liaoxingyu
d9a63a959f
fix bug in mgn #272
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Summary: fix get_norm bug in mgn
2020-09-17 18:17:53 +08:00
liaoxingyu
4d573b8107
refactor reid head
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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
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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
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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
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
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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
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
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
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
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
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
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
23bedfce12
update version0.2 code
2020-03-25 10:58:26 +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
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
