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main.cpp
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/*
Copyright (C) 2014 Jerome Revaud
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 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 this program. If not, see <http://www.gnu.org/licenses/>
*/
#include "std.h"
#include "image.h"
#include "io.h"
#include "deep_matching.h"
#include "main.h"
#include <thread>
void usage(const int language)
{
#define p(msg) std_printf(msg "\n");
p("usage:");
switch(language){
case EXE_OPTIONS:
p("./deepmatching image1 image2 [options]");
p("Compute the 'DeepMatching' between two images and print a list of")
p("pair-wise point correspondences:")
p(" x1 y1 x2 y2 score index ...")
p("(index refers to the local maximum from which the match was retrieved)")
p("Images must be in PPM, PNG or JPG format. Version 1.2.2")
break;
case MATLAB_OPTIONS:
p("matches = deepmatching(image1, image2 [, options])")
p("Compute the 'DeepMatching' between two images.")
p("Images must be HxWx3 single matrices.")
p("Options is an optional string argument ('' by default).")
p("The function returns a matrix with 6 columns, each row being x1 y1 x2 y2 score index.")
p("(index refers to the local maximum from which the match was retrieved)")
p("Version 1.2.2")
break;
case PYTHON_OPTIONS:
p("matches = deepmatching.deepmatching(image1, image2, options='')")
p("Compute the 'DeepMatching' between two images.")
p("Images must be HxWx3 numpy arrays (converted to float32).")
p("Options is an optional string argument ('' by default).")
p("The function returns a numpy array with 6 columns, each row being x1 y1 x2 y2 score index.")
p("(index refers to the local maximum from which the match was retrieved)")
p("Version 1.2.2")
break;
}
p("")
p("Options:")
p(" -h, --help print this message")
//p(" HOG parameters (low-level pixel descriptor):")
//p(" -png_settings (auto) recommended for uncompressed images")
//p(" -jpg_settings (auto) recommended for compressed images")
//p(" in more details: (for fine-tuning)")
//p(" -hog.presm <f=1.0> prior image smoothing")
//p(" -hog.midsm <f=1.0> intermediate HOG smoothing")
//p(" -hog.sig <f=0.2> sigmoid strength")
//p(" -hog.postsm <f=1.0> final HOG-smoothing")
//p(" -hog.ninth <f=0.3> robustness to pixel noise (eg. JPEG artifacts)")
p("")
p(" Matching parameters:")
//p(" -iccv_settings settings used for the ICCV paper")
//p(" -improved_settings (default) supposedly improved settings")
//p(" in more details: (for fine-tuning)")
p(" -downscale/-R <n=1> downsize the input images by a factor 2^n")
//p(" -overlap <n=999> use overlapping patches in image1 from level n")
//p(" -subref <n=0> 0: denser sampling or 1: not of image1 patches")
p(" -ngh_rad <n=0> if n>0: restrict matching to n pxl neighborhood")
p(" -nlpow <f=1.4> non-linear rectification x := x^f")
//p(" -maxima_mode <n=0> 0: from all top cells / 1: from local maxima")
//p(" -min_level <n=2> skip maxima in levels [0, 1, ..., n-1]")
p(" -mem <n=1> if n>0: optimize memory footprint (bit unstable)")
//p(" -scoring_mode <n=1> type of correspondence scoring mode (0/1)")
p("")
p(" Fully scale & rotation invariant DeepMatching:")
p(" if either one of these options is used, then this mode is activated:")
p(" -max_scale <factor=5> max scaling factor")
p(" -rot_range <from=0> <to=360> rotation range")
p("")
p(" Other parameters:")
p(" -resize <width> <height> to resize input images beforehand")
p(" -v increase verbosity")
p(" -nt <n> multi-threading with <n> threads")
if(language==EXE_OPTIONS) {
p(" -out <file_name> output correspondences in a file")
