liaoxingyu
ea8a3cc534
fix typro
2020-07-10 16:26:35 +08:00
grimoire
76afdd8d66
fix bugs of rank_cylib
2020-07-07 11:12:46 +08:00
liaoxingyu
fec7abc461
finish v0.2 ddp training
2020-07-06 16:57:43 +08:00
liaoxingyu
5ae2cff47e
fix circle/arcface pred_logits
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fix #136
2020-07-06 16:57:03 +08:00
liaoxingyu
b7a2b1c21a
support DDP sampler and augment
2020-07-06 16:55:23 +08:00
liaoxingyu
c851c7edc8
fix dataset prefix #76
2020-07-06 16:54:54 +08:00
liaoxingyu
4cc157a12f
add lars optimizer
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Summary: support lars optimizer refer to https://arxiv.org/abs/1708.03888 which can make large batch training stable
2020-06-22 12:12:19 +08:00
liaoxingyu
f10ce253f1
refactor arcface and circle loss
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#111
2020-06-22 11:56:39 +08:00
liaoxingyu
3840f3f79a
fix arcface NaN problem
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Summary: fix classifier init bugs, which will not initialize classifier weights when use arcface or circle loss.
In this way, it will lead loss NaN problem.
2020-06-18 12:05:44 +08:00
liaoxingyu
8879db3fba
update training instruction
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Summary: update dataset configuration and training instruction
2020-06-16 19:43:36 +08:00
liaoxingyu
ecc2b1a790
update naive sampler
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Summary: update naive sampler which will introduce unbalanced sampling
2020-06-15 20:50:25 +08:00
liaoxingyu
56a1ab4a5d
update fast global avgpool
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Summary: update fast pool according to https://arxiv.org/pdf/2003.13630.pdf
2020-06-12 16:34:03 +08:00
liaoxingyu
cbdc01a1c3
update pairwise circle loss
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Summary: add param of pairwise circle loss to config, and update pairwise circle loss version
2020-06-10 19:07:29 +08:00
liaoxingyu
96b9ad2d99
fix docs in ToTensor
2020-06-10 19:06:03 +08:00
liaoxingyu
3732f94405
update osnet
2020-06-09 14:38:49 +08:00
liaoxingyu
25a7f82df7
change style in baseline
2020-06-05 11:23:11 +08:00
liaoxingyu
bc221cb05f
fix mgn multi-gpu training problem
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Summary: norm_type in pool_reduce will not change when use syncBN
2020-06-05 11:11:50 +08:00
liaoxingyu
94d85fe11c
fix convert caffe model problem
2020-06-04 16:39:12 +08:00
liaoxingyu
e7156e1cfa
fix mgn not registered problem
2020-06-03 11:46:28 +08:00
liaoxingyu
85672b1e75
add circle & arcface layer info
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Summary: show num_features and num_classes in circle & arcface layer, like nn.Linear
2020-05-31 15:50:56 +08:00
liaoxingyu
e2761f7581
fix style in comm dataset
2020-05-30 16:56:08 +08:00
liaoxingyu
c036ac5bdd
update reduction head
2020-05-30 16:50:02 +08:00
liaoxingyu
36c04f0a9f
fix resume training problem
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Summary: when resume training, need to reiter dataloader because we update pid_dict in dataset, but dataloader with multiprocess won't do the same update
2020-05-30 16:44:18 +08:00
liaoxingyu
5528d17ace
refactor code
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Summary: change code style and refactor code, add avgmax pooling layer in gem_pool
2020-05-28 13:49:39 +08:00
liaoxingyu
cd69ba6ffb
update augmix augments
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Summary: replace augmix augmentations for adapting reid
2020-05-27 22:56:31 +08:00
liaoxingyu
a1cb123cfa
fix R101 bottleneck missing problem
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Summary: add key 101 in block dict to support R101
2020-05-26 14:48:32 +08:00
liaoxingyu
d4b71de3aa
switch between soft and hard margin when inf
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Summary: Add a mechnism to automatic switch triplet loss with soft margin to hard margin when loss becomes inf.
2020-05-26 14:36:33 +08:00
liaoxingyu
5982f90920
support loading various pretrained weights
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Summary: Support loading pretrained model by custom path. With this function, we can load infoMin weights.
