This file is indexed.

/usr/include/mia-2.2/mia/2d/interpolator.cxx is in libmia-2.2-dev 2.2.2-1+b1.

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
/* -*- mia-c++  -*-
 *
 * This file is part of MIA - a toolbox for medical image analysis 
 * Copyright (c) Leipzig, Madrid 1999-2014 Gert Wollny
 *
 * MIA 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 3 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 MIA; if not, see <http://www.gnu.org/licenses/>.
 *
 */

/*
  The filter routines for splines and omoms is based on code by 
  Philippe Thevenaz http://bigwww.epfl.ch/thevenaz/interpolation/
*/

#include <cmath>

#if defined(__SSE2__)
#include <emmintrin.h>
#endif

NS_MIA_BEGIN

template <typename T>
struct __dispatch_min_max<T2DVector<T> > {
	static void apply(const T2DVector<T>& i, T2DVector<T>& min, T2DVector<T>& max) {
		if (i.x > max.x) max.x = i.x; 
		if (i.y > max.y) max.y = i.y; 
		if (i.x < min.x) min.x = i.x; 
		if (i.y < min.y) min.y = i.y; 
	}
}; 


struct FConvertVector {
	C2DDVector operator () (const C2DFVector& x) const {
		return C2DDVector(x); 
	}
}; 

template <> 
struct __dispatch_copy<std::vector<C2DFVector>, std::vector<C2DDVector> > {
	static void apply(const std::vector<C2DFVector>& input, std::vector<C2DDVector>& output){
		std::transform(input.begin(), input.end(), output.begin(), FConvertVector());
	}
}; 

template <> 
struct __dispatch_copy<C2DFVectorfield, C2DDVectorfield > {
	static void apply(const C2DFVectorfield& input, C2DDVectorfield& output){
		std::transform(input.begin(), input.end(), output.begin(), FConvertVector());
	}
}; 


template <typename T>
T2DConvoluteInterpolator<T>::T2DConvoluteInterpolator(const T2DDatafield<T>& image, PSplineKernel  kernel):
	m_coeff(image.get_size()), 
	m_kernel(kernel),
	m_x_boundary(produce_spline_boundary_condition("mirror")), 
	m_y_boundary(produce_spline_boundary_condition("mirror")), 
	m_x_index(kernel->size()),
	m_y_index(kernel->size()),
	m_x_weight(kernel->size()),
	m_y_weight(kernel->size()), 
	m_x_cache(kernel->size(), *m_x_boundary, false), 
	m_y_cache(kernel->size(), *m_y_boundary, true)
{
	m_x_boundary->set_width(image.get_size().x); 
	m_y_boundary->set_width(image.get_size().y); 
	prefilter(image); 
}
template <typename T>
T2DConvoluteInterpolator<T>::T2DConvoluteInterpolator(const T2DDatafield<T>& image, PSplineKernel kernel, 
						      const CSplineBoundaryCondition& xbc, const CSplineBoundaryCondition& ybc):
	m_coeff(image.get_size()), 
	m_kernel(kernel),
	m_x_boundary(xbc.clone()), 
	m_y_boundary(ybc.clone()), 
	m_x_index(kernel->size()),
	m_y_index(kernel->size()),
	m_x_weight(kernel->size()),
	m_y_weight(kernel->size()), 
	m_x_cache(kernel->size(), *m_x_boundary, false), 
	m_y_cache(kernel->size(), *m_y_boundary, true)
{
	prefilter(image); 
}

template <typename T>
void T2DConvoluteInterpolator<T>::prefilter(const T2DDatafield<T>& image)
{
	m_x_boundary->set_width(image.get_size().x); 
	m_x_cache.reset();
	m_y_boundary->set_width(image.get_size().y); 
	m_y_cache.reset();
	


	min_max<typename T2DDatafield<T>::const_iterator >::get(image.begin(), image.end(), m_min, m_max);
	// always allow a zero value 
	if (T() < m_min) 
		m_min = T(); 

	
	// copy the data
	__dispatch_copy<T2DDatafield<T>, TCoeff2D >::apply(image, m_coeff); 
	if (m_kernel->get_poles().empty()) 
		return; 

	int cachXSize = image.get_size().x;	
	int cachYSize = image.get_size().y;
	
