This file is indexed.

/usr/include/gamera/plugins/segmentation.hpp is in python-gamera-dev 3.3.3-2+deb7u1.

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
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
/*
 *
 * Copyright (C) 2001-2005 Ichiro Fujinaga, Michael Droettboom,
 * and Karl MacMillan
 *
 * This program is free software; you can redistribute it and/or
 * modify it under the terms of the GNU General Public License
 * as published by the Free Software Foundation; either version 2
 * of the License, or (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 * 
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
 */


#ifndef kwm05212002_segmentation
#define kwm05212002_segmentation

#include <vector>
#include <algorithm>
#include <functional>
#include <map>
#include <stdexcept>
#include "gamera.hpp"
#include "gamera_limits.hpp"
#include "features.hpp"
#include "image_utilities.hpp"
#include "projections.hpp"

/*
  Connected-component analysis (8-connected)

  This is the standard two-pass connected-component analysis algorithm that
  will work on any matrix regardless of the storage format but only for
  OneBit or floating-point pixels.  The labeling works by setting the value
  in the matrix to the correct label (that is why OneBit matrices use
  unsigned shorts instead of some bit-packed format).  This means that the
  number of components is limited by the size of the pixel type (65536 for
  unsigned shorts).

  Authors
  -------
  Karl MacMillan <karlmac@peabody.jhu.edu>
  adapted from OMR by Ichiro Fujinaga <ich@peabody.jhu.edu>

  History
  -------
  Started 6/8/01 KWM

  TODO
  ----
  - This algorithm can be significantly faster when working on run-length data
  so an appropriate specialization should be made when run-length matrices
  are completed.
*/

namespace {
  /*
    This is a two-step connected-component labeling algorithm - the first step
    labels the pixel and the second pass reduces the number of labels to one
    per connected-component. The data necessary to form this second pass is
    stored in the equivalence and equiv_table objects.
  */
  struct equivalence {
    equivalence(size_t l = 0, size_t e = 0) { label = l; equiv = e; }
    size_t label;
    size_t equiv;
    // for sorting by label
    bool operator<(const equivalence& other) const {
      return label < other.label; }
    bool operator==(const equivalence& other) const {
      return label == other.label &&  equiv == other.equiv; }
  };
  
  struct equiv_table : public std::vector<equivalence> {
    equiv_table() : std::vector<equivalence>() { }
    // add an equivalence
    void add(size_t a, size_t b) {
      if (size() == 0 || (back().label != a || back().equiv != b)) {
        if (a < b)
          push_back(equivalence(a, b));
        else
          push_back(equivalence(b, a));
      }
    }
  };
}

namespace Gamera {

  template<class T>
  ImageList* cc_analysis(T& image) {
    equiv_table eq;
    // get the max value that can be held in the matrix
    typename T::value_type max_value = 
      std::numeric_limits<typename T::value_type>::max();
    // The first label we use is 2 to distinguish it from an unlabled black pixel
    typename T::value_type curr_label = 2;

    typename T::value_type W, NW, N, NE;
    ImageAccessor<typename T::value_type> acc;
    typename T::Iterator row, col, lr, ul, above;
    lr = image.lowerRight();
    ul = image.upperLeft();
    // progress_bar.set_length(image.nrows() / 40);
    size_t i0 = 0;
    for (row = image.upperLeft(); row.y != lr.y; ++row.y, ++i0) {
      for (col = row; col.x != lr.x; ++col.x) {
        /*
          If this image has been labeled once already, it is necessary to start
          with all the pixels labeled with 1.
        */
        if (acc(col) > 0)
          acc.set(1, col);
        if (acc(col) > 0) {
          W = NW = N = NE = 0;
          if (col.y != ul.y) {
            above = col;
            --above.y;
            N = acc(above);
            if (col.x != ul.x) {
              --above.x;
              NW = acc(above);
              ++above.x;
            }
            ++above.x;
            if (above.x != lr.x)
              NE = acc(above);
          }
          if (col.x != ul.x)
            W = acc(col - Diff2D(1, 0));
        
