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34 Commits (8b309b0f4e7e7fafea5d601397c1a86378071bd5)

Author SHA1 Message Date
zuchen.wang 8b309b0f4e add contrastive loss 2021-10-13 20:05:07 +08:00
Xingyu Liao 1dce15efad
faster dataloader with pre-fetch and cuda stream (#456) 
Summary: add a background thread to create a generator with pre-fetch, and create a new cuda stream to copy tensor from cpu to gpu in parallel.

Reviewed by: l1aoxingyu
 2021-04-12 15:03:35 +08:00
Xingyu Liao 883fd4aede
add configurable decorator & linear loss decouple (#441) 
Summary: Add configurable decorator which can call `Baseline` with `Baseline(cfg)` or `Baseline(cfg, heads=heads, ...)`
Decouple linear and loss computation for partial-fc support.

Reviewed By: l1aoxingyu
 2021-03-23 12:10:06 +08:00
liaoxingyu 6b4b935ce4 fix augmix warning 
Summary: add array.clone to avoid warning about numpy array not writable
 2021-01-29 11:50:33 +08:00
liaoxingyu 15e1729a27 update fastreid V1.0 2021-01-18 11:36:38 +08:00
liaoxingyu 766f309d03 feat: update pairwise cosface and pairwise circle loss 2020-12-22 15:51:49 +08:00
liaoxingyu a327a70f0d v0.3 update 
Summary:
1. change DPP training in apex way;
2. make warmup scheduler by iter and lr scheduler by epoch;
3. replace random erasing with torchvision implementation;
4. naming modification in config file
 2020-12-07 14:19:20 +08:00
liaoxingyu ea06ead9e3 fix problem when converting to caffe model (#261) 
Summary: caffe cannot support normalization(sub mean and div std) in network, so make the normalization operators inplace which will not trigger when converting to caffe.

close #261
 2020-09-25 11:26:20 +08:00
liaoxingyu d9a63a959f fix bug in mgn #272 
Summary: fix get_norm bug in mgn
 2020-09-17 18:17:53 +08:00
liaoxingyu 4d573b8107 refactor reid head 
Summary: merge BNneckHead, LinearHead and ReductionHead into EmbeddingHead
because they are highly similar and can be prepared for ClsHead
 2020-09-10 10:57:37 +08:00
liaoxingyu d00ce8fc3c refactor model arch 2020-09-01 16:14:45 +08:00
liaoxingyu 16655448c2 onnx/trt support 
Summary: change model pretrain mode and support onnx/TensorRT export
 2020-07-29 17:43:39 +08:00
liaoxingyu 3f35eb449d minor update 2020-07-14 11:58:06 +08:00
liaoxingyu ea8a3cc534 fix typro 2020-07-10 16:26:35 +08:00
liaoxingyu fec7abc461 finish v0.2 ddp training 2020-07-06 16:57:43 +08:00
liaoxingyu 56a1ab4a5d update fast global avgpool 
Summary: update fast pool according to https://arxiv.org/pdf/2003.13630.pdf
 2020-06-12 16:34:03 +08:00
liaoxingyu 25a7f82df7 change style in baseline 2020-06-05 11:23:11 +08:00
liaoxingyu 94d85fe11c fix convert caffe model problem 2020-06-04 16:39:12 +08:00
liaoxingyu 5528d17ace refactor code 
Summary: change code style and refactor code, add avgmax pooling layer in gem_pool
 2020-05-28 13:49:39 +08:00
liaoxingyu 84c733fa85 fix: remove prefetcher, put normalizer in model 
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 9fae467adf feat(engine/defaults): add DefaultPredictor to get image reid features 
Add a new predictor interface, and modify demo code to predict image features.
 2020-05-08 19:24:27 +08:00
liaoxingyu a2dcd7b4ab feat(layers/norm): add ghost batchnorm 
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 
set parameter num_classes in meta_arch to easily modify different heads fc layer
 2020-04-29 21:29:48 +08:00
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 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 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 23bedfce12 update version0.2 code 2020-03-25 10:58:26 +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 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