mirror of
https://github.com/acanas/swad-core.git
synced 2024-09-22 00:00:40 +02:00
447 lines
14 KiB
C++
447 lines
14 KiB
C++
|
/*
|
||
|
* FOTOMATON. Detector de rostros de la plataforma SWAD
|
||
|
*
|
||
|
* Copyright (C) 2018 Daniel J. Calandria Hernández,
|
||
|
* Antonio Cañas Vargas &
|
||
|
* Jesús Mesa González.
|
||
|
*
|
||
|
* 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 "util.h"
|
||
|
#include <iostream>
|
||
|
#include <vector>
|
||
|
#include <stdio.h>
|
||
|
|
||
|
using namespace std;
|
||
|
using namespace cv;
|
||
|
|
||
|
bool operator < ( const pair<REAL, Rect> &a, const pair<REAL, Rect> &b )
|
||
|
{
|
||
|
return a.first < b.first;
|
||
|
}
|
||
|
|
||
|
|
||
|
///////////////////////////////////////////////////////////
|
||
|
|
||
|
void stretch_contrast (IplImage *m, int channel, int *h, int max, int f);
|
||
|
void enhance_contrast (IplImage *img, float t);
|
||
|
void enhance_saturation (IplImage *img, float t);
|
||
|
void enhance_light (IplImage *img, int r, int c, float f);
|
||
|
void contraer (IplImage *mat, int channel, int orig, int dest, int f);
|
||
|
bool check_background (IplImage *img, int r, int c, int t);
|
||
|
void ExtractObjectImage ( IplImage *src, const Rect &r, float ratio, IplImage *dst );
|
||
|
|
||
|
///////////////////////////////////////////////////////////
|
||
|
|
||
|
int main (int argc, char **argv)
|
||
|
{
|
||
|
|
||
|
char file_name[512];
|
||
|
|
||
|
if (argc < 4)
|
||
|
{
|
||
|
cout << "fotomaton <classifier> <input_file> <width>" << endl;
|
||
|
return 2;
|
||
|
}
|
||
|
|
||
|
// Obtener la anchura de la imagen.
|
||
|
int width = atoi ( argv[3] );
|
||
|
|
||
|
if ( width <= 0)
|
||
|
{
|
||
|
cout << "Error: Width must be positive!" << endl;
|
||
|
return 2;
|
||
|
}
|
||
|
|
||
|
// Cargar el clasificador en cascada proporcionado como argumento.
|
||
|
CascadeClassifier cascade;
|
||
|
string ruta_classifier(argv[1]); // Convertir en string la ruta donde se encuentra el clasificador.
|
||
|
|
||
|
if (!cascade.load (ruta_classifier)){
|
||
|
|
||
|
cout << "Error: Classifier not found!" << endl;
|
||
|
return 2;
|
||
|
}
|
||
|
|
||
|
// Cargar imagen.
|
||
|
IplImage *img = cvLoadImage(argv[2]);
|
||
|
if (!img)
|
||
|
{
|
||
|
cout << "Error: Image cannot be read!" << endl;
|
||
|
return 2;
|
||
|
}
|
||
|
|
||
|
string str_name;
|
||
|
PartPath ( argv[2], 0, &str_name, 0 );
|
||
|
|
||
|
for (int i = strlen(argv[2])-1; i>= 0; i--)
|
||
|
if (argv[2][i] == '.')
|
||
|
{
|
||
|
argv[2][i] = '\0';
|
||
|
break;
|
||
|
}
|
||
|
|
||
|
// Detectar objetos.
|
||
|
|
||
|
Mat gray_img; // Crear una matriz donde almacenar en escala de grises la imagen leída.
|
||
|
Mat m_img = cvarrToMat(img);
|
||
|
cvtColor (m_img, gray_img, CV_BGR2GRAY); // Almacenar en la matriz anterior la imagen en escala de grises.
|
||
|
vector <Rect> objects; // Crear un vector en el cual almacenar los objetos detectados.
|
||
|
|
||
|
cascade.detectMultiScale(gray_img, objects, 1.09, 1);
|
||
|
|
||
|
// Si no se han detectado caras (vector de rectángulos vacío) se genera el mapa de la imagen
|
||
|
// sin enmascarar.
