337
↓ 1 callersMethodinit_params
Load ImageNet pretrained weights
models/ResNeXt.py:1418
↓ 1 callersMethodinit_params
Load ImageNet pretrained weights
models/ResNeXt.py:1459
↓ 1 callersMethodinit_scale_factors
(self)
models/HACNN.py:243
↓ 1 callersMethodlogits
(self, x)
models/SEResNet.py:356
↓ 1 callersMethodlogits
(self, features)
models/InceptionV4.py:306
↓ 1 callersFunctionmain
()
train_img_model_xent.py:86
↓ 1 callersFunctionmain
()
train_img_model_xent_htri.py:83
↓ 1 callersFunctionmain
()
train_vid_model_xent_htri.py:77
↓ 1 callersFunctionmain
()
train_vid_model_xent.py:71
↓ 1 callersFunctionmain
()
train_img_model_ring.py:78
↓ 1 callersFunctionmain
()
train_img_model_cent.py:78
↓ 1 callersFunctionpooling_factor
(pool_type='avg')
models/DPN.py:440
↓ 1 callersMethodreset
(self)
utils.py:27
↓ 1 callersFunctionse_resnet101
(num_classes=1000, pretrained='imagenet')
models/SEResNet.py:402
↓ 1 callersFunctionse_resnet50
(num_classes=1000, pretrained='imagenet')
models/SEResNet.py:391
↓ 1 callersFunctionse_resnext101_32x4d
(num_classes=1000, pretrained='imagenet')
models/SEResNet.py:435
next →1–100 of 335, ranked by callers