This file is indexed.

/usr/include/opencv2/flann/flann.hpp is in libopencv-flann-dev 2.4.9.1+dfsg-1.5ubuntu1.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
/*M///////////////////////////////////////////////////////////////////////////////////////
//
//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
//  By downloading, copying, installing or using the software you agree to this license.
//  If you do not agree to this license, do not download, install,
//  copy or use the software.
//
//
//                           License Agreement
//                For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
//   * Redistribution's of source code must retain the above copyright notice,
//     this list of conditions and the following disclaimer.
//
//   * Redistribution's in binary form must reproduce the above copyright notice,
//     this list of conditions and the following disclaimer in the documentation
//     and/or other materials provided with the distribution.
//
//   * The name of the copyright holders may not be used to endorse or promote products
//     derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/

#ifndef _OPENCV_FLANN_HPP_
#define _OPENCV_FLANN_HPP_

#ifdef __cplusplus

#include "opencv2/core/types_c.h"
#include "opencv2/core/core.hpp"
#include "opencv2/flann/flann_base.hpp"
#include "opencv2/flann/miniflann.hpp"

namespace cvflann
{
    CV_EXPORTS flann_distance_t flann_distance_type();
    FLANN_DEPRECATED CV_EXPORTS void set_distance_type(flann_distance_t distance_type, int order);
}


namespace cv
{
namespace flann
{

template <typename T> struct CvType {};
template <> struct CvType<unsigned char> { static int type() { return CV_8U; } };
template <> struct CvType<char> { static int type() { return CV_8S; } };
template <> struct CvType<unsigned short> { static int type() { return CV_16U; } };
template <> struct CvType<short> { static int type() { return CV_16S; } };
template <> struct CvType<int> { static int type() { return CV_32S; } };
template <> struct CvType<float> { static int type() { return CV_32F; } };
template <> struct CvType<double> { static int type() { return CV_64F; } };


// bring the flann parameters into this namespace
using ::cvflann::get_param;
using ::cvflann::print_params;

// bring the flann distances into this namespace
using ::cvflann::L2_Simple;
using ::cvflann::L2;
using ::cvflann::L1;
using ::cvflann::MinkowskiDistance;
using ::cvflann::MaxDistance;
using ::cvflann::HammingLUT;
using ::cvflann::Hamming;
using ::cvflann::Hamming2;
using ::cvflann::HistIntersectionDistance;
using ::cvflann::HellingerDistance;
using ::cvflann::ChiSquareDistance;
using ::cvflann::KL_Divergence;



template <typename Distance>
class GenericIndex
{
public:
        typedef typename Distance::ElementType ElementType;
        typedef typename Distance::ResultType DistanceType;

        GenericIndex(const Mat& features, const ::cvflann::IndexParams& params, Distance distance = Distance());

        ~GenericIndex();

        void knnSearch(const vector<ElementType>& query, vector<int>& indices,
                       vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
        void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);

        int radiusSearch(const vector<ElementType>& query, vector<int>& indices,
                         vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
        int radiusSearch(const Mat& query, Mat& indices, Mat& dists,
                         DistanceType radius, const ::cvflann::SearchParams& params);

        void save(std::string filename) { nnIndex->save(filename); }

        int veclen() const { return nnIndex->veclen(); }

        int size() const { return nnIndex->size(); }

        ::cvflann::IndexParams getParameters() { return nnIndex->getParameters(); }

        FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters() { return nnIndex->getIndexParameters(); }

private:
        ::cvflann::Index<Distance>* nnIndex;
};


#define FLANN_DISTANCE_CHECK \
    if ( ::cvflann::flann_distance_type() != cvflann::FLANN_DIST_L2) { \
        printf("[WARNING] You are using cv::flann::Index (or cv::flann::GenericIndex) and have also changed "\
        "the distance using cvflann::set_distance_type. This is no longer working as expected "\
        "(cv::flann::Index always uses L2). You should create the index templated on the distance, "\
        "for example for L1 distance use: GenericIndex< L1<float> > \n"); \
    }


template <typename Distance>
GenericIndex<Distance>::GenericIndex(const Mat& dataset, const ::cvflann::IndexParams& params, Distance distance)
{
    CV_Assert(dataset.type() == CvType<ElementType>::type());
    CV_Assert(dataset.isContinuous());
    ::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);

    nnIndex = new ::cvflann::Index<Distance>(m_dataset, params, distance);