|
||
|
if (objects.empty())
|
||
|
{
|
||
|
IplImage *img_map = cvCreateImage (cvSize(width, (width*img->height)/img->width), 8, 3);
|
||
|
cvResize (img, img_map);
|
||
|
sprintf (file_name, "%s_map.jpg", argv[2]);
|
||
|
cvSaveImage (file_name, img_map);
|
||
|
return 1;
|
||
|
}
|
||
|
|
||
|
// Enmascarar la imagen y generar mapa.
|
||
|
if(img->width < width)
|
||
|
width = img->width;
|
||
|
|
||
|
IplImage *img_map = cvCreateImage (cvSize(width, (width*img->height)/img->width), 8, 3);
|
||
|
cvResize (img, img_map);
|
||
|
CvMat *mask = cvCreateMat (img_map->height, img_map->width, CV_8UC1);
|
||
|
cvSet (mask, cvRealScalar(1));
|
||
|
|
||
|
sprintf (file_name, "%s_map.txt", argv[2]);
|
||
|
ofstream map_file ( file_name );
|
||
|
|
||
|
|
||
|
// Extaer cada una de las imágenes y aplicar los diferentes filtros.
|
||
|
IplImage *img_object = cvCreateImage ( cvSize(150, 200), 8, 3 );
|
||
|
for (int i = objects.size()-1; i >= 0; i--)
|
||
|
{
|
||
|
int res = 1; // fondo blanco?
|
||
|
|
||
|
Rect r;
|
||
|
r.x = (objects[i].x * width) / img->width;
|
||
|
r.y = (objects[i].y * width) / img->width;
|
||
|
r.width = (objects[i].width * width) / img->width;
|
||
|
r.height = (objects[i].height * width) / img->width;
|
||
|
cvCircle ( mask, cvPoint(r.x + r.width/2, r.y + r.height/2), r.width*0.75+1, CV_RGB(0,0,0), -1, CV_AA );
|
||
|
|
||
|
// Extraer y mejorar imagen.
|
||
|
////////////////////////////////////////////////////////
|
||
|
ExtractObjectImage ( img, objects[i], 0.75, img_object );
|
||
|
sprintf (file_name, "%s_%03d_paso1.jpg", argv[2], i);
|
||
|
cvSaveImage (file_name, img_object);
|
||
|
|
||
|
enhance_contrast (img_object, 0.0009);
|
||
|
enhance_saturation ( img_object, 0.0001);
|
||
|
|
||
|
if (!check_background( img_object, int(0.07*img_object->height), int(0.1*img_object->width), 150 ) )
|
||
|
{
|
||
|
cvCircle ( img_map, cvPoint(r.x + r.width/2, r.y + r.height/2), r.width*0.75+1, CV_RGB(255,0,0), 2, CV_AA );
|
||
|
res = 0;
|
||
|
}
|
||
|
else
|
||
|
{
|
||
|
cvCircle ( img_map, cvPoint(r.x + r.width/2, r.y + r.height/2), r.width*0.75+1, CV_RGB(0,255,0), 2, CV_AA );
|
||
|
sprintf (file_name, "%s_%03d_paso2.jpg", argv[2], i);
|
||
|
cvSaveImage (file_name, img_object);
|
||
|
enhance_light (img_object, int(0.07*img_object->height),
|
||
|
int(0.1*img_object->width), 20.0);
|
||
|
sprintf (file_name, "%s_%03d_paso3.jpg", argv[2], i);
|
||
|
cvSaveImage (file_name, img_object);
|
||
|
}
|
||
|
////////////////////////////////////////////////////////
|
||
|
|
||
|
sprintf (file_name, "%s_%03d", str_name.c_str(), i);
|
||
|
map_file << int(r.x + r.width/2) << " " << int(r.y + r.height/2) << " " << int(r.width*0.75+1) << " " << res << " " << file_name << '\n';
|
||
|
}
|
||
|
map_file.close();
|
||
|
cvSubS ( img_map, cvScalar(80,120,120,0), img_map, mask );
|
||
|
