Triplet-deep-hash-pytorch
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Pytorch implementation of "Fast Training of Triplet-based Deep Binary Embedding Networks".
Triplet-deep-hash-pytorch
Pytorch implementation of "Fast Training of Triplet-based Deep Binary Embedding Networks". http://arxiv.org/abs/1603.02844
Feel free to contribute code.
Update 2017.11.13
Refactor this project.
Use code in https://github.com/kentsommer/keras-inceptionV4 to extract feature.
DEMO
Deep hash for "A", "B".
TODO
- [x] Add multiclass support.
- [x] Make code clean.
- [ ] Add more base networks.
- [ ] Add query code for new project.
Usage
Train
- Put training pictures in
train/[category-id]
, test pictures indata/test
. - Run
src/extract_feature/batch_extarct_test.py
andsrc/extract_feature/batch_extract_train.py
to extract feature for future use. - Run
src/hash_net/generate_random_dataset.py
to generate random training data. - Run
src/hash_net/hashNet.py
to train your triplet deep hash network.
~~## Test~~
~~1. Create folder test, and create pos, neg in test with pictures that you want to retrive.~~
~~2. Run testQue.py
to query your picture set.~~