exit(1);}
}
bool endswith(const char *str, const char *suffix)
{
if(!str || !suffix) return false;
size_t lenstr = strlen(str);
size_t lensuffix = strlen(suffix);
if(lensuffix > lenstr) return false;
return strncmp(str + lenstr - lensuffix, suffix, lensuffix) == 0;
}
image_t* rescale_image( image_t* im, int width, int height )
{
image_t* res = image_new(width,height);
image_resize_bilinear_newsize(res, im, width, height);
image_delete(im);
return res;
}
const char *parse_options(dm_params_t *params, scalerot_params_t *sr_params, bool *use_scalerot, float *fx, float *fy, const int argc, const char **argv, const int language, image_t **im1, image_t **im2) {
int current_arg = 0;
const char* out_filename = NULL;
// parse options
while(current_arg < argc)
{
const char* a = argv[current_arg++];
#define isarg(key) !strcmp(a,key)
if(isarg("-h") || isarg("--help") ) usage(language);
// HOG and patch parameters
//else if(isarg("-hog.presm"))
// params->desc_params.presmooth_sigma = atof(argv[current_arg++]);
//else if(isarg("-hog.sig"))
// params->desc_params.hog_sigmoid = atof(argv[current_arg++]);
//else if(isarg("-hog.midsm"))
// params->desc_params.mid_smoothing = atof(argv[current_arg++]);
//else if(isarg("-hog.postsm"))
// params->desc_params.post_smoothing = atof(argv[current_arg++]);
//else if(isarg("-hog.ninth"))
// params->desc_params.ninth_dim = atof(argv[current_arg++]);
//else if(isarg("-hog.nrmpix"))
// params->desc_params.norm_pixels = atof(argv[current_arg++]);
else if(isarg("-png_settings")) {
params->desc_params.presmooth_sigma = 0; // no image smoothing since the image is uncompressed
params->desc_params.hog_sigmoid = 0.2;
params->desc_params.mid_smoothing = 1.5;
params->desc_params.post_smoothing = 1;
params->desc_params.ninth_dim = 0.1; } // low ninth_dim since image PSNR is high
else if(isarg("-jpg_settings")) {
params->desc_params.presmooth_sigma = 1; // smooth the image to remove jpg artifacts
params->desc_params.hog_sigmoid = 0.2;
params->desc_params.mid_smoothing = 1.5;
params->desc_params.post_smoothing = 1;
params->desc_params.ninth_dim = 0.3; } // higher ninth_dim because of pixel noise
// matching parameters
else if(isarg("-R") || isarg("-downscale"))
params->prior_img_downscale = atoi(argv[current_arg++]);
//else if(isarg("-overlap"))
// params->overlap = atoi(argv[current_arg++]);
//else if(isarg("-subref"))
// params->subsample_ref = atoi(argv[current_arg++]);
else if(isarg("-nlpow"))
params->nlpow = atof(argv[current_arg++]);
else if(isarg("-ngh_rad"))
params->ngh_rad = atoi(argv[current_arg++]);
// maxima parameters
//else if(isarg("-maxima_mode"))
// params->maxima_mode = atoi(argv[current_arg++]);
else if(isarg("-mem")) {
params->low_mem = atoi(argv[current_arg++]); }
//else if(isarg("-min_level"))
// params->min_level = atoi(argv[current_arg++]);
//else if(isarg("-scoring_mode"))
// params->scoring_mode = atoi(argv[current_arg++]);
//else if(isarg("-iccv_settings")) {
// params->prior_img_downscale = 2;
// params->overlap = 0; // overlap from level 0
// params->subsample_ref = 1;
// params->nlpow = 1.6;
// params->maxima_mode = 1;
// params->low_mem = 0;
// params->min_level = 2;
// params->scoring_mode = 0; }
//else if(isarg("-improved_settings")) {
// params->prior_img_downscale = 1; // less down-scale
// params->overlap = 999; // no overlap
// params->subsample_ref = 0; // dense patch sampling at every level in first image
// params->nlpow = 1.4;
// params->maxima_mode = 0;
// params->low_mem = 1;
// params->min_level = 2;
// params->scoring_mode = 1; } // improved scoring
//else if(isarg("-max_psize")) {