sprintf (file_name, "%s_map.jpg", argv[2]);
|
||
|
cvSaveImage (file_name, img_map);
|
||
|
|
||
|
|
||
|
cvReleaseImage (&img_map);
|
||
|
cvReleaseImage (&img_object);
|
||
|
cvReleaseImage (&img);
|
||
|
|
||
|
return 0;
|
||
|
}
|
||
|
|
||
|
|
||
|
void ExtractObjectImage ( IplImage *src, const Rect &r, float ratio, IplImage *dst )
|
||
|
{
|
||
|
Rect obj_r;
|
||
|
|
||
|
obj_r = r;
|
||
|
obj_r.y -= r.height / 2;
|
||
|
obj_r.height += 1.5*r.height;
|
||
|
obj_r.x -= r.width / 2;
|
||
|
obj_r.width += r.width;
|
||
|
if (obj_r.y < 0)
|
||
|
obj_r.y = 0;
|
||
|
if (obj_r.x < 0)
|
||
|
obj_r.x = 0;
|
||
|
if (obj_r.y + obj_r.height >= src->height)
|
||
|
obj_r.height = src->height - obj_r.y;
|
||
|
if (obj_r.x + obj_r.width >= src->width)
|
||
|
obj_r.width = src->width - obj_r.x;
|
||
|
|
||
|
if (obj_r.width / obj_r.height > ratio)
|
||
|
{
|
||
|
//Añadir filas por abajo, si se puede. Si no, quitar columnas
|
||
|
if (obj_r.y + obj_r.width / ratio > src->height)
|
||
|
{
|
||
|
float f = obj_r.height * ratio;
|
||
|
obj_r.x = obj_r.x + (obj_r.width - f)/2;
|
||
|
obj_r.width = f;
|
||
|
}
|
||
|
else
|
||
|
obj_r.height = obj_r.width / ratio;
|
||
|
}
|
||
|
else
|
||
|
{
|
||
|
//Añadir columnas si se puede
|
||
|
float f = obj_r.height * ratio;
|
||
|
if (obj_r.x + (obj_r.width - f)/2 < 0 ||
|
||
|
obj_r.x + (obj_r.width + f)/2 > src->width )
|
||
|
obj_r.height = obj_r.width / ratio;
|
||
|
else
|
||
|
{
|
||
|
obj_r.x = obj_r.x + (obj_r.width - f)/2;
|
||
|
obj_r.width = f;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
CvMat mat_aux;
|
||
|
cvGetSubRect (src, &mat_aux, obj_r);
|
||
|
cvResize (&mat_aux, dst);
|
||
|
}
|
||
|
|
||
|
|
||
|
|
||
|
/*************************************************************/
|
||
|
/* FILTROS DE REALCE */
|
||
|
/*************************************************************/
|
||
|
|
||
|
//Mejora de contraste.
|
||
|
|
||
|
void enhance_contrast (IplImage *img, float t)
|
||
|
{
|
||
|
int *hist[3];
|
||
|
for (int i = 0; i < 3; ++i)
|
||
|
{
|
||
|
hist[i] = new int[256];
|
||
|
memset (hist[i], 0, sizeof(int)*256);
|
||
|
}
|
||
|
int count = 0;
|
||
|
|
||
|
//Calcular histogramas
|
||
|
for (int i = 0; i < img->height; ++i)
|
||
|
for (int j = 0; j < img->width; ++j)
|
||
|
for (int k = 0; k < 3; ++k)
|
||
|
{
|
||
|
++hist[k][((uchar*) (img->imageData + i * img->widthStep))[j * img->nChannels + k]];
|
||
|
}
|
||
|
|
||
|
count = img->height * img->width;
|
||
|
|
||
|
//Estirar el contraste teniendo en cuenta los pixels de piel.
|
||
|
for (int i = 0; i < 3; ++i)
|
||
|
stretch_contrast (img, i, hist[i], int(t * count), 255 );
|
||
|
|
||
|
}
|
||
|
// Mejora de saturacion.
|
||
|
void enhance_saturation (IplImage *img, float t)
|
||
|
{
|
||
|
cvCvtColor(img,img, CV_RGB2HSV);
|
||
|
|
||
|
int hist[256];
|
||
|
int count = 0;
|
||
|
|
||
|
// Calcular histogramas.
