Is there a way to scale down with highest quality a font which is png image in opengl at startup? I tried gluScaleImage but there are many artefacts. Is there anything that uses lanczos or something like that? I don't want to write a shader or anything that does the scaling runtime.
This is based on an algorithm, I copied decades ago from the German c't Magazin, and still use it from time to time for similar issues like described by OP.
bool scaleDown(
const Image &imgSrc,
Image &imgDst,
int w, int h,
int align)
{
const int wSrc = imgSrc.w(), hSrc = imgSrc.h();
assert(w > 0 && w <= wSrc && h > 0 && h <= hSrc);
// compute scaling factors
const double sx = (double)wSrc / (double)w;
const double sy = (double)hSrc / (double)h;
const double sxy = sx * sy;
// prepare destination image
imgDst.resize(w, h, (w * 3 + align - 1) / align * align);
// cache some data
const uint8 *const dataSrc = imgSrc.data();
const int bPRSrc = imgSrc.bPR();
// perform scaling
for (int y = 0; y < h; ++y) {
const double yStart = sy * y;
const double yEnd = std::min(sy * (y + 1), (double)hSrc);
const int yStartInt = (int)yStart;
const int yEndInt = (int)yEnd - (yEndInt == yEnd);
const double tFrm = 1 + yStartInt - yStart, bFrm = yEnd - yEndInt;
for (int x = 0; x < w; ++x) {
const double xStart = sx * x;
const double xEnd = std::min(sx * (x + 1), (double)wSrc);
const int xStartInt = (int)xStart;
const int xEndInt = (int)xEnd - (xEndInt == xEnd);
double lFrm = 1 + xStartInt - xStart, rFrm = xEnd - xEndInt;
double pixel[3] = { 0.0, 0.0, 0.0 }; // values of target pixel
for (int i = yStartInt; i <= yEndInt; ++i) {
int jData = i * bPRSrc + xStartInt * 3;
for (int j = xStartInt; j <= xEndInt; ++j) {
double pixelAdd[3];
for (int k = 0; k < 3; ++k) {
pixelAdd[k] = (double)dataSrc[jData++] / sxy;
}
if (j == xStartInt) {
for (int k = 0; k < 3; ++k) pixelAdd[k] *= lFrm;
} else if (j == xEndInt) {
for (int k = 0; k < 3; ++k) pixelAdd[k] *= rFrm;
}
if (i == yStartInt) {
for (int k = 0; k < 3; ++k) pixelAdd[k] *= tFrm;
} else if (i == yEndInt) {
for (int k = 0; k < 3; ++k) pixelAdd[k] *= bFrm;
}
for (int k = 0; k < 3; ++k) pixel[k] += pixelAdd[k];
}
}
imgDst.setPixel(x, y,
(uint8)pixel[0], (uint8)pixel[1], (uint8)pixel[2]);
}
}
// done
return true;
}
If I got it right, this implements a bilinear interpolation.
I don't dare to call it a Minimal Complete Verifiable Example although this is what I intended to do.
The complete sample application:
A simplified class Image
image.h:
#ifndef IMAGE_H
#define IMAGE_H
#include <vector>
// convenience type for bytes
typedef unsigned char uint8;
// image helper class
class Image {
private: // variables:
int _w, _h; // image size
size_t _bPR; // bytes per row
std::vector<uint8> _data; // image data
public: // methods:
// constructor.
Image(): _w(0), _h(0), _bPR(0) { }
// destructor.
~Image() = default;
// copy constructor.
Image(const Image&) = delete; // = default; would work as well.
// copy assignment.
Image& operator=(const Image&) = delete; // = default; would work as well.
