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License: MIT License
Very accessible code for my MSc thesis. Inexpensive quantization method for ANN search also known as Enhanced Residual VQ.
License: MIT License
Thanks for this great work.
I notice it doesn't compile on OSX (using clang). My system is MacOS Sierra. Matlab version is R2017a.
When I ran compile.m, it gives these errors:
>>compile
Use "XCode Clang++" compiling
Error using mex
clang: error: unsupported option '-fopenmp'
Error compile (line 4)
mex linscan_aqd_knn_mex.cc linscan_aqd.cc -Iinclude CXXFLAGS="\$CXXFLAGS ...
Any ideas about this problem? Thanks,
Hi jltmtz,
Recently I'm very interested in the Stacked Quantizers, and I want to run the code you provided, but I find there is no download linking of features_m_128.mat
and features_m_128_gt.mat
. Would you like to provide the two .mat
files for me?
Thanks for your great work and kind reply.
When I run AQ part of this code, it throws the following error message:
Error: NARGIN and NARGOUT are not supported in parfor or SPMD blocks.
Error in AQ_pipeline (line 64)
CODES = AQ_encoding(X, CODEBOOKS, N, V);
Error in demo (line 44)
[codes, codebooks, distortions, R] = AQ_pipeline( X_train, h(ones(1,m)), nitsAQ, N_train, verbose );
Any ideas about this problem? Thanks~
Dear Julieta,
Thanks for your great work .
Recently I'm very interested in the Stacked Quantizers. When I run PQ,OPQ,SQ part of this code, their recalls are all low(for example the recall is only 0.011 when N=10000, Any ideas about this problem? T
Looking forward to your reply! Thanks~
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