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cnn-cbir-benchmark's Introduction

Benchmark for Image Retrieval (BKIR)

License

This project tries to build a benchmark for image retrieval, particularly for Instance-level image retrieval.

Running on Scores Dataset

Fisher vector and VLAD are both currently working on the scores dataset. To run them,

  1. install score-retrieval,
  2. run make, follow the instructions, then run make again,
  3. run make yael,
  4. run make hesaff,
  5. run make setup-dataset,
  6. run the commands in the fv or vlad make target manually (make fv/make vlad isn't working right now for some reason).

Note: The training parameters in gmm.py (for FV) and kmeans.py (for VLAD) have been massively reduced for ease of testing. If you want a real training run, increase them.

Methods

method feature mAP (best) status links
fc_retrieval CNN 60.2% finished fc_retrieval
rmac_retrieval CNN to be tested finished rmac_retrieval
crow_retrieval CNN to be tested finished crow_retrieval
fv_retrieval SIFT 67.29% finished fv_retrieval
vlad_retrieval SIFT 63.13% finished vlad_retrieval

the methods on above have the following characteristics:

  • Low dimension
  • Time - tested
  • Used in industry

Contribution

If you are interested in this project, feel free to contribute your code. Only Python and C++ code are accepted.

cnn-cbir-benchmark's People

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