aboutsummaryrefslogtreecommitdiff
path: root/src/pix_opencv_knear.cc
diff options
context:
space:
mode:
Diffstat (limited to 'src/pix_opencv_knear.cc')
-rw-r--r--src/pix_opencv_knear.cc502
1 files changed, 502 insertions, 0 deletions
diff --git a/src/pix_opencv_knear.cc b/src/pix_opencv_knear.cc
new file mode 100644
index 0000000..0d8a98c
--- /dev/null
+++ b/src/pix_opencv_knear.cc
@@ -0,0 +1,502 @@
+////////////////////////////////////////////////////////
+//
+// GEM - Graphics Environment for Multimedia
+//
+// zmoelnig@iem.kug.ac.at
+//
+// Implementation file
+//
+// Copyright (c) 1997-2000 Mark Danks.
+// Copyright (c) Günther Geiger.
+// Copyright (c) 2001-2002 IOhannes m zmoelnig. forum::für::umläute. IEM
+// Copyright (c) 2002 James Tittle & Chris Clepper
+// For information on usage and redistribution, and for a DISCLAIMER OF ALL
+// WARRANTIES, see the file, "GEM.LICENSE.TERMS" in this distribution.
+//
+/////////////////////////////////////////////////////////
+
+#include "pix_opencv_knear.h"
+
+
+CPPEXTERN_NEW_WITH_TWO_ARGS(pix_opencv_knear, t_symbol *, A_DEFSYM, t_floatarg, A_DEFFLOAT )
+
+/////////////////////////////////////////////////////////
+//
+// pix_opencv_knear
+//
+/////////////////////////////////////////////////////////
+
+/////////////////////////////////////////////////////////
+//
+// Find the min box. The min box respect original aspect ratio image
+// The image is a binary data and background is white.
+//
+/////////////////////////////////////////////////////////
+
+
+void pix_opencv_knear :: findX(IplImage* imgSrc,int* min, int* max)
+{
+ int i;
+ int minFound=0;
+ CvMat data;
+ CvScalar maxVal=cvRealScalar(imgSrc->width * 255);
+ CvScalar val=cvRealScalar(0);
+
+ // for each col sum, if sum < width*255 then we find the min
+ // then continue to end to search the max, if sum< width*255 then is new max
+ for (i=0; i< imgSrc->width; i++)
+ {
+ cvGetCol(imgSrc, &data, i);
+ val= cvSum(&data);
+ if(val.val[0] < maxVal.val[0])
+ {
+ *max= i;
+ if(!minFound)
+ {
+ *min= i;
+ minFound= 1;
+ }
+ }
+
+ }
+}
+
+void pix_opencv_knear :: findY(IplImage* imgSrc,int* min, int* max)
+{
+ int i;
+ int minFound=0;
+ CvMat data;
+ CvScalar maxVal=cvRealScalar(imgSrc->width * 255);
+ CvScalar val=cvRealScalar(0);
+
+ // for each col sum, if sum < width*255 then we find the min
+ // then continue to end to search the max, if sum< width*255 then is new max
+ for (i=0; i< imgSrc->height; i++)
+ {
+ cvGetRow(imgSrc, &data, i);
+ val= cvSum(&data);
+ if(val.val[0] < maxVal.val[0])
+ {
+ *max=i;
+ if(!minFound)
+ {
+ *min= i;
+ minFound= 1;
+ }
+ }
+ }
+}
+
+/////////////////////////////////////////////////////////
+//
+// Find the bounding box.