2020-05-26 14:33:18 +08:00
liaoxingyu
5d4758125d
support ResNet34 backbone
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Summary: add BasicBlock to support ResNet34
2020-05-26 13:18:09 +08:00
liaoxingyu
84c733fa85
fix: remove prefetcher, put normalizer in model
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1. remove messy data prefetcher which will cause confusion
2. put normliazer in model to accelerate training via GPU computing
2020-05-25 23:39:11 +08:00
liaoxingyu
94c86579a3
fix(heads): fix bug in reduce head
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add neck_feat from config, add inplace in leakyrelu for memory save
2020-05-23 10:41:13 +08:00
liaoxingyu
c21de64166
fix: add linear initial method
2020-05-21 23:59:51 +08:00
liaoxingyu
e990cf3e34
style: fix some typro
2020-05-21 15:55:51 +08:00
liaoxingyu
2ac55a7601
feat: update roc curve and TPR@FPR metric
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support plot multiple ROC curves with different model
2020-05-20 14:29:33 +08:00
liaoxingyu
e344eae1cc
feat: support plotting roc curve and compute auc score
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ROC curve and AUC score will be help for thresholds
2020-05-19 20:45:26 +08:00
liaoxingyu
fd90555e19
feat: add multi-dataset joint training
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new feature that can support joint training, and find some bugs in funtion combine_all of datasets/bases.py that assume person id in dataset has been relabeld from 0 to num_class.
Another bug appears in msmt17 which trainset and testset person id both begin from 0, and we should change testset id from num_class of trainset.
2020-05-18 20:06:04 +08:00
liaoxingyu
579a5cf552
fix: modify re-rank typro
2020-05-18 17:05:20 +08:00
liaoxingyu
d63bf5facc
fix: add syncBN options in defaultTraine
2020-05-16 22:44:53 +08:00
liaoxingyu
b28c0032e8
fix: add monkey-patching to enable syncBN
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add a trigger to make syncBN work
2020-05-15 13:33:33 +08:00
liaoxingyu
18a33f7962
feat: add MGN model
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support MGN architecture and training config
2020-05-15 11:39:54 +08:00
liaoxingyu
bf18479541
fix: revise syncBN bug
2020-05-14 14:52:37 +08:00
liaoxingyu
0872a32621
feat: add syncBN support
2020-05-14 13:15:09 +08:00
liaoxingyu
0356ef8c5c
feat: add SyncBN and GroupNorm suppor
2020-05-14 11:36:28 +08:00
liaoxingyu
5ae3d4fecf
feat: add aqe support in test phase
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query expansion will combine the retrived topk nearest neighbors with the original query feature,
it will enhance mAP by a large margin.feat:
2020-05-13 16:27:22 +08:00
liaoxingyu
320010f2ae
feat: support re-rank in test phase
2020-05-13 11:47:52 +08:00
Xingyu Liao
01d940bfdd
update vehicle dataset
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Summary: Pull Request resolved : #49
Reviewed By: xingyu liao
2020-05-12 21:44:05 +08:00
liaoxingyu
9addfb0ae2
feat: support visualizing label list
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add features to support label list visualization, which can be used
for label correction or check the hardest sample
2020-05-12 21:35:33 +08:00
Jinkai Zheng
640c9bfc97
Add small, medium and large vehicle test datasets
2020-05-11 01:34:19 -05:00
Jinkai Zheng
e059b751a6
Add modified vehicle datasets with small, medium and large test datastes
2020-05-11 01:30:56 -05:00
liaoxingyu
9b6fda3830
style: remove title in visualization
2020-05-11 14:12:29 +08:00
liaoxingyu
13bb03eb07
feat: add rank result visualization tools
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Update visualization tools which can save rank list with AP metrics from high to low, vice versa.
In order to compute AP fast in visualizer, modify rank_cylib to get all_AP instead of mAP.
In this way, we can use Cython to compute results.
2020-05-10 23:17:10 +08:00
liaoxingyu
651e6ba9c4
feat: support multiprocess predictor
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add asyncpredictor to support multiprocessing feature extraction with dataloader
2020-05-09 18:23:36 +08:00
liaoxingyu
4be4cacb73
fix: add a simple way to reset data prefetcher when resume training
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use data prefetcher build-in reset function to reload it rather than
redefining a new data prefetcher, otherwise it will introduce other
problems in eval-only mode.
2020-05-09 11:58:27 +08:00
liaoxingyu
9fae467adf
feat(engine/defaults): add DefaultPredictor to get image reid features
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Add a new predictor interface, and modify demo code to predict image features.
2020-05-08 19:24:27 +08:00
liaoxingyu
8ab0bc2455
style(backbone): make parameters loading logging more elegant
2020-05-08 12:22:06 +08:00
liaoxingyu
0b15ac4e03
feat(hooks&optim): update stochastic weight averging hooks
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Update swa method which will do after regular training if you
set this option enabled.