|
||
|
for (int i = 0; i < img->height; ++i)
|
||
|
for (int j = 0; j < img->width; ++j)
|
||
|
{
|
||
|
++hist[((uchar*) (img->imageData + i*img->widthStep))[j * img->nChannels + 2]];
|
||
|
++count;
|
||
|
}
|
||
|
|
||
|
count = img->height *img->width;
|
||
|
|
||
|
// Estirar el contraste teniendo en cuenta los pixels de piel
|
||
|
stretch_contrast (img, 2, hist, int(t * count), 255 );
|
||
|
|
||
|
cvCvtColor(img,img, CV_HSV2RGB);
|
||
|
}
|
||
|
|
||
|
// Realce de blancos.
|
||
|
void enhance_light (IplImage *img, int r, int c, float f)
|
||
|
{
|
||
|
int avg[3] = {0,0,0};
|
||
|
int nuevo_valor, savg, total = 0;
|
||
|
|
||
|
// Obtener el color medio de la imagen, tomando las esquinas como referencia
|
||
|
|
||
|
// Esquina izquierda.
|
||
|
for (int i = 0; i <= r; ++i)
|
||
|
for (int j = c - (c * i) / r; j >= 0; --j)
|
||
|
{
|
||
|
++total;
|
||
|
for (int n = 0; n < 3; ++n)
|
||
|
avg[n] += ((uchar*)(img->imageData + i * img->widthStep))[j * img->nChannels + n];
|
||
|
}
|
||
|
// Esquina derecha.
|
||
|
for (int i = 0; i <= r; ++i)
|
||
|
for (int j = (c * i) / r; j <= c; ++j)
|
||
|
{
|
||
|
++total;
|
||
|
for (int n = 0; n < 3; ++n)
|
||
|
avg[n] += ((uchar*)(img->imageData + i * img->widthStep))[img->width -1 - c + j];
|
||
|
}
|
||
|
|
||
|
for (int i = 0; i < 3; ++i)
|
||
|
avg[i] /= total;
|
||
|
|
||
|
// Obtener el nuevo valor de blanco.
|
||
|
savg = (avg[0] + avg[1] + avg[2])/3;
|
||
|
nuevo_valor = int(savg + (255 - savg) / f);
|
||
|
|
||
|
//Desplazar hacia el nuevo blanco
|
||
|
for (int i = 0; i < 3; ++i)
|
||
|
contraer (img, i, avg[i], nuevo_valor, 255);
|
||
|
}
|
||
|
|
||
|
// Estira el histograma h asociado a m.
|
||
|
void stretch_contrast (IplImage *m, int channel, int *h, int max, int f)
|
||
|
{
|
||
|
int /*max = int(t * m.rows() * m.cols()),*/ sum = 0;
|
||
|
int inf = 0, sup = 0, w;
|
||
|
|
||
|
// Limite inferior.
|
||
|
for (unsigned i = 0; i < 256; ++i)
|
||
|
{
|
||
|
sum += h[i];
|
||
|
|
||
|
if (sum > max)
|
||
|
{ inf = i; break; }
|
||
|
}
|
||
|
|
||
|
// Limite superior.
|
||
|
sum = 0;
|
||
|
for (int i = 256-1; i >= 0; --i)
|
||
|
{
|
||
|
sum += h[i];
|
||
|
|
||
|
if (sum > max)
|
||
|
{ sup = i; break; }
|
||
|
}
|
||
|
|
||
|
|
||
|
// Estirar histograma entre [inf,sup].
|
||
|
w = sup - inf;
|
||
|
|
||
|
//cout << "inf = " << inf << ", sup = " << sup << ", w = " << w << endl;
|
||
|
|
||
|
for (int i = 0; i < m->height; ++i)
|
||
|
for (int j = 0; j < m->width; ++j)
|
||
|
{
|
||
|
if (((uchar*) (m->imageData + i * m->widthStep))[j * m->nChannels + channel] < inf)
|
||
|
((uchar*) (m->imageData + i * m->widthStep))[j * m->nChannels + channel] = 0;
|
||
|
else if (((uchar*) (m->imageData + i * m->widthStep))[j * m->nChannels + channel] > sup)
|
||
|
((uchar*) (m->imageData + i * m->widthStep))[j * m->nChannels + channel] = f;
|
||
|
else ((uchar*) (m->imageData + i * m->widthStep))[j * m->nChannels + channel] = int(rint( (((uchar*) (m->imageData + i * m->widthStep))[j * m->nChannels + channel] - inf) * f / w));
|
||
|
}
|
||
|
}
|
||
|
|
||
|
/*
|
||
|
* Reimplementación de la rutina contraer del proyecto de Alvarez y Rodrigo.