// returns width of image.
int w() const { return _w; }
// returns height of image.
int h() const { return _h; }
// returns bytes per row.
size_t bPR() const { return _bPR; }
// returns pointer to image data.
const uint8* data(
int y = 0) // row number
const {
return &_data[y * _bPR];
}
// returns data size (in bytes).
size_t size() const { return _data.size(); }
// clears image.
void clear();
// resizes image.
uint8* resize( // returns allocated buffer
int w, // image width
int h, // image height
int bPR); // bytes per row
// returns pixel.
int getPixel(
int x, // column
int y) // row
const;
// sets pixel.
void setPixel(
int x, // column
int y, // row
uint8 r, uint8 g, uint8 b);
// sets pixel.
void setPixel(
int x, // column
int y, // row
int value) // RGB value
{
setPixel(x, y, value & 0xff, value >> 8 & 0xff, value >> 16 & 0xff);
}
};
// helper functions:
inline uint8 getR(int value) { return value & 0xff; }
inline uint8 getG(int value) { return value >> 8 & 0xff; }
inline uint8 getB(int value) { return value >> 16 & 0xff; }
#endif // IMAGE_H
image.cc:
#include <cassert>
#include "image.h"
// clears image.
void Image::clear()
{
_data.clear(); _w = _h = _bPR = 0;
}
// allocates image data.
uint8* Image::resize( // returns allocated buffer
int w, // image width
int h, // image height
int bPR) // bits per row
{
assert(w >= 0 && 3 * w <= bPR);
assert(h >= 0);
_w = w; _h = h; _bPR = bPR;
const size_t size = h * bPR;
_data.resize(size);
return _data.data();
}
// returns pixel.
int Image::getPixel(
int x, // column
int y) // row
const {
assert(x >= 0 && x < _w);
assert(y >= 0 && y < _h);
const size_t offs = y * _bPR + 3 * x;
return _data[offs + 0]
| _data[offs + 1] << 8
| _data[offs + 2] << 16;
}
// sets pixel.
void Image::setPixel(
int x, // column
int y, // row
uint8 r, uint8 g, uint8 b) // R, G, B values
{
assert(x >= 0 && x < _w);
assert(y >= 0 && y < _h);
const size_t offs = y * _bPR + 3 * x;
_data[offs + 0] = r;
_data[offs + 1] = g;
_data[offs + 2] = b;
}
Image Scaling
imageScale.h:
#ifndef IMAGE_SCALE_H
#define IMAGE_SCALE_H
#include "image.h"
/* scales an image to a certain width and height.
*
* Note:
* imgSrc and imgDst may not be identical.
*/
bool scaleTo( // returns true if successful
const Image &imgSrc, // source image
Image &imgDst, // destination image
int w, int h, // destination width and height
int align = 4); // row alignment
/* scales an image about a certain horizontal/vertical scaling factor.
*
* Note:
* imgSrc and imgDst may not be identical.
*/
inline bool scaleXY( // returns true if successful
const Image &imgSrc, // source image
Image &imgDst, // destination image
double sX, // horizontal scaling factor (must be > 0 but not too large)
double sY, // vertical scaling factor (must be > 0 but not too large)
int align = 4) // row alignment
{
return sX > 0.0 && sY > 0.0
? scaleTo(imgSrc, imgDst,
(int)(sX * imgSrc.w()), (int)(sY * imgSrc.h()), align)
: false;
}
/* scales an image about a certain scaling factor.
*
* Note:
* imgSrc and imgDst may not be identical.