          if (W  == 0) W  = max_value;
          if (NW == 0) NW = max_value;
          if (N  == 0) N  = max_value;
          if (NE == 0) NE = max_value;
          typename T::value_type smallest_label = max_value;
        
          if (smallest_label > W ) smallest_label = W;
          if (smallest_label > NW) smallest_label = NW;
          if (smallest_label > N ) smallest_label = N;
          if (smallest_label > NE) smallest_label = NE;
        
          if (smallest_label == max_value) { // new object found!
            acc.set(curr_label, col);
            if (curr_label == max_value) {
              throw std::range_error("Max label exceeded - change OneBitPixel type in pixel.hpp");
            }
            curr_label++;
          } else {
            acc.set(smallest_label, col);
          
            // adjust equiv_table if necessary
            if (W  == max_value) W  = 0;
            if (NW == max_value) NW = 0;
            if (N  == max_value) N  = 0;
            if (NE == max_value) NE = 0;
          
            if (W && W != smallest_label)
              eq.add(smallest_label, W);
            if (NW && NW != smallest_label)
              eq.add(smallest_label, NW);
            if (N && N != smallest_label)
              eq.add(smallest_label, N);
            if (NE && NE != smallest_label)
              eq.add(smallest_label, NE);
          }
        }
      }
      // if ((i0 % 20) == 0)
      // progress_bar.step();
    }
  
    /*
      labels size can be curr_label because curr_label is always the next
      label - i.e. it is currently unused
    */

    std::vector<size_t> labels(curr_label);
    for (size_t i = 0; i < labels.size(); i++)
      labels[i] = i;
  
    // sort by label
    std::sort(eq.begin(), eq.end());
  
    // resolve the equivalences

    for (size_t i = 1; i < eq.size(); i++) {
      size_t x = eq[i].label;
      size_t y = eq[i].equiv;
    
      if (labels[y] > labels[x]) {
        if (labels[y] != y)
          labels[labels[y]] = labels[x];
        labels[y] = labels[x];
      } else if (labels[y] < labels[x]) {
        if (labels[labels[y]] < labels[x])
          labels[x] = labels[labels[y]];
        else
          labels[x] = labels[y];
      }
    }
    bool swapped = true;
    while (swapped) {
      swapped = false;
      for (size_t i = 0; i < eq.size(); i++) {
        size_t x = eq[i].label;
        size_t y = eq[i].equiv;
      
        if (labels[x] != labels[y]) {
          swapped = true;
          if (labels[x] < labels[y])
            labels[y] = labels[x];
          else
            labels[x] = labels[y];
        }
      }
    }
  
    for (size_t i = 0; i < labels.size(); i++)
      if(labels[labels[i]] < labels[i])
        labels[i] = labels[labels[i]];
  
    /*
      Second Pass - relabel with equivalences and get bounding boxes
      This used to use a map, but I think that it is worth the memory
      use to use a vector for mapping the labels to the rects. The 
      vector is a lot faster.
    */
    ImageList* ccs = NULL;

    typedef std::vector<Rect*> map_type;
    map_type rects(labels.size(), 0);
    try {
      row = image.upperLeft();
      for (size_t i = 0; i < image.nrows(); i++, ++row.y) {
        size_t j;
        for (j = 0, col = row; j < image.ncols(); j++, ++col.x) {
          // relabel
          acc.set(labels[acc(col)], col); 
          // put bounding box in map
          typename T::value_type label = acc(col);
          if (label) {
            if (rects[label] == 0) {
              rects[label] = new Rect(Point(j, i), Dim(1, 1));
            } else {
              if (j < rects[label]->ul_x())
                rects[label]->ul_x(j);
              if (j > rects[label]->lr_x())
                rects[label]->lr_x(j);
              if (i < rects[label]->ul_y())
                rects[label]->ul_y(i);
              if (i > rects[label]->lr_y())
                rects[label]->lr_y(i);
            }
          }
        }
        // if ((i % 20) == 0)
        // progress_bar.step();
      }