+//
+//
+/////////////////////////////////////////////////////////
+
+CvRect pix_opencv_knear :: findBB(IplImage* imgSrc)
+{
+ CvRect aux;
+ int xmin, xmax, ymin, ymax;
+ xmin=xmax=ymin=ymax=0;
+
+ this->findX(imgSrc, &xmin, &xmax);
+ this->findY(imgSrc, &ymin, &ymax);
+
+ aux=cvRect(xmin, ymin, xmax-xmin, ymax-ymin);
+
+ return aux;
+}
+
+IplImage pix_opencv_knear :: preprocessing(IplImage* imgSrc,int new_width, int new_height)
+{
+ IplImage* result;
+ IplImage* scaledResult;
+
+ CvMat data;
+ CvMat dataA;
+ CvRect bb;//bounding box
+
+ // find bounding box
+ bb=this->findBB(imgSrc);
+
+ if ( ( bb.width == 0 ) || ( bb.height == 0 ) )
+ {
+ bb.x = 0;
+ bb.y = 0;
+ bb.width = imgSrc->width;
+ bb.height = imgSrc->height;
+ }
+
+ // get bounding box data and no with aspect ratio, the x and y can be corrupted
+ cvGetSubRect(imgSrc, &data, cvRect(bb.x, bb.y, bb.width, bb.height));
+ // create image with this data with width and height with aspect ratio 1
+ // then we get highest size betwen width and height of our bounding box
+ int size=(bb.width>bb.height)?bb.width:bb.height;
+ result=cvCreateImage( cvSize( size, size ), 8, 1 );
+ cvSet(result,CV_RGB(255,255,255),NULL);
+ // copy de data in center of image
+ int x=(int)floor((float)(size-bb.width)/2.0f);
+ int y=(int)floor((float)(size-bb.height)/2.0f);
+ cvGetSubRect(result, &dataA, cvRect(x,y,bb.width, bb.height));
+ cvCopy(&data, &dataA, NULL);
+ // scale result
+ scaledResult=cvCreateImage( cvSize( new_width, new_height ), 8, 1 );
+ cvResize(result, scaledResult, CV_INTER_NN);
+
+ // return processed data
+ return *scaledResult;
+
+}
+
+void pix_opencv_knear :: load_patterns(void)
+{
+ IplImage* src_image;
+ IplImage prs_image;
+ CvMat row,data;
+ char file[255];
+ int i=0,j;
+ CvMat row_header, *row1;
+
+ this->x_rsamples = 0;
+
+ for( j = 0; j< this->x_nsamples; j++)
+ {
+
+ // load fileath
+
+ if ( x_filepath[0] == '/' ){ // absolute path
+ sprintf(file,"%s/%03d.png",this->x_filepath, j);
+ } else { // relative path
+ std::string absolutePath = localPath + x_filepath;
+ sprintf(file,"%s/%03d.png",absolutePath.c_str(), j);
+ }
+ src_image = cvLoadImage(file,0);
+ if(!src_image)
+ {
+ post("pix_opencv_knear : error: couldn't load image %s\n", file);
+ continue;
+ }
+ if ( ( this->x_pwidth == -1 ) || ( this->x_pheight == -1 ) )
+ {
+ this->x_pwidth = src_image->width;
+ this->x_pheight = src_image->height;
+ // post( "pix_opencv_knear : loaded : %s (%dx%d)", file, src_image->width, src_image->height);
+ this->x_rsamples++;
+ }
+ else if ( ( src_image->width != this->x_pwidth ) || ( src_image->height != this->x_pheight ) )
+ {
+ post( "pix_opencv_knear : error : %s (%dx%d) : wrong size ( should be %dx%d )", file, src_image->width, src_image->height, this->x_pwidth, this->x_pheight);
+ continue;
+ }
+ else
+ {
+ // post( "pix_opencv_knear : loaded : %s (%dx%d)", file, src_image->width, src_image->height);
+ this->x_rsamples++;
+ }
+
+ // process file
+ prs_image = this->preprocessing(src_image, this->x_pwidth, this->x_pheight);