*/
inline bool scale( // returns true if successful
const Image &imgSrc, // source image
Image &imgDst, // destination image
double s, // scaling factor (must be > 0 but not too large)
int align = 4) // row alignment
{
return scaleXY(imgSrc, imgDst, s, s, align);
}
#endif // IMAGE_SCALE_H
imageScale.cc:
#include <cassert>
#include <algorithm>
#include "imageScale.h"
namespace {
template <typename VALUE>
VALUE clip(VALUE value, VALUE min, VALUE max)
{
return value < min ? min : value > max ? max : value;
}
bool scaleDown(
const Image &imgSrc,
Image &imgDst,
int w, int h,
int align)
{
const int wSrc = imgSrc.w(), hSrc = imgSrc.h();
assert(w > 0 && w <= wSrc && h > 0 && h <= hSrc);
// compute scaling factors
const double sx = (double)wSrc / (double)w;
const double sy = (double)hSrc / (double)h;
const double sxy = sx * sy;
// prepare destination image
imgDst.resize(w, h, (w * 3 + align - 1) / align * align);
// cache some data
const uint8 *const dataSrc = imgSrc.data();
const int bPRSrc = imgSrc.bPR();
// perform scaling
for (int y = 0; y < h; ++y) {
const double yStart = sy * y;
const double yEnd = std::min(sy * (y + 1), (double)hSrc);
const int yStartInt = (int)yStart;
const int yEndInt = (int)yEnd - (yEndInt == yEnd);
const double tFrm = 1 + yStartInt - yStart, bFrm = yEnd - yEndInt;
for (int x = 0; x < w; ++x) {
const double xStart = sx * x;
const double xEnd = std::min(sx * (x + 1), (double)wSrc);
const int xStartInt = (int)xStart;
const int xEndInt = (int)xEnd - (xEndInt == xEnd);
double lFrm = 1 + xStartInt - xStart, rFrm = xEnd - xEndInt;
double pixel[3] = { 0.0, 0.0, 0.0 }; // values of target pixel
for (int i = yStartInt; i <= yEndInt; ++i) {
int jData = i * bPRSrc + xStartInt * 3;
for (int j = xStartInt; j <= xEndInt; ++j) {
double pixelAdd[3];
for (int k = 0; k < 3; ++k) {
pixelAdd[k] = (double)dataSrc[jData++] / sxy;
}
if (j == xStartInt) {
for (int k = 0; k < 3; ++k) pixelAdd[k] *= lFrm;
} else if (j == xEndInt) {
for (int k = 0; k < 3; ++k) pixelAdd[k] *= rFrm;
}
if (i == yStartInt) {
for (int k = 0; k < 3; ++k) pixelAdd[k] *= tFrm;
} else if (i == yEndInt) {
for (int k = 0; k < 3; ++k) pixelAdd[k] *= bFrm;
}
for (int k = 0; k < 3; ++k) pixel[k] += pixelAdd[k];
}
}
imgDst.setPixel(x, y,
(uint8)pixel[0], (uint8)pixel[1], (uint8)pixel[2]);
}
}
// done
return true;
}
bool scaleUp(
const Image &imgSrc,
Image &imgDst,
int w, int h,
int align)
{
const int wSrc = imgSrc.w(), hSrc = imgSrc.h();
assert(w && w >= wSrc && h && h >= hSrc);
// compute scaling factors
const double sx = (double)wSrc / (double)w;
const double sy = (double)hSrc / (double)h;
// prepare destination image
imgDst.resize(w, h, (w * 3 + align - 1) / align * align);
// cache some data
const uint8 *const dataSrc = imgSrc.data();
const int bPRSrc = imgSrc.bPR();
// perform scaling
for (int y = 0; y < h; ++y) {
const double yStart = sy * y;
const double yEnd = std::min(sy * (y + 1), (double)hSrc - 1);
const int yStartInt = (int)yStart;
const int yEndInt = (int)yEnd;
if (yStartInt < yEndInt) {
const double bFract = clip((double)((yEnd - yEndInt) / sy), 0.0, 1.0);
const double tFract = 1.0 - bFract;
for (int x = 0; x < w; ++x) {
const double xStart = sx * x;
const double xEnd = std::min(sx * (x + 1), (double)wSrc - 1);
const int xStartInt = (int)xStart, xEndInt = (int)xEnd;
double pixel[4];
if (xStartInt < xEndInt) {
const double rFract
= clip((double)((xEnd - xEndInt) / sx), 0.0, 1.0);
const double lFract = 1.0 - rFract;
int jData = yStartInt * bPRSrc + xStartInt * 3;
for (int k = 0; k < 3; ++k) {