	{
		coeff_vector buffer(cachXSize);
		for (int y = 0; y < cachYSize; y++) {
			m_coeff.get_data_line_x(y,buffer);
			m_x_boundary->filter_line(buffer, m_kernel->get_poles());
			m_coeff.put_data_line_x(y,buffer);
		}
	}
	
	{
		coeff_vector buffer(cachYSize);
		for (int x = 0; x < cachXSize; x++) {
			m_coeff.get_data_line_y(x,buffer);
			m_y_boundary->filter_line(buffer, m_kernel->get_poles());
			m_coeff.put_data_line_y(x,buffer);
		}
	}
}

template <typename T>
T2DConvoluteInterpolator<T>::~T2DConvoluteInterpolator()
{
}

template <typename T>
const typename T2DConvoluteInterpolator<T>::TCoeff2D& T2DConvoluteInterpolator<T>::get_coefficients() const
{
	return m_coeff; 
}
	

template <class T, class U>
struct bounded<T2DVector<T>, T2DVector<U> > {
	static void apply(T2DVector<T>& r, const T2DVector<U>& min, const T2DVector<U>& max)
	{
		r.x = (r.x >= min.x) ? ( (r.x <= max.x) ? r.x : max.x) : min.x;
		r.y = (r.y >= min.y) ? ( (r.y <= max.y) ? r.y : max.y) : min.y;
	}
};

// this struct is created to letthe compiler create fixed sized loops 
// which can then be optimezed and unrolled 
template <class C, int size>
struct add_2d {
	typedef typename C::value_type U; 
	
	static typename C::value_type apply(const C&  coeff, const CSplineKernel::VWeight& xweight, 
					    const CSplineKernel::VWeight& yweight,
					    const CSplineKernel::VIndex& xindex, 
					    const CSplineKernel::VIndex& yindex) 
	{
		U result = U();
		for (size_t y = 0; y < size; ++y) {
			U rx = U();
			const U *p = &coeff(0, yindex[y]);
			for (size_t x = 0; x < size; ++x) {
				rx += xweight[x] * p[xindex[x]];
			}
			result += yweight[y] * rx; 
		}
		return result; 
	}
};


template <typename T>
typename T2DConvoluteInterpolator<T>::TCoeff2D::value_type T2DConvoluteInterpolator<T>::evaluate() const
{
	typedef typename TCoeff2D::value_type U; 

	U result = U();
	
	// give the compiler some chance to optimize and unroll the 
	// interpolation loop by creating some fixed size calls  
	switch (m_kernel->size()) {
	case 2: result = add_2d<TCoeff2D,2>::apply(m_coeff, m_x_weight, m_y_weight, 
					    m_x_index, m_y_index); break; 
	case 3: result = add_2d<TCoeff2D,3>::apply(m_coeff, m_x_weight, m_y_weight, 
					    m_x_index, m_y_index); break; 
	case 4: result = add_2d<TCoeff2D,4>::apply(m_coeff, m_x_weight, m_y_weight, 
					    m_x_index, m_y_index); break; 
	case 5: result = add_2d<TCoeff2D,5>::apply(m_coeff, m_x_weight, m_y_weight, 
					    m_x_index, m_y_index); break; 
	case 6: result = add_2d<TCoeff2D,6>::apply(m_coeff, m_x_weight, m_y_weight, 
					    m_x_index, m_y_index); break; 
	default: {
		/* perform interpolation */
		for (size_t y = 0; y < m_kernel->size(); ++y) {
			U rx = U();
			const typename  TCoeff2D::value_type *p = &m_coeff(0, m_y_index[y]);
			for (size_t x = 0; x < m_kernel->size(); ++x) {
				rx += m_x_weight[x] * p[m_x_index[x]];
				cvdebug() << m_x_weight[x] << "*" << p[m_x_index[x]] << "\n"; 
			}
			result += m_y_weight[y] * rx; 
		}
	}
	} // end switch 

	return result; 
}

template <class C, int size>
struct add_2d_new {
	typedef typename C::value_type U; 
	