      // create ConnectedComponents
      ccs = new ImageList();
      try {
        for (size_t i = 0; i < rects.size(); ++i) {
          if (rects[i] != 0) {
            ccs->push_back(new ConnectedComponent<typename T::data_type>(*((typename T::data_type*)image.data()),
                                                                         OneBitPixel(i),
                                                                         Point(rects[i]->offset_x() + image.offset_x(),
                                                                               rects[i]->offset_y() + image.offset_y()),
                                                                         rects[i]->dim()));
            delete rects[i];
          }
        }
      } catch (std::exception e) {
        for (ImageList::iterator i = ccs->begin(); i != ccs->end(); ++i)
          delete *i;
        delete ccs;
        throw;
      }
    } catch (std::exception e) {
      for (size_t i = 0; i != rects.size(); ++i)
        delete rects[i];
    }
    return ccs;
  }

  template<class T>
  inline void delete_connected_components(T* ccs) {
    for (typename T::iterator i = ccs->begin(); i != ccs->end(); ++i)
      delete *i;
    delete ccs;
  }

  namespace ccs {
    /*
      Connected-component filters for use with C++ - there are equivalent
      Python versions for use within the Python Gamera environment. Unlike
      the Python versions these are in-place.
    */

    template<class T>
    void filter_wide(T& ccs, size_t max_width) {
      typename T::iterator i;
      for (i = ccs.begin(); i != ccs.end();) {
        if ((*i)->ncols() > max_width) {
          std::fill((*i)->vec_begin(), (*i)->vec_end(), 0);
          delete *i;
          ccs.erase(i++);
        } else {
          ++i;
        }
      }
    }
  
    template<class T>
    void filter_narrow(T& ccs, size_t min_width) {
      typename T::iterator i;
      for (i = ccs.begin(); i != ccs.end();) {
        if ((*i)->ncols() < min_width) {
          std::fill((*i)->vec_begin(), (*i)->vec_end(), 0);
          delete *i;
          ccs.erase(i++);
        } else {
          ++i;
        }
      } 
    }

    template<class T>
    void filter_tall(T& ccs, size_t max_height) {
      typename T::iterator i;
      for (i = ccs.begin(); i != ccs.end();) {
        if ((*i)->nrows() > max_height) {
          std::fill((*i)->vec_begin(), (*i)->vec_end(), 0);
          delete *i;
          ccs.erase(i++);
        } else {
          ++i;
        }
      } 
    }
  
    template<class T>
    void filter_short(T& ccs, size_t min_height) {
      typename T::iterator i;
      for (i = ccs.begin(); i != ccs.end();) {
        if ((*i)->nrows() < min_height) {
          std::fill((*i)->vec_begin(), (*i)->vec_end(), 0);
          delete *i;
          ccs.erase(i++);
        } else {
          ++i;
        }
      } 
    }
  
    template<class T>
    void filter_large(T& ccs, size_t max_size) {
      typename T::iterator i;
      for (i = ccs.begin(); i != ccs.end();) {
        if ((*i)->nrows() > max_size && (*i)->ncols() > max_size) {
          std::fill((*i)->vec_begin(), (*i)->vec_end(), 0);
          delete *i;
          ccs.erase(i++);
        } else {
          ++i;
        }
      } 
    }

    template<class T>
    void filter_small(T& ccs, size_t min_size) {
      typename T::iterator i;
      for (i = ccs.begin(); i != ccs.end();) {
        if ((*i)->nrows() < min_size && (*i)->ncols() < min_size) {
          std::fill((*i)->vec_begin(), (*i)->vec_end(), 0);
          delete *i;
          ccs.erase(i++);
        } else {
          ++i;
        }
      } 
    }

    template<class T>
    void filter_black_area_large(T& ccs, int max_area) {
      typename T::iterator i;
      for (i = ccs.begin(); i != ccs.end();) {
        int bai = (int)black_area(**i);
        if (bai > max_area) {
          std::fill((*i)->vec_begin(), (*i)->vec_end(), 0);
          delete *i;
          ccs.erase(i++);
        } else {
          ++i;
        }
      } 
    }