pixel[k] = tFract * lFract * dataSrc[jData++];
}
for (int k = 0; k < 3; ++k) {
pixel[k] += tFract * rFract * dataSrc[jData++];
}
jData = yEndInt * bPRSrc + xStartInt * 3;
for (int k = 0; k < 3; ++k) {
pixel[k] += bFract * lFract *dataSrc[jData++];
}
for (int k = 0; k < 3; ++k) {
pixel[k] += bFract * rFract *dataSrc[jData++];
}
} else {
int jData = yStartInt * bPRSrc + xStartInt * 3;
for (int k = 0; k < 3; ++k) {
pixel[k] = tFract * dataSrc[jData++];
}
jData = yEndInt * bPRSrc + xStartInt * 3;
for (int k = 0; k < 3; ++k) {
pixel[k] += bFract * dataSrc[jData++];
}
}
imgDst.setPixel(x, y,
(uint8)pixel[0], (uint8)pixel[1], (uint8)pixel[2]);
}
} else {
for (int x = 0; x < w; ++x) {
const double xStart = sx * x;
const double xEnd = std::min(sx * (x + 1), (double)wSrc - 1);
const int xStartInt = (int)xStart, xEndInt = (int)xEnd;
double pixel[3];
if (xStartInt < xEndInt) {
const double rFract
= clip((double)((xEnd - xEndInt) / sx), 0.0, 1.0);
const double lFract = 1.0 - rFract;
int jData = yStartInt * bPRSrc + xStartInt * 3;
for (int k = 0; k < 3; ++k) {
pixel[k] = lFract * dataSrc[jData++];
}
for (int k = 0; k < 3; ++k) {
pixel[k] += rFract * dataSrc[jData++];
}
} else {
int jData = yStartInt * bPRSrc + xStartInt * 3;
for (int k = 0; k < 3; ++k) pixel[k] = dataSrc[jData++];
}
imgDst.setPixel(x, y,
(uint8)pixel[0], (uint8)pixel[1], (uint8)pixel[2]);
}
}
}
// done
return true;
}
} // namespace
bool scaleTo(const Image &imgSrc, Image &imgDst, int w, int h, int align)
{
Image imgTmp;
return w <= 0 || h <= 0 ? false
: w >= imgSrc.w() && h >= imgSrc.h()
? scaleUp(imgSrc, imgDst, w, h, align)
: w <= imgSrc.w() && h <= imgSrc.h()
? scaleDown(imgSrc, imgDst, w, h, align)
: w >= imgSrc.w()
? scaleUp(imgSrc, imgTmp, w, imgSrc.h(), 1)
&& scaleDown(imgTmp, imgDst, w, h, align)
: scaleDown(imgSrc, imgTmp, w, imgSrc.h(), 1)
&& scaleUp(imgTmp, imgDst, w, h, align);
}
PPM file IO
imagePPM.h:
#ifndef IMAGE_PPM_H
#define IMAGE_PPM_H
#include <iostream>
#include "image.h"
// reads a binary PPM file.
bool readPPM( // returns true if successful
std::istream &in, // input stream (must be opened with std::ios::binary)
Image &img, // image to read into
int align = 4); // row alignment
// writes binary PPM file.
bool writePPM( // returns true if successful
std::ostream &out, // output stream (must be opened with std::ios::binary)
const Image &img); // image to write from
#endif // IMAGE_PPM_H
imagePPM.cc:
#include <sstream>
#include <string>
#include "imagePPM.h"
// reads a binary PPM file.
bool readPPM( // returns true if successful
std::istream &in, // input stream (must be opened with std::ios::binary)
Image &img, // image to read into
int align) // row alignment
{
// parse header
std::string buffer;
if (!getline(in, buffer)) return false;
if (buffer != "P6") {
std::cerr << "Wrong header! 'P6' expected.\n";
return false;
}
int w = 0, h = 0, t = 0;
for (int i = 0; i < 3;) {
if (!getline(in, buffer)) return false;
if (buffer.empty()) continue; // skip empty lines
if (buffer[0] == '#') continue; // skip comments
std::istringstream str(buffer);
switch (i) {
case 0:
if (!(str >> w)) continue;
++i;
case 1:
if (!(str >> h)) continue;
++i;
case 2:
if (!(str >> t)) continue;
++i;
}
}
if (t != 255) {
std::cerr << "Unsupported format! t = 255 expected.\n";
return false;
}
// allocate image buffer
uint8 *data = img.resize(w, h, (w * 3 + align - 1) / align * align);
// read data
for (int i = 0; i < h; ++i) {
if (!in.read((char*)data, 3 * img.w())) return false;
data += img.bPR();
}
// done
return true;
}
// writes binary PPM file.