|
||
|
*/
|
||
|
void contraer (IplImage *mat, int channel, int orig, int dest, int f)
|
||
|
{
|
||
|
float k = dest / float(orig);
|
||
|
|
||
|
if (f > orig)
|
||
|
{
|
||
|
for (int i = 0; i < mat->height; ++i)
|
||
|
for (int j = 0; j < mat->width; ++j)
|
||
|
{
|
||
|
float val;
|
||
|
|
||
|
if (((uchar*) (mat->imageData + i * mat->widthStep))[j * mat->nChannels + channel] < orig)
|
||
|
val = ((uchar*) (mat->imageData + i * mat->widthStep))[j * mat->nChannels + channel] * k;
|
||
|
else
|
||
|
val = ((((uchar*) (mat->imageData + i * mat->widthStep))[j * mat->nChannels + channel] - orig) * (f - dest) / float(f - orig)) + dest;
|
||
|
|
||
|
// Se comprueba que este dentro del rango [0,f]
|
||
|
if (val < 0)
|
||
|
((uchar*) (mat->imageData + i * mat->widthStep))[j * mat->nChannels + channel] = 0;
|
||
|
else if (val > f)
|
||
|
((uchar*) (mat->imageData + i * mat->widthStep))[j * mat->nChannels + channel] = f;
|
||
|
else
|
||
|
((uchar*) (mat->imageData + i * mat->widthStep))[j * mat->nChannels + channel] = int(rint(val));
|
||
|
}
|
||
|
}
|
||
|
|
||
|
}
|
||
|
|
||
|
|
||
|
bool check_background (IplImage *img, int r, int c, int t)
|
||
|
{
|
||
|
// Comprueba los dos triangulos de las esquinas superiores.
|
||
|
int avg[3]; // Medias para rojo, verde y azul.
|
||
|
bool ok = true;
|
||
|
int total = 0;
|
||
|
|
||
|
|
||
|
// Esquina izquierda.
|
||
|
avg[0] = avg[1] = avg[2] = 0;
|
||
|
|
||
|
// Calcular media.
|
||
|
for (int i = 0; i <= r; ++i)
|
||
|
for (int j = c - (c * i) / r; j >= 0; --j)
|
||
|
{
|
||
|
++total;
|
||
|
avg[0] += ((uchar*) (img->imageData + i * img->widthStep))[j * img->nChannels ];
|
||
|
avg[1] += ((uchar*) (img->imageData + i * img->widthStep))[j * img->nChannels + 1];
|
||
|
avg[2] += ((uchar*) (img->imageData + i * img->widthStep))[j * img->nChannels + 2];
|
||
|
}
|
||
|
avg[0] /= total;
|
||
|
avg[1] /= total;
|
||
|
avg[2] /= total;
|
||
|
ok = (avg[0] + avg[1] + avg[2]) > 3*t;
|
||
|
if (!ok) //el fondo es oscuro
|
||
|
return false;
|
||
|
|
||
|
// Esquina derecha.
|
||
|
avg[0]= avg[1] = avg[2] = total = 0;
|
||
|
for (int i = 0; i <= r; ++i)
|
||
|
for (int j = (c * i) / r; j <= c; ++j)
|
||
|
{
|
||
|
++total;
|
||
|
avg[0] += ((uchar*) (img->imageData + i * img->widthStep))[(img->width - 1 - c + j) * img->nChannels ];
|
||
|
avg[1] += ((uchar*) (img->imageData + i * img->widthStep))[(img->width - 1 - c + j) * img->nChannels + 1];
|
||
|
avg[2] += ((uchar*) (img->imageData + i * img->widthStep))[(img->width - 1 - c + j) * img->nChannels + 2];
|
||
|
}
|
||
|
|
||
|
avg[0] /= total;
|
||
|
avg[1] /= total;
|
||
|
avg[2] /= total;
|
||
|
ok = (avg[0] + avg[1] + avg[2]) > 3*t;
|
||
|
|
||
|
return ok;
|
||
|
}
|