blender/extern/libmv/intern/detector.cc

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/*
* ***** BEGIN GPL LICENSE BLOCK *****
*
* 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.
*
* The Original Code is Copyright (C) 2011 Blender Foundation.
* All rights reserved.
*
* Contributor(s): Blender Foundation,
* Sergey Sharybin
*
* ***** END GPL LICENSE BLOCK *****
*/
#include "intern/detector.h"
#include "intern/image.h"
#include "intern/utildefines.h"
#include "libmv/simple_pipeline/detect.h"
using libmv::Detect;
using libmv::DetectOptions;
using libmv::Feature;
using libmv::FloatImage;
struct libmv_Features {
int count;
Feature* features;
};
namespace {
libmv_Features *libmv_featuresFromVector(
const libmv::vector<Feature>& features) {
libmv_Features* libmv_features = LIBMV_STRUCT_NEW(libmv_Features, 1);
int count = features.size();
if (count) {
libmv_features->features = LIBMV_STRUCT_NEW(Feature, count);
for (int i = 0; i < count; i++) {
libmv_features->features[i] = features.at(i);
}
} else {
libmv_features->features = NULL;
}
libmv_features->count = count;
return libmv_features;
}
void libmv_convertDetectorOptions(libmv_DetectOptions *options,
DetectOptions *detector_options) {
switch (options->detector) {
#define LIBMV_CONVERT(the_detector) \
case LIBMV_DETECTOR_ ## the_detector: \
detector_options->type = DetectOptions::the_detector; \
break;
LIBMV_CONVERT(FAST)
LIBMV_CONVERT(MORAVEC)
LIBMV_CONVERT(HARRIS)
#undef LIBMV_CONVERT
}
detector_options->margin = options->margin;
detector_options->min_distance = options->min_distance;
detector_options->fast_min_trackness = options->fast_min_trackness;
detector_options->moravec_max_count = options->moravec_max_count;
detector_options->moravec_pattern = options->moravec_pattern;
detector_options->harris_threshold = options->harris_threshold;
}
} // namespace
libmv_Features *libmv_detectFeaturesByte(const unsigned char* image_buffer,
int width,
int height,
int channels,
libmv_DetectOptions* options) {
// Prepare the image.
FloatImage image;
libmv_byteBufferToFloatImage(image_buffer, width, height, channels, &image);
// Configure detector.
DetectOptions detector_options;
libmv_convertDetectorOptions(options, &detector_options);
// Run the detector.
libmv::vector<Feature> detected_features;
Detect(image, detector_options, &detected_features);
// Convert result to C-API.
libmv_Features* result = libmv_featuresFromVector(detected_features);
return result;
}
libmv_Features* libmv_detectFeaturesFloat(const float* image_buffer,
int width,
int height,
int channels,
libmv_DetectOptions* options) {
// Prepare the image.
FloatImage image;
libmv_floatBufferToFloatImage(image_buffer, width, height, channels, &image);
// Configure detector.
DetectOptions detector_options;
libmv_convertDetectorOptions(options, &detector_options);
// Run the detector.
libmv::vector<Feature> detected_features;
Detect(image, detector_options, &detected_features);
// Convert result to C-API.
libmv_Features* result = libmv_featuresFromVector(detected_features);
return result;
}
void libmv_featuresDestroy(libmv_Features* libmv_features) {
if (libmv_features->features) {
LIBMV_STRUCT_DELETE(libmv_features->features);
}
LIBMV_STRUCT_DELETE(libmv_features);
}
int libmv_countFeatures(const libmv_Features* libmv_features) {
return libmv_features->count;
}
void libmv_getFeature(const libmv_Features* libmv_features,
int number,
double* x,
double* y,
double* score,
double* size) {
Feature &feature = libmv_features->features[number];
*x = feature.x;
*y = feature.y;
*score = feature.score;
*size = feature.size;
}