2020-05-08 12:20:04 +08:00
liaoxingyu
afac8aad5d
Fix(engine): fix preciseBN dataloader bugs
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preciseBN needs to pass data prefetcher, but now a DataLoader is passed
2020-05-06 14:26:34 +08:00
liaoxingyu
948af64fd1
feat: add swa algorithm
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Add swa and related config options,
if it is enabled, model will do swa after regular training
2020-05-06 10:17:44 +08:00
liaoxingyu
6d96529d4c
fix(data): fix resume training bug
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fix dataset pid dictionary loading bug when resume training,
data prefetcher will pre-load a batch of data, this will lead to
misalignment of old pid dict and updated pid dict.
We can address this problem by redefine a prefetcher in resume_or_load
2020-05-05 23:20:42 +08:00
liaoxingyu
a2dcd7b4ab
feat(layers/norm): add ghost batchnorm
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add a get_norm fucntion to easily change normalization between batchnorm, ghost bn and group bn
2020-05-01 09:02:46 +08:00
liaoxingyu
329764bb60
refactor(heads): move num_classes out from heads
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set parameter num_classes in meta_arch to easily modify different heads fc layer
2020-04-29 21:29:48 +08:00
liaoxingyu
d27729c5bb
refactor(preciseBN): add preciseBN datasets show
2020-04-29 21:05:53 +08:00
liaoxingyu
ec19bcc1d3
style(configs): put all config files together
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put all config files into one place for easily control,
and add tools for put train_net.py which almost the same in
different projects
2020-04-29 16:18:54 +08:00
liaoxingyu
e38a799b63
fix(engine/defaults): fix precise bn bug
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fix problem in precise bn, which will not use precise bn datasets, and throw some errors
2020-04-29 16:16:54 +08:00
zjk15068083791
2f3f6e3267
Add files via upload
2020-04-27 16:27:44 +08:00
liaoxingyu
5daf322ac6
fix(data/samplers): fix bug in triplet sampler
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use drop indices to avoid two groups of same id,
but did not consider drop indices = 0, then will lead to
indentites[:0], this is a no teminal loop
2020-04-27 15:25:29 +08:00
liaoxingyu
325d9abb76
feat($solver): change scheduler call methods
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using name of lr scheduler in config to call
2020-04-27 15:12:01 +08:00
liaoxingyu
9e3f2c1e7a
fix($data/transforms): change augmix augmentation pool
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change augmentation_all from augmentation_reid in augmix
because we found AutoAugmentation using ImageNet Policy will not harm performance
2020-04-27 15:06:27 +08:00
liaoxingyu
4d3e5fd378
refactor(evaluation): add feature l2 norm in evaluation
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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($modeling/heads): fix targets missing bug
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fix bug in heads about return outputs without targets.
2020-04-27 14:49:58 +08:00
liaoxingyu
2efbc6d371
fix($modeling/heads/bnneck_head): fix heads outputs bug
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fix bug of heads outputs, which will lead to no targets return.
2020-04-27 11:48:21 +08:00
liaoxingyu
a6bd0371e2
feat($data): add autoaugment
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add auto augmentation support with ImageNet policy and CIFAR10 policy.
modify codes in transforms and config for adapting to this augmentation.
2020-04-27 11:41:12 +08:00
liaoxingyu
8abd3bab03
feat($layers): add new act func
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add mish, gelu supported
2020-04-24 12:17:00 +08:00
liaoxingyu
3984f0c91d
refactor($modeling/meta): refactor heads output
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without intermediate variables generated by reid heads, make it more flexible
2020-04-24 12:16:18 +08:00
liaoxingyu
e3ae03cc58
feat($modeling/backbones): add new backbones
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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
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remove useless meta_archs and backbones
2020-04-21 11:42:14 +08:00
liaoxingyu
bb50b6c5a7
docs($projects): update agw readme
2020-04-21 11:35:54 +08:00
liaoxingyu
95a3c62ad2
refactor(fastreid)
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refactor architecture
2020-04-20 10:59:29 +08:00
liaoxingyu
9684500a57
chagne arch
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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
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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
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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
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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
eacee874aa
fix merge
2020-03-25 11:06:39 +08:00
liaoxingyu
91dc9bc71f
Merge branch 'master' of github.com:L1aoXingyu/fast-reid
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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
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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
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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
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Refactor resnet pretrain
2020-02-28 21:20:41 +08:00
L1aoXingyu
b020c7f0ae
Fix data prefetcher minor bug
2020-02-27 12:16:57 +08:00
L1aoXingyu
12957f66aa
Change architecture:
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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
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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
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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