+ // post( "pix_opencv_knear : preprocessed : %s (%dx%d)", file, this->x_pwidth, this->x_pheight);
+
+ if ( ( this->trainData == NULL ) || ( this->trainClasses == NULL ))
+ {
+ this->trainData = cvCreateMat(this->x_nsamples, this->x_pwidth*this->x_pheight, CV_32FC1);
+ this->trainClasses = cvCreateMat(this->x_nsamples, 1, CV_32FC1);
+ }
+
+ // set class label
+ cvGetRow(this->trainClasses, &row, j);
+ cvSet(&row, cvRealScalar(i), NULL);
+ // set data
+ cvGetRow(this->trainData, &row, j);
+
+ IplImage* img = cvCreateImage( cvSize( this->x_pwidth, this->x_pheight ), IPL_DEPTH_32F, 1 );
+ // convert 8 bits image to 32 float image
+ cvConvertScale(&prs_image, img, 0.0039215, 0);
+
+ cvGetSubRect(img, &data, cvRect( 0, 0, this->x_pwidth, this->x_pheight) );
+
+ // convert data matrix sizexsize to vecor
+ row1 = cvReshape( &data, &row_header, 0, 1 );
+ cvCopy(row1, &row, NULL);
+ cvReleaseImage( &img );
+ }
+
+ // create the classifier
+ post( "pix_opencv_knear : loaded : %d samples from %s", this->x_rsamples, this->x_filepath);
+ if ( this->x_rsamples == this->x_nsamples )
+ {
+ this->knn=new CvKNearest( this->trainData, this->trainClasses, 0, false, this->x_nsamples );
+ this->x_nearest=cvCreateMat(1,this->x_nsamples,CV_32FC1);
+ this->x_dist=cvCreateMat(1,this->x_nsamples,CV_32FC1);
+ }
+}
+
+
+/////////////////////////////////////////////////////////
+// Constructor
+//
+/////////////////////////////////////////////////////////
+pix_opencv_knear :: pix_opencv_knear(t_symbol *path, t_floatarg nsamples)
+{
+ m_dataout = outlet_new(this->x_obj, &s_anything);
+
+ comp_xsize = 320;
+ comp_ysize = 240;
+
+ rgba = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 4 );
+ rgb = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 3 );
+ grey = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 1 );
+
+ x_filepath = ( char * ) getbytes( 1024 );
+ sprintf( x_filepath, "%s", path->s_name );
+ x_nsamples = (int)nsamples;
+
+ x_classify = 0;
+ x_pwidth = -1;
+ x_pheight = -1;
+
+ trainData = NULL;
+ trainClasses = NULL;
+
+ t_canvas* canvas = canvas_getcurrent();
+ localPath = std::string(canvas_getdir(canvas)->s_name) + "/";
+
+ try {
+ this->load_patterns();
+ } catch(...) {
+ error( "can't load patterns" );
+ return;
+ }
+}
+
+/////////////////////////////////////////////////////////
+// Destructor
+//
+/////////////////////////////////////////////////////////
+pix_opencv_knear :: ~pix_opencv_knear()
+{
+ // destroy cv structures
+ cvReleaseImage( &rgba );
+ cvReleaseImage( &rgb );
+ cvReleaseImage( &grey );
+ cvReleaseMat( &trainData );
+ cvReleaseMat( &trainClasses );
+
+}
+
+/////////////////////////////////////////////////////////
+// processImage
+//
+/////////////////////////////////////////////////////////
+void pix_opencv_knear :: processRGBAImage(imageStruct &image)
+{
+ int i;
+
+ if ((this->comp_xsize!=image.xsize)&&(this->comp_ysize!=image.ysize))
+ {
+
+ this->comp_xsize = image.xsize;
+ this->comp_ysize = image.ysize;
+
+ // destroy cv_images to clean memory
+ cvReleaseImage( &rgba );
+ cvReleaseImage( &rgb );