    template<class T>
    void filter_black_area_small(T& ccs, int min_area) {
      typename T::iterator i;
      for (i = ccs.begin(); i != ccs.end();) {
        int bai = (int)black_area(**i);
        if (bai < min_area) {
          std::fill((*i)->vec_begin(), (*i)->vec_end(), 0);
          delete *i;
          ccs.erase(i++);
        } else {
          ++i;
        }
      } 
    }
  }

  size_t find_split_point(IntVector *projections, double& center) {
    double minimum = std::numeric_limits<size_t>::max();
    double middle = double(projections->size()) * center;
    size_t minimum_index = 0;
    size_t start = size_t(middle / 2);
    size_t end = size_t(((projections->size() - middle) / 2) + middle);
    for (size_t i=start; i != end; ++i) {
      double distance_from_middle = abs(middle - i);
      int value = (*projections)[i];
      double score = value*value*2 + distance_from_middle*distance_from_middle;
      if (score < minimum) {
        minimum = score;
        minimum_index = i;
      }
    }
    if (minimum_index == 0)
      minimum_index = 1;
    else if (minimum_index == projections->size() - 1)
      minimum_index = projections->size() - 2; 
    return minimum_index;
  }

  size_t find_split_point_max(IntVector *projections, double& center) {
    double minimum = std::numeric_limits<size_t>::max();
    double middle = double(projections->size()) * center;
    size_t minimum_index = 0;
    size_t start = size_t(middle / 2);
    size_t end = size_t(((projections->size() - middle) / 2) + middle);
    for (size_t i=start; i != end; ++i) {
      double distance_from_middle = abs(middle - i);
      int value = (*projections)[i];
      double score = -(value*value*2) + distance_from_middle*distance_from_middle*distance_from_middle;
      if (score < minimum) {
        minimum = score;
        minimum_index = i;
      }
    }
    if (minimum_index == 0)
      minimum_index = 1;
    else if (minimum_index == projections->size() - 1)
      minimum_index = projections->size() - 2; 
    return minimum_index;
  }

  template<class T>
  void split_error_cleanup(T* view,
                           ImageList* splits,
                           IntVector *projs,
                           ImageList* ccs) {
    delete view->data();
    delete view;
    for (ImageList::iterator i = splits->begin(); i != splits->end(); ++i) 
      delete (*i);
    delete splits;
    if (projs != NULL)
      delete projs;
    if (ccs != NULL) {
      for (ImageList::iterator i = ccs->begin(); i != ccs->end(); ++i) 
        delete (*i);
      delete ccs;
    }
  }

  template<class T>
  ImageList* splitx(T& image, FloatVector* center) {
    ImageList* splits = new ImageList();
    typename ImageFactory<T>::view_type* view = 0;
    ImageList* ccs = NULL;
    ImageList::iterator ccs_it;
    size_t last_split, new_split;

    if (image.ncols() <= 1) {
      view = simple_image_copy(T(image, image.origin(), image.dim()));
      splits->push_back(view);
      return splits;
    }
    sort(center->begin(), center->end());
    IntVector *projs = projection_cols(image);
    last_split = 0;
    for (size_t i = 0; i<center->size(); i++) {
      new_split = find_split_point(projs, (*center)[i]);
      if (new_split <= last_split)
        continue;
      view = simple_image_copy(T(image, 
                                 Point(image.ul_x() + last_split, image.ul_y()), 
                                 Dim(new_split - last_split, image.nrows())));
      last_split = new_split;
      try {
        ccs = cc_analysis(*view);
      } catch (std::range_error x) {
        split_error_cleanup(view, splits, projs, ccs);
        throw x;
      }
      for (ccs_it = ccs->begin(); ccs_it != ccs->end(); ++ccs_it)
        splits->push_back(*ccs_it);
      delete view;
      delete ccs;
    }
    delete projs;
    view = simple_image_copy(T(image, 
                               Point(image.ul_x() + last_split, image.ul_y()),
                               Dim(image.ncols() - last_split, image.nrows())));
    try {
      ccs = cc_analysis(*view);
    } catch (std::range_error x) {
      split_error_cleanup(view, splits, NULL, ccs);
      throw x;
    }
    for (ccs_it = ccs->begin(); ccs_it != ccs->end(); ++ccs_it)
      splits->push_back(*ccs_it);
    delete view;
    delete ccs;
    return splits;
  }

