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27 Commits (907798c8c98b00c84db2a38d6af64ea94ceff830)

Author SHA1 Message Date
liaoxingyu 4d3e5fd378 refactor(evaluation): add feature l2 norm in evaluation 
change the l2 norm function from inference function in Module to reid evaluation.
because sometimes we need to use the original features generated by model rather than normalized ones.
 2020-04-27 14:51:39 +08:00
liaoxingyu 9910bb9158 fix($modeling/heads): fix targets missing bug 
fix bug in heads about return outputs without targets.
 2020-04-27 14:49:58 +08:00
liaoxingyu 2efbc6d371 fix($modeling/heads/bnneck_head): fix heads outputs bug 
fix bug of heads outputs, which will lead to no targets return.
 2020-04-27 11:48:21 +08:00
liaoxingyu 3984f0c91d refactor($modeling/meta): refactor heads output 
without intermediate variables generated by reid heads, make it more flexible
 2020-04-24 12:16:18 +08:00
liaoxingyu e3ae03cc58 feat($modeling/backbones): add new backbones 
add osnet, resnext and resnest backbone supported
 2020-04-24 12:14:56 +08:00
liaoxingyu b098b194ba refactor($modeling/meta_arch): remove bdb_network 2020-04-21 11:44:29 +08:00
liaoxingyu 6c9af664dc refactor($modeling/meta_arch): remove useless parts 
remove useless meta_archs and backbones
 2020-04-21 11:42:14 +08:00
liaoxingyu 95a3c62ad2 refactor(fastreid) 
refactor architecture
 2020-04-20 10:59:29 +08:00
liaoxingyu 9684500a57 chagne arch 
1. change dataset show to trainset show and testset show seperately
2. add cls layer to easily plug in circle loss and arcface
 2020-04-19 12:54:01 +08:00
liaoxingyu be9faa5605 update focal loss 
update dataset info display
update seperate lr
update adaptive label smooth regularization
 2020-04-17 13:46:10 +08:00
liaoxingyu 9cf222e093 refactor bn_no_bias 2020-04-08 21:04:09 +08:00
liaoxingyu 4d2fa28dbb update freeze layer 
update preciseBN
update circle loss with metric learning and cross entropy loss form
update loss call methods
 2020-04-06 23:34:27 +08:00
liaoxingyu 6a8961ce48 1. upload circle loss and arcface 
2. finish freeze training
3. update augmix data augmentation
 2020-04-05 23:54:26 +08:00
liaoxingyu c6e0176c53 Upload demo.py and example 2020-04-03 15:07:27 +08:00
liaoxingyu 91dc9bc71f Merge branch 'master' of github.com:L1aoXingyu/fast-reid 
 Conflicts:
	fastreid/config/defaults.py
	fastreid/layers/gem_pool.py
	fastreid/modeling/backbones/resnet.py
	fastreid/modeling/heads/__init__.py
	fastreid/modeling/heads/build.py
	fastreid/modeling/losses/build.py
	fastreid/modeling/meta_arch/__init__.py
	fastreid/modeling/meta_arch/abd_network.py
	fastreid/modeling/meta_arch/baseline.py
	fastreid/modeling/meta_arch/bdb_network.py
	fastreid/modeling/meta_arch/mf_network.py
	projects/StrongBaseline/configs/Base-Strongbaseline.yml
	projects/StrongBaseline/configs/baseline_dukemtmc.yml
	projects/StrongBaseline/train_net.py
 2020-03-25 11:05:28 +08:00
liaoxingyu 23bedfce12 update version0.2 code 2020-03-25 10:58:26 +08:00
L1aoXingyu b1058118ca update BDB-net code 
update MF-net code
 2020-03-19 12:23:41 +08:00
L1aoXingyu acf363c181 1. Change loss function as a build-in attributes of heads 
2. Update agw and bagtricks result
 2020-03-16 15:23:09 +08:00
L1aoXingyu bab602dfd2 Fix minor bug in build criterion, it will replace by multiple call 
Refactor resnet pretrain
 2020-02-28 21:20:41 +08:00
L1aoXingyu 12957f66aa Change architecture: 
1. delete redundant preprocess
2. add data prefetcher to accelerate data loading
3. fix minor bug of triplet sampler when only one image for one id
 2020-02-18 21:01:23 +08:00
L1aoXingyu e01d9b241f Update AGW baseline result 2020-02-13 20:37:08 +08:00
L1aoXingyu 327d74ffbb Update strong baseline result 
Change data sampler
 2020-02-13 00:19:15 +08:00
L1aoXingyu a2f69d0537 Update StrongBaseline results for market1501 and dukemtmc 2020-02-11 22:38:40 +08:00
L1aoXingyu 8a9c0ccfad Finish first version for fastreid 2020-02-10 22:13:04 +08:00
L1aoXingyu db6ed12b14 Update sampler code 2020-02-10 07:38:56 +08:00
liaoxingyu 71950d2c09 1. Fix evaluation code 
2. Finish multi-dataset evaluation
3. Decouple image preprocess and output postprocess with model forward for DataParallel training
4. Finish build backbone registry
5. Fix dataset sampler
 2020-01-21 20:24:26 +08:00
liaoxingyu b761b656f3 Finish basic training loop and evaluation results 2020-01-20 21:33:37 +08:00