+ cvReleaseImage( &grey );
+
+ // create cv_images
+ this->rgba = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 4 );
+ this->rgb = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 3 );
+ this->grey = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 1 );
+
+ }
+
+ memcpy( rgba->imageData, image.data, image.xsize*image.ysize*4 );
+ cvCvtColor(rgba, grey, CV_BGRA2GRAY);
+
+ if ( this->x_classify )
+ {
+ IplImage prs_image;
+ CvMat row_header, *row1, odata;
+
+ // post( "pix_opencv_knear : size : (%dx%d)", this->x_pwidth, this->x_pheight);
+
+ // process file
+ prs_image = this->preprocessing(this->grey, this->x_pwidth, this->x_pheight);
+
+ //Set data
+ IplImage* img32 = cvCreateImage( cvSize( this->x_pwidth, this->x_pheight ), IPL_DEPTH_32F, 1 );
+ cvConvertScale(&prs_image, img32, 0.0039215, 0);
+ cvGetSubRect(img32, &odata, cvRect(0,0, this->x_pwidth, this->x_pheight));
+ row1 = cvReshape( &odata, &row_header, 0, 1 );
+
+ this->knn->find_nearest(row1,this->x_nsamples,0,0,this->x_nearest,this->x_dist);
+ for ( i=0; i<this->x_nsamples; i++ )
+ {
+ // post( "pix_opencv_knear : distance : %f", this->x_dist->data.fl[i] );
+ }
+ outlet_float(this->m_dataout, this->x_dist->data.fl[0]);
+
+ cvReleaseImage( &img32 );
+ this->x_classify = 0;
+ }
+
+ memcpy( image.data, rgba->imageData, image.xsize*image.ysize*4 );
+}
+
+void pix_opencv_knear :: processRGBImage(imageStruct &image)
+{
+ int i;
+
+ if ((this->comp_xsize!=image.xsize)&&(this->comp_ysize!=image.ysize))
+ {
+
+ this->comp_xsize = image.xsize;
+ this->comp_ysize = image.ysize;
+
+ // destroy cv_images to clean memory
+ cvReleaseImage( &rgba );
+ cvReleaseImage( &rgb );
+ cvReleaseImage( &grey );
+
+ // create cv_images
+ this->rgba = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 4 );
+ this->rgb = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 3 );
+ this->grey = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 1 );
+
+ }
+
+ memcpy( rgb->imageData, image.data, image.xsize*image.ysize*3 );
+ cvCvtColor(rgb, grey, CV_BGR2GRAY);
+
+ if ( this->x_classify )
+ {
+ IplImage prs_image;
+ CvMat row_header, *row1, odata;
+
+ // post( "pix_opencv_knear : size : (%dx%d)", this->x_pwidth, this->x_pheight);
+
+ // process file
+ prs_image = this->preprocessing(this->grey, this->x_pwidth, this->x_pheight);
+
+ //Set data
+ IplImage* img32 = cvCreateImage( cvSize( this->x_pwidth, this->x_pheight ), IPL_DEPTH_32F, 1 );
+ cvConvertScale(&prs_image, img32, 0.0039215, 0);
+ cvGetSubRect(img32, &odata, cvRect(0,0, this->x_pwidth, this->x_pheight));
+ row1 = cvReshape( &odata, &row_header, 0, 1 );
+
+ this->knn->find_nearest(row1,this->x_nsamples,0,0,this->x_nearest,this->x_dist);
+ for ( i=0; i<this->x_nsamples; i++ )
+ {
+ // post( "pix_opencv_knear : distance : %f", this->x_dist->data.fl[i] );
+ }
+ outlet_float(this->m_dataout, this->x_dist->data.fl[0]);
+
+ cvReleaseImage( &img32 );
+ this->x_classify = 0;
+ }
+
+ memcpy( image.data, rgb->imageData, image.xsize*image.ysize*3 );
+}
+