  template<class T>
  ImageList* splitx_max(T& image, FloatVector* center) {
    ImageList* splits = new ImageList();
    typename ImageFactory<T>::view_type* view = 0;
    ImageList* ccs = NULL;
    ImageList::iterator ccs_it;
    size_t last_split, new_split;

    if (image.ncols() <= 1) {
      view = simple_image_copy(T(image, image.origin(), image.dim()));
      splits->push_back(view);
      return splits;
    }
    sort(center->begin(), center->end());
    IntVector *projs = projection_cols(image);
    last_split = 0;
    for (size_t i = 0; i<center->size(); i++) {
      new_split = find_split_point_max(projs, (*center)[i]);
      if (new_split <= last_split)
        continue;
      view = simple_image_copy(T(image, 
                                 Point(image.ul_x()+last_split, image.ul_y()),
                                 Dim(new_split - last_split, image.nrows())));
      last_split = new_split;
      try {
        ccs = cc_analysis(*view);
      } catch (std::range_error x) {
        split_error_cleanup(view, splits, projs, ccs);
        throw x;
      }
      for (ccs_it = ccs->begin(); ccs_it != ccs->end(); ++ccs_it)
        splits->push_back(*ccs_it);
      delete view;
      delete ccs;
    }
    delete projs;
    view = simple_image_copy(T(image, 
                               Point(image.ul_x() + last_split, image.ul_y()),
                               Dim(image.ncols() - last_split, image.nrows())));
    try { 
      ccs = cc_analysis(*view);
    } catch (std::range_error x) {
      split_error_cleanup(view, splits, NULL, ccs);
      throw x;
    }
    for (ccs_it = ccs->begin(); ccs_it != ccs->end(); ++ccs_it)
      splits->push_back(*ccs_it);
    delete view;
    delete ccs;
    return splits;
  }

  template<class T>
  ImageList* splity(T& image, FloatVector* center) {
    ImageList* splits = new ImageList();
    typename ImageFactory<T>::view_type* view = 0;
    ImageList* ccs = NULL;
    ImageList::iterator ccs_it;
    size_t last_split, new_split;

    if (image.nrows() <= 1) {
      view = simple_image_copy(T(image, image.origin(), image.dim()));
      splits->push_back(view);
      return splits;
    }
    sort(center->begin(), center->end());
    IntVector *projs = projection_rows(image);
    last_split = 0;
    for (size_t i = 0; i<center->size(); i++) {
      new_split = find_split_point(projs, (*center)[i]);
      if (new_split <= last_split)
        continue;
      view = simple_image_copy(T(image, 
                                 Point(image.ul_x(), image.ul_y()+last_split), 
                                 Dim(image.ncols(), new_split - last_split)));
      last_split = new_split;
      try {
        ccs = cc_analysis(*view);
      } catch (std::range_error x) {
        split_error_cleanup(view, splits, projs, ccs);
        throw x;
      }
      for (ccs_it = ccs->begin(); ccs_it != ccs->end(); ++ccs_it)
        splits->push_back(*ccs_it);
      delete view;
      delete ccs;
    }
    delete projs;
    view = simple_image_copy(T(image, 
                               Point(image.ul_x(), image.ul_y() + last_split),
                               Dim(image.ncols(), image.nrows() - last_split)));
    try {
      ccs = cc_analysis(*view);
    } catch (std::range_error x) {
      split_error_cleanup(view, splits, NULL, ccs);
      throw x;
    }
    for (ccs_it = ccs->begin(); ccs_it != ccs->end(); ++ccs_it)
      splits->push_back(*ccs_it);
    delete view;
    delete ccs;
    return splits;
  }
}

#endif