// params->max_psize = atoi(argv[current_arg++]); }
// scale & rot invariant version
else if(isarg("-scale") || isarg("-max_scale")) {
*use_scalerot = true;
float scale = atof(argv[current_arg++]);
sr_params->max_sc0 = sr_params->max_sc1 = int(1 + 2*log2(scale)); }
else if(isarg("-rot") || isarg("-rot_range")) {
*use_scalerot = true;
int min_rot = atoi(argv[current_arg++]);
int max_rot = atoi(argv[current_arg++]);
while( min_rot < 0 ) {
min_rot += 360;
max_rot += 360;
}
sr_params->min_rot = int(floor(0.5 + min_rot/45.));
sr_params->max_rot = int(floor(1.5 + max_rot/45.));
while( sr_params->max_rot - sr_params->min_rot > 8 )
sr_params->max_rot--;
assert( sr_params->min_rot < sr_params->max_rot ); }
// other parameters
else if(isarg("-resize")) {
assert((*im1)->width==(*im2)->width && (*im1)->height==(*im2)->height);
int width = atoi(argv[current_arg++]);
int height = atoi(argv[current_arg++]);
*fx *= (*im1)->width / float(width);
*fy *= (*im1)->height / float(height);
*im1 = rescale_image(*im1, width, height);
*im2 = rescale_image(*im2, width, height); }
else if(isarg("-v"))
params->verbose++;
else if(isarg("-nt")) {
params->n_thread = atoi(argv[current_arg++]);
if (params->n_thread==0)
params->n_thread = std::thread::hardware_concurrency(); }
else if(language == EXE_OPTIONS && isarg("-out"))
out_filename = argv[current_arg++];
else {
err_printf("error: unexpected parameter '%s'", a);
exit(-1);
}
}
if( *use_scalerot )
assert( params->ngh_rad == 0 || !"max trans cannot be used in full scale and rotation mode");
else
if( params->subsample_ref && (!ispowerof2((*im1)->width) || !ispowerof2((*im1)->height)) ) {
err_printf("WARNING: first image has dimension which are not power-of-2\n");
err_printf("For improved results, you should consider resizing the images with '-resize <w> <h>'\n");
}
return out_filename;
}
int main(int argc, const char ** argv)
{
if( argc<=2 || !strcmp(argv[1],"-h") || !strcmp(argv[1],"--help") ) usage(EXE_OPTIONS);
int current_arg = 3;
image_t *im1=NULL, *im2=NULL;
{
color_image_t *cim1 = color_image_load(argv[1]);
color_image_t *cim2 = color_image_load(argv[2]);
// Following deactivated because quite useless/dangerous in practice
// default behavior == always using -jpg_settings
//if( endswith(argv[1],"png") || endswith(argv[1],"PNG") )
// argv[--current_arg] = "-png_settings"; // set default
//if( endswith(argv[1],"ppm") || endswith(argv[1],"PPM") )
// argv[--current_arg] = "-png_settings"; // set default
//if( endswith(argv[1],"jpg") || endswith(argv[1],"JPG") )
// argv[--current_arg] = "-jpg_settings"; // set default
//if( endswith(argv[1],"jpeg") || endswith(argv[1],"JPEG") )
// argv[--current_arg] = "-jpg_settings"; // set default
im1 = image_gray_from_color(cim1);
im2 = image_gray_from_color(cim2);
color_image_delete(cim1);
color_image_delete(cim2);
}
// set params to default
dm_params_t params;
set_default_dm_params(&params);
scalerot_params_t sr_params;
set_default_scalerot_params(&sr_params);
bool use_scalerot = false;
float fx=1, fy=1;
// parse options
const char* out_filename = parse_options(&params, &sr_params, &use_scalerot, &fx, &fy, argc-current_arg,
&argv[current_arg], EXE_OPTIONS, &im1, &im2);
// compute deep matching
float_image* corres = use_scalerot ?
deep_matching_scale_rot( im1, im2, &params, &sr_params ) :
deep_matching ( im1, im2, &params, NULL ); // standard call
// save result
output_correspondences( out_filename, (corres_t*)corres->pixels, corres->ty, fx, fy );
free_image(corres);
image_delete(im1);
image_delete(im2);
return 0;
}

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