+void pix_opencv_knear :: processYUVImage(imageStruct &image)
+{
+ post( "pix_opencv_knear : yuv format not supported" );
+}
+
+void pix_opencv_knear :: processGrayImage(imageStruct &image)
+{
+ int i;
+
+ if ((this->comp_xsize!=image.xsize)&&(this->comp_ysize!=image.ysize))
+ {
+
+ this->comp_xsize = image.xsize;
+ this->comp_ysize = image.ysize;
+
+ // destroy cv_images to clean memory
+ cvReleaseImage( &rgba );
+ cvReleaseImage( &rgb );
+ cvReleaseImage( &grey );
+
+ // create cv_images
+ this->rgba = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 4 );
+ this->rgb = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 3 );
+ this->grey = cvCreateImage( cvSize(comp_xsize, comp_ysize), 8, 1 );
+
+ }
+
+ memcpy( grey->imageData, image.data, image.xsize*image.ysize*1 );
+
+ if ( this->x_classify )
+ {
+ IplImage prs_image;
+ CvMat row_header, *row1, odata;
+
+ // post( "pix_opencv_knear : size : (%dx%d)", this->x_pwidth, this->x_pheight);
+
+ // process file
+ prs_image = this->preprocessing(this->grey, this->x_pwidth, this->x_pheight);
+
+ //Set data
+ IplImage* img32 = cvCreateImage( cvSize( this->x_pwidth, this->x_pheight ), IPL_DEPTH_32F, 1 );
+ cvConvertScale(&prs_image, img32, 0.0039215, 0);
+ cvGetSubRect(img32, &odata, cvRect(0,0, this->x_pwidth, this->x_pheight));
+ row1 = cvReshape( &odata, &row_header, 0, 1 );
+
+ this->knn->find_nearest(row1,this->x_nsamples,0,0,this->x_nearest,this->x_dist);
+ for ( i=0; i<this->x_nsamples; i++ )
+ {
+ // post( "pix_opencv_knear : distance : %f", this->x_dist->data.fl[i] );
+ }
+ outlet_float(this->m_dataout, this->x_dist->data.fl[0]);
+
+ cvReleaseImage( &img32 );
+ this->x_classify = 0;
+ }
+
+ memcpy( image.data, grey->imageData, image.xsize*image.ysize*1 );
+}
+
+/////////////////////////////////////////////////////////
+// static member function
+//
+/////////////////////////////////////////////////////////
+void pix_opencv_knear :: obj_setupCallback(t_class *classPtr)
+{
+ class_addmethod(classPtr, (t_method)&pix_opencv_knear::bangMessCallback,
+ gensym("bang"), A_NULL);
+ class_addmethod(classPtr, (t_method)&pix_opencv_knear::loadMessCallback,
+ gensym("load"), A_SYMBOL, A_DEFFLOAT, A_NULL);
+}
+
+void pix_opencv_knear :: bangMessCallback(void *data)
+{
+ if ( GetMyClass(data)->trainData == NULL )
+ {
+ ::post( "pix_opencv_knear : no patterns loaded : cannot process" );
+ return;
+ }
+ GetMyClass(data)->x_classify=1;
+}
+
+void pix_opencv_knear :: loadMessCallback(void *data, t_symbol *path, t_floatarg nsamples)
+{
+ if ( (int) nsamples <= 0 )
+ {
+ ::post( "pix_opencv_knear : wrong number of samples : %d", nsamples );
+ return;
+ }
+ else
+ {
+ GetMyClass(data)->x_nsamples = (int)nsamples;
+ GetMyClass(data)->x_rsamples = 0;
+ cvReleaseMat( &GetMyClass(data)->trainData );
+ cvReleaseMat( &GetMyClass(data)->trainClasses );
+ GetMyClass(data)->trainData = NULL;
+ GetMyClass(data)->trainClasses = NULL;
+ }
+ strcpy( GetMyClass(data)->x_filepath, path->s_name );
+ GetMyClass(data)->load_patterns();
+}
generated by cgit v1.2.1 (git 2.18.0) at 2024-05-04 06:07:49 +0000