	static typename C::value_type value(const C&  coeff, const CSplineKernel::SCache& xc, 
					    const CSplineKernel::SCache& yc) 
	{
		U result = U();
		if (xc.is_flat) {
			for (size_t y = 0; y < size; ++y) {
				U rx = U();
				const U *p = &coeff(0, yc.index[y]);
				for (size_t x = 0; x < size; ++x) {
					rx += xc.weights[x] * p[xc.start_idx + x];
				}
				result += yc.weights[y] * rx; 
			}
		}else{
			for (size_t y = 0; y < size; ++y) {
				U rx = U();
				const U *p = &coeff(0, yc.index[y]);
				for (size_t x = 0; x < size; ++x) {
					rx += xc.weights[x] * p[xc.index[x]];
				}
				result += yc.weights[y] * rx; 
			}
		}
		return result; 
	}
};

template <typename T>
struct add_2d_new<T2DDatafield< T >, 1> {
	

	static T value(const T2DDatafield< T >&  coeff, 
		       const CSplineKernel::SCache& xc, 
		       const CSplineKernel::SCache& yc) {
		return coeff(xc.index[0], yc.index[0]); 
	}
}; 


#ifdef __SSE__
template <>
struct add_2d_new<T2DDatafield< double >, 4> {
	static double value(const T2DDatafield< double >&  coeff, 
			    const CSplineKernel::SCache& xc, 
			    const CSplineKernel::SCache& yc); 
}; 
#endif

#ifdef __SSE2__

template <>
struct add_2d_new<T2DDatafield< float >, 4> {
	

	static float value(const T2DDatafield< float >&  coeff, 
			    const CSplineKernel::SCache& xc, 
			    const CSplineKernel::SCache& yc); 
}; 
#endif


template <typename T>
T  T2DConvoluteInterpolator<T>::operator () (const C2DFVector& x) const
{
	typedef typename TCoeff2D::value_type U; 
	
	m_kernel->get_uncached(x.x, m_x_cache);
	
	if (x.y != m_y_cache.x) 
		m_kernel->get_cached(x.y, m_y_cache);
	
	U result = U();
	
	// give the compiler some chance to optimize 
	switch (m_kernel->size()) {
	case 1: result = add_2d_new<TCoeff2D,1>::value(m_coeff, m_x_cache, m_y_cache); break; 
	case 2: result = add_2d_new<TCoeff2D,2>::value(m_coeff, m_x_cache, m_y_cache); break; 
	case 3: result = add_2d_new<TCoeff2D,3>::value(m_coeff, m_x_cache, m_y_cache); break; 
	case 4: result = add_2d_new<TCoeff2D,4>::value(m_coeff, m_x_cache, m_y_cache); break; 
	case 5: result = add_2d_new<TCoeff2D,5>::value(m_coeff, m_x_cache, m_y_cache); break; 
	case 6: result = add_2d_new<TCoeff2D,6>::value(m_coeff, m_x_cache, m_y_cache); break; 
	default: {
		/* perform interpolation */
		assert(0 && "spline degree > 5 not implemented");
	}
	} // end switch 
	
	bounded<U, T>::apply(result, m_min, m_max);
	
	return round_to<U, T>::value(result); 
}

template <typename T>
T2DVector<T> T2DConvoluteInterpolator<T>::derivative_at(const C2DFVector& x) const
{
	T2DVector<T> result;
	
	// cut at boundary maybe we can do better
	if (x.x < 0.0 || x.y < 0.0 || x.x >= m_coeff.get_size().x || x.y >= m_coeff.get_size().y)
		return result;

	const int xi = m_kernel->get_indices(x.x, m_x_index); 
	const double fx = x.x - xi; 
	m_kernel->get_derivative_weights(fx, m_x_weight); 
	m_x_boundary->apply(m_x_index, m_x_weight);
	
	const int yi = m_kernel->get_indices(x.y, m_y_index); 
	const double fy = x.y - yi; 
	m_kernel->get_weights(fy, m_y_weight);
	m_y_boundary->apply(m_y_index, m_y_weight);
	

	typename TCoeff2D::value_type r = evaluate();	
	result.x = round_to<typename TCoeff2D::value_type, T>::value(r);  

	
	m_kernel->get_weights(fx, m_x_weight); 
	m_kernel->get_derivative_weights(fy, m_y_weight); 

	r = evaluate();	
	result.y = round_to<typename TCoeff2D::value_type, T>::value(r);  
	
	return result; 
}

NS_MIA_END