    FLANN_DISTANCE_CHECK

    nnIndex->buildIndex();
}

template <typename Distance>
GenericIndex<Distance>::~GenericIndex()
{
    delete nnIndex;
}

template <typename Distance>
void GenericIndex<Distance>::knnSearch(const vector<ElementType>& query, vector<int>& indices, vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
    ::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
    ::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
    ::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());

    FLANN_DISTANCE_CHECK

    nnIndex->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
}


template <typename Distance>
void GenericIndex<Distance>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
    CV_Assert(queries.type() == CvType<ElementType>::type());
    CV_Assert(queries.isContinuous());
    ::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);

    CV_Assert(indices.type() == CV_32S);
    CV_Assert(indices.isContinuous());
    ::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);

    CV_Assert(dists.type() == CvType<DistanceType>::type());
    CV_Assert(dists.isContinuous());
    ::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);

    FLANN_DISTANCE_CHECK

    nnIndex->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
}

template <typename Distance>
int GenericIndex<Distance>::radiusSearch(const vector<ElementType>& query, vector<int>& indices, vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
    ::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
    ::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
    ::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());

    FLANN_DISTANCE_CHECK

    return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}

template <typename Distance>
int GenericIndex<Distance>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
    CV_Assert(query.type() == CvType<ElementType>::type());
    CV_Assert(query.isContinuous());
    ::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);

    CV_Assert(indices.type() == CV_32S);
    CV_Assert(indices.isContinuous());
    ::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);

    CV_Assert(dists.type() == CvType<DistanceType>::type());
    CV_Assert(dists.isContinuous());
    ::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);

    FLANN_DISTANCE_CHECK

    return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}

/**
 * @deprecated Use GenericIndex class instead
 */
template <typename T>
class
#ifndef _MSC_VER
 FLANN_DEPRECATED
#endif
 Index_ {
public:
        typedef typename L2<T>::ElementType ElementType;
        typedef typename L2<T>::ResultType DistanceType;

    Index_(const Mat& features, const ::cvflann::IndexParams& params);

    ~Index_();

    void knnSearch(const vector<ElementType>& query, vector<int>& indices, vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
    void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);

    int radiusSearch(const vector<ElementType>& query, vector<int>& indices, vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
    int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& params);

    void save(std::string filename)
        {
            if (nnIndex_L1) nnIndex_L1->save(filename);
            if (nnIndex_L2) nnIndex_L2->save(filename);
        }

    int veclen() const
    {
            if (nnIndex_L1) return nnIndex_L1->veclen();
            if (nnIndex_L2) return nnIndex_L2->veclen();
        }

    int size() const
    {
            if (nnIndex_L1) return nnIndex_L1->size();
            if (nnIndex_L2) return nnIndex_L2->size();
        }

        ::cvflann::IndexParams getParameters()
        {
            if (nnIndex_L1) return nnIndex_L1->getParameters();
            if (nnIndex_L2) return nnIndex_L2->getParameters();

        }

        FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters()
        {
            if (nnIndex_L1) return nnIndex_L1->getIndexParameters();
            if (nnIndex_L2) return nnIndex_L2->getIndexParameters();
        }

private:
        // providing backwards compatibility for L2 and L1 distances (most common)
        ::cvflann::Index< L2<ElementType> >* nnIndex_L2;
        ::cvflann::Index< L1<ElementType> >* nnIndex_L1;
};