bool writePPM( // returns true if successful
std::ostream &out, // output stream (must be opened with std::ios::binary)
const Image &img) // image to write from
{
// write header
if (!(out << "P6\n" << img.w() << ' ' << img.h() << " 255\n")) return false;
// write image data
for (size_t y = 0; y < img.h(); ++y) {
const uint8 *const data = img.data(y);
if (!out.write((const char*)data, 3 * img.w())) return false;
}
// done
return true;
}
The main application
scaleRGBImg.cc:
#include <iostream>
#include <fstream>
#include <string>
#include "image.h"
#include "imagePPM.h"
#include "imageScale.h"
int main(int argc, char **argv)
{
// read command line arguments
if (argc <= 3) {
std::cerr << "Missing arguments!\n";
std::cout
<< "Usage:\n"
<< " scaleRGBImg IN_FILE SCALE OUT_FILE\n";
return 1;
}
const std::string inFile = argv[1];
char *end;
const double s = std::strtod(argv[2], &end);
if (end == argv[2] || *end != '\0') {
std::cerr << "Invalid scale factor '" << argv[2] << "'!\n";
return 1;
}
if (s <= 0.0) {
std::cerr << "Invalid scale factor " << s << "!\n";
return 1;
}
const std::string outFile = argv[3];
// read image
Image imgSrc;
{ std::ifstream fIn(inFile.c_str(), std::ios::binary);
if (!readPPM(fIn, imgSrc)) {
std::cerr << "Reading '" << inFile << "' failed!\n";
return 1;
}
}
// scale image
Image imgDst;
if (!scale(imgSrc, imgDst, s)) {
std::cerr << "Scaling failed!\n";
return 1;
}
// write image
{ std::ofstream fOut(outFile.c_str(), std::ios::binary);
if (!writePPM(fOut, imgDst) || (fOut.close(), !fOut.good())) {
std::cerr << "Writing '" << outFile << "' failed!\n";
return 1;
}
}
// done
return 0;
}
Test
Compiled in cygwin64:
$ g++ -std=c++11 -o scaleRGBImg scaleRGBImg.cc image.cc imagePPM.cc imageScale.cc
$
A sample image test.ppm for a test – converted to PPM in GIMP:
Test with the sample image:
$ for I in 0.8 0.6 0.4 0.2 ; do echo ./scaleRGBImg test.ppm $I test.$I.ppm ; done
./scaleRGBImg test.ppm 0.8 test.0.8.ppm
./scaleRGBImg test.ppm 0.6 test.0.6.ppm
./scaleRGBImg test.ppm 0.4 test.0.4.ppm
./scaleRGBImg test.ppm 0.2 test.0.2.ppm
$ for I in 0.8 0.6 0.4 0.2 ; do ./scaleRGBImg test.ppm $I test.$I.ppm ; done
$
This is what came out:
test.0.8.ppm:
test.0.6.ppm:
test.0.4.ppm:
test.0.2.ppm:
I am new to kinect project
And I am implementing a depth threshold when distance is greater than 400mm
for (UINT y = 0; y < pImg->rows; ++y)
{
// Get row pointers for Mats
const USHORT* pDepthRow = depth->ptr<USHORT>(y);
for (UINT x = 0; x < pImg->cols; ++x)
{
USHORT raw_depth = pDepthRow[x];
SHORT realDepth = NuiDepthPixelToDepth(raw_depth);
// If depth value is valid, convert and copy it
if (raw_depth != 65535)
{
if(realDepth >400 ) //greater than 400mm
{
pImg->at<Vec4b>(y,x)[0] = 255;
pImg->at<Vec4b>(y,x)[1] = 255;
pImg->at<Vec4b>(y,x)[2] = 255;
pImg->at<Vec4b>(y,x)[3] = 255;
}
else
{
pImg->at<Vec4b>(y,x)[0] = 0;
pImg->at<Vec4b>(y,x)[1] = 0;
pImg->at<Vec4b>(y,x)[2] = 0;
pImg->at<Vec4b>(y,x)[3] = 0;
}
}
}
It seems get the correct result but reduces the frame rate massively.
