Linking faiss in your Cmake projects

1-Flat.cpp

/**
 * Copyright (c) 2015-present, Facebook, Inc.
 * All rights reserved.
 *
 * This source code is licensed under the BSD+Patents license found in the
 * LICENSE file in the root directory of this source tree.
 */

#include <cstdio>
#include <cstdlib>

#include <faiss/IndexFlat.h>


int main() {
    int d = 64;                            // dimension
    int nb = 100000;                       // database size
    int nq = 10000;                        // nb of queries

    float *xb = new float[d * nb];
    float *xq = new float[d * nq];

    for(int i = 0; i < nb; i++) {
        for(int j = 0; j < d; j++)
            xb[d * i + j] = drand48();
        xb[d * i] += i / 1000.;
    }

    for(int i = 0; i < nq; i++) {
        for(int j = 0; j < d; j++)
            xq[d * i + j] = drand48();
        xq[d * i] += i / 1000.;
    }

    faiss::IndexFlatL2 index(d);           // call constructor
    printf("is_trained = %s\n", index.is_trained ? "true" : "false");
    index.add(nb, xb);                     // add vectors to the index
    printf("ntotal = %ld\n", index.ntotal);

    int k = 4;

    {       // sanity check: search 5 first vectors of xb
        long *I = new long[k * 5];
        float *D = new float[k * 5];

        index.search(5, xb, k, D, I);

        // print results
        printf("I=\n");
        for(int i = 0; i < 5; i++) {
            for(int j = 0; j < k; j++)
                printf("%5ld ", I[i * k + j]);
            printf("\n");
        }

        printf("D=\n");
        for(int i = 0; i < 5; i++) {
            for(int j = 0; j < k; j++)
                printf("%7g ", D[i * k + j]);
            printf("\n");
        }

        delete [] I;
        delete [] D;
    }


    {       // search xq
        long *I = new long[k * nq];
        float *D = new float[k * nq];

        index.search(nq, xq, k, D, I);

        // print results
        printf("I (5 first results)=\n");
        for(int i = 0; i < 5; i++) {
            for(int j = 0; j < k; j++)
                printf("%5ld ", I[i * k + j]);
            printf("\n");
        }

        printf("I (5 last results)=\n");
        for(int i = nq - 5; i < nq; i++) {
            for(int j = 0; j < k; j++)
                printf("%5ld ", I[i * k + j]);
            printf("\n");
        }

        delete [] I;
        delete [] D;
    }



    delete [] xb;
    delete [] xq;

    return 0;
}

CMakeLists.txt

cmake_minimum_required (VERSION 2.8)
project (faiss_demo_app)
#find_package( FAISS REQUIRED ) #no cmake file from faiss team yet. may be future they make one. 

# Faiss-github: 
# This is equivalent to doing: 
# g++ 1-Flat.cpp -L /usr/local/lib/ -lfaiss

add_executable( faissDemo 1-Flat.cpp )

link_directories("/usr/local/lib/")
target_link_libraries( faissDemo faiss )

try_faiss.py

# This script loads the whole image descriptors (computed by `place_recog_analysis_tool`).
# Then try using faiss into it. Use my docker image: mpkuse/kusevisionkit:ros-kinetic-vins-tf-faiss
#
# Author  : Manohar Kuse <[email protected]>
# 29th Apr, 209
#

import numpy as np
from TerminalColors import bcolors
tcol = bcolors()
import faiss
import time

#--------------------------------------------------
if False:
    # load `pinhole_1loop_in_lab` to train an index
    BASE = '/Bulk_Data/_tmp_saved_seq/mynt_pinhole_1loop_in_lab/'
    fname = BASE+'/gray_conv6_K16__centeredinput.npz'
    DESCRIPTOR_STR = 'from '+fname

    print tcol.OKGREEN, 'Load ', fname, tcol.ENDC
    loaded = np.load(fname)
    netvlad_desc = loaded['netvlad_desc'].astype('float32')
    netvlad_at_i = loaded['netvlad_at_i']
    print 'netvlad_desc.shape=', netvlad_desc.shape , '\tnetvlad_at_i.shape', netvlad_at_i.shape


#--------------------------------------------------


BASE = '/Bulk_Data/_tmp/'
BASE = '/Bulk_Data/_tmp_saved_seq/mynt_mall0/'

fname = BASE+'/gray_conv6_K16__centeredinput.npz'
DESCRIPTOR_STR = 'from '+fname

print tcol.OKGREEN, 'Load ', fname, tcol.ENDC
loaded = np.load(fname)
netvlad_desc = loaded['netvlad_desc'].astype('float32')
netvlad_at_i = loaded['netvlad_at_i']
print 'netvlad_desc.shape=', netvlad_desc.shape , '\tnetvlad_at_i.shape', netvlad_at_i.shape

index = faiss.IndexFlatIP( 4096 )
# index.add( netvlad_desc[0:-200] )

for i in range(0, len(netvlad_desc) ):
# for i in range(0, 500 ):
    print tcol.HEADER, '---', i , tcol.ENDC

    if i-150 >= 0:
        start_t = time.time()
        print 'add netvlad_desc[', i-150, ']', '\t done in %4.4fms' %(1000.*(time.time() - start_t))
        index.add( np.expand_dims( netvlad_desc[i-150], 0 ) )

    if i<200:
        print 'i less than 200. not seen enough'
        continue




    start_t = time.time()
    print 'search(', i, ')'
    # D, I = index.search( np.expand_dims(netvlad_desc[i],0), 4 )
    D, I = index.search( netvlad_desc[i-3:i], 4 )
    print 'Elapsed time: %4.4fms' %(1000.* (time.time() - start_t) )
    print 'i=', i, '::::>\n', I
    print D