#ifdef _MSC_VER
template <typename T>
class FLANN_DEPRECATED Index_;
#endif

template <typename T>
Index_<T>::Index_(const Mat& dataset, const ::cvflann::IndexParams& params)
{
    printf("[WARNING] The cv::flann::Index_<T> class is deperecated, use cv::flann::GenericIndex<Distance> instead\n");

    CV_Assert(dataset.type() == CvType<ElementType>::type());
    CV_Assert(dataset.isContinuous());
    ::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);

    if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
        nnIndex_L1 = NULL;
        nnIndex_L2 = new ::cvflann::Index< L2<ElementType> >(m_dataset, params);
    }
    else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
        nnIndex_L1 = new ::cvflann::Index< L1<ElementType> >(m_dataset, params);
        nnIndex_L2 = NULL;
    }
    else {
        printf("[ERROR] cv::flann::Index_<T> only provides backwards compatibility for the L1 and L2 distances. "
        "For other distance types you must use cv::flann::GenericIndex<Distance>\n");
        CV_Assert(0);
    }
    if (nnIndex_L1) nnIndex_L1->buildIndex();
    if (nnIndex_L2) nnIndex_L2->buildIndex();
}

template <typename T>
Index_<T>::~Index_()
{
    if (nnIndex_L1) delete nnIndex_L1;
    if (nnIndex_L2) delete nnIndex_L2;
}

template <typename T>
void Index_<T>::knnSearch(const vector<ElementType>& query, vector<int>& indices, vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
    ::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
    ::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
    ::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());

    if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
    if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
}


template <typename T>
void Index_<T>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
    CV_Assert(queries.type() == CvType<ElementType>::type());
    CV_Assert(queries.isContinuous());
    ::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);

    CV_Assert(indices.type() == CV_32S);
    CV_Assert(indices.isContinuous());
    ::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);

    CV_Assert(dists.type() == CvType<DistanceType>::type());
    CV_Assert(dists.isContinuous());
    ::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);

    if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
    if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
}

template <typename T>
int Index_<T>::radiusSearch(const vector<ElementType>& query, vector<int>& indices, vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
    ::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
    ::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
    ::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());

    if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
    if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}

template <typename T>
int Index_<T>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
    CV_Assert(query.type() == CvType<ElementType>::type());
    CV_Assert(query.isContinuous());
    ::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);

    CV_Assert(indices.type() == CV_32S);
    CV_Assert(indices.isContinuous());
    ::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);

    CV_Assert(dists.type() == CvType<DistanceType>::type());
    CV_Assert(dists.isContinuous());
    ::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);

    if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
    if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}


template <typename Distance>
int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params,
                           Distance d = Distance())
{
    typedef typename Distance::ElementType ElementType;
    typedef typename Distance::ResultType DistanceType;

    CV_Assert(features.type() == CvType<ElementType>::type());
    CV_Assert(features.isContinuous());
    ::cvflann::Matrix<ElementType> m_features((ElementType*)features.ptr<ElementType>(0), features.rows, features.cols);

    CV_Assert(centers.type() == CvType<DistanceType>::type());
    CV_Assert(centers.isContinuous());
    ::cvflann::Matrix<DistanceType> m_centers((DistanceType*)centers.ptr<DistanceType>(0), centers.rows, centers.cols);

    return ::cvflann::hierarchicalClustering<Distance>(m_features, m_centers, params, d);
}


template <typename ELEM_TYPE, typename DIST_TYPE>
FLANN_DEPRECATED int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params)
{
    printf("[WARNING] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> is deprecated, use "
        "cv::flann::hierarchicalClustering<Distance> instead\n");

    if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
        return hierarchicalClustering< L2<ELEM_TYPE> >(features, centers, params);
    }
    else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
        return hierarchicalClustering< L1<ELEM_TYPE> >(features, centers, params);
    }
    else {
        printf("[ERROR] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> only provides backwards "
        "compatibility for the L1 and L2 distances. "
        "For other distance types you must use cv::flann::hierarchicalClustering<Distance>\n");
        CV_Assert(0);
    }
}

} } // namespace cv::flann

#endif // __cplusplus

#endif