When I want to get rid of the loop by using the cv::inRange, but this function only support 8U1C when the raw depth is 16U.
So what else can I use to segment the depth according to the real distance?
Try to improve performance by storing a reference to the pixel.
Change this:
if (realDepth > 400) //greater than 400mm
{
pImg->at<Vec4b>(y,x)[0] = 255;
pImg->at<Vec4b>(y,x)[1] = 255;
pImg->at<Vec4b>(y,x)[2] = 255;
pImg->at<Vec4b>(y,x)[3] = 255;
}
else
{
pImg->at<Vec4b>(y,x)[0] = 0;
pImg->at<Vec4b>(y,x)[1] = 0;
pImg->at<Vec4b>(y,x)[2] = 0;
pImg->at<Vec4b>(y,x)[3] = 0;
}
To this:
(I don´t know what T is because I dont know what pImg is.
T should be equal to the return value of the at method. I assume it is Vec4b.)
T& pixel = pImg->at<Vec4b>(y, x); // probably Vec4b& pixel = ..
if (realDepth > 400) //greater than 400mm
{
pixel[0] = 255;
pixel[1] = 255;
pixel[2] = 255;
pixel[3] = 255;
}
else
{
pixel[0] = 0;
pixel[1] = 0;
pixel[2] = 0;
pixel[3] = 0;
}
I'm attempting to convert a MATLAB .mat file to openCV MAT and then applying several masks to those files. I am building from cvmatio source code. I am receiving the following error:
OpenCV Error: Assertion failed (A.size == arrays[i0]->size) in init,
file
/home/derek/Documents/Libraries/opencv-3.0.0-beta/modules/core/src/matrix.cpp,
line 4279 terminate called after throwing an instance of
'cv::Exception' what():
/home/derek/Documents/Libraries/opencv-3.0.0-beta/modules/core/src/matrix.cpp:4279:
error: (-215) A.size == arrays[i0]->size in function init
Here is the source file I've written. It occurs at the line with MixChannels. Note that SrcImage is a 3 channel Mat. lower and upper are the threshold values in an array who's length is equal to the number of channels.
/*
* Mask.cpp
*
* Created on: Mar 16, 2015
* Author: derek
*/
#include <cv.h>
#include <highgui.h>
#include "imgcodecs.hpp"
#include "highgui.hpp"
#include "imgproc.hpp"
using namespace cv;
Mat Mask(Mat SrcImage, double lower[], double upper[]){
int height=SrcImage.rows;
int width=SrcImage.cols;
int depth=SrcImage.depth();
Mat B2d = Mat::ones(height, width,depth);
Mat out(height, width, depth);
Mat outL(height, width, depth);
Mat outU(height,width, depth);
for (int i=1; i< SrcImage.channels(); i=i+1){
int from_to[]={i,1};
mixChannels(&SrcImage, 3, &out, 1, from_to, 1 );
threshold(out, outL, lower[i], 1, THRESH_BINARY);
threshold(out, outU, upper[i], 1, THRESH_BINARY);
bitwise_and(B2d, outL, B2d);
bitwise_and(B2d, outU, B2d);
}
return B2d;
}
Also, here is an excerpt of the actual CV_Assertion error location. As indicated in the error, it occurs at "(A.size == arrays[i0]->size)".
void NAryMatIterator::init(const Mat** _arrays, Mat* _planes, uchar** _ptrs, int _narrays)
{
CV_Assert( _arrays && (_ptrs || _planes) );
int i, j, d1=0, i0 = -1, d = -1;
arrays = _arrays;
ptrs = _ptrs;
planes = _planes;
narrays = _narrays;
nplanes = 0;
size = 0;
if( narrays < 0 )
{
for( i = 0; _arrays[i] != 0; i++ )
;
narrays = i;
CV_Assert(narrays <= 1000);
}
iterdepth = 0;
for( i = 0; i < narrays; i++ )
{
CV_Assert(arrays[i] != 0);
const Mat& A = *arrays[i];
if( ptrs )
ptrs[i] = A.data;
if( !A.data )
continue;
if( i0 < 0 )
{
i0 = i;
d = A.dims;
// find the first dimensionality which is different from 1;
// in any of the arrays the first "d1" step do not affect the continuity
for( d1 = 0; d1 < d; d1++ )
if( A.size[d1] > 1 )
break;
}
else
CV_Assert( A.size == arrays[i0]->size );
if( !A.isContinuous() )
{
CV_Assert( A.step[d-1] == A.elemSize() );
for( j = d-1; j > d1; j-- )
if( A.step[j]*A.size[j] < A.step[j-1] )
break;
iterdepth = std::max(iterdepth, j);
}
}
if( i0 >= 0 )
{
size = arrays[i0]->size[d-1];
for( j = d-1; j > iterdepth; j-- )
{
int64 total1 = (int64)size*arrays[i0]->size[j-1];
if( total1 != (int)total1 )
break;
size = (int)total1;
}
iterdepth = j;
if( iterdepth == d1 )
iterdepth = 0;
nplanes = 1;
for( j = iterdepth-1; j >= 0; j-- )
nplanes *= arrays[i0]->size[j];
}
else
iterdepth = 0;
idx = 0;
if( !planes )
return;
for( i = 0; i < narrays; i++ )
{
CV_Assert(arrays[i] != 0);
const Mat& A = *arrays[i];
if( !A.data )
{
planes[i] = Mat();
continue;
}
planes[i] = Mat(1, (int)size, A.type(), A.data);
}
}
Well it's obviously too late of an answer, but here is the reason why your code failed:
Since your SrcImage is a single Mat with multiple channels, you should'we written:
mixChannels(&SrcImage, 1, &out, 1, from_to, 1 );
(The assert error was related to this, since mixChannels expected 3 Mats, which is 3 times bigger than your Mat.)
Also opencv MixChannels labels channels from 0, not sure if the i=1 was intended, or just a typo.
Cheers!
here is my matlab code:
imageData = imageData ./ toolbox.c3d.p.tprctile(imageData(xy),99.2);
imageData(imageData>1) = 1;
here is my openCV/c++ code, the matrix dst is an openCV matrix
cv::Mat dst
std::vector<float> result;
for (std::vector<int>::iterator it = index.begin() ; it != index.end(); ++it)
{
int ind = *it;
float temp = dst.at<float>(ind - 1);
result.push_back(temp);
}
float divider = tprctile(result,99.2);
dst = dst/ divider;
utility function for percentile
float Utils::tprctile(std::vector<float> channel, double pt)
{
std::sort(channel.begin(),channel.end());
int ptInd = Utilities::MatlabRound (pt/100 * channel.size() );
return channel[ptInd];
// Matlab code
// function val = tprctile(data, pt)
// data = sort(data);
// ptInd = round( pt/100 * length(data) );
// val = data(ptInd);
}
my question is regarding imageData(imageData>1) = 1
what is the most efficient way to implement this function - i can of course iterate through dst like I did. is there a better way?
What you want is to truncate the image with cv::threshold.
The following should do what you require:
cv::threshold(dst, dst, 1, 1, CV_THRESH_TRUNC);
This truncates all values above 1 and stores the result in dst.
http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html?highlight=threshold#threshold
this is what i'm doing at the moment
int matrixSize = dst.rows *dst.cols;
cv::MatConstIterator_<float> it = dst.begin<float>(), it_end = dst.end<float>();
for(int i = 0 ; i < matrixSize ; ++i, ++it)
{
float value = *it;
if(value > 1.0)
{
dst.at<float>(i) = 1.0;
}
}
So I'm trying to erode a binary matrix.
I create the matrix using this code:
cv::Mat tmp = cv::Mat::zeros( IMG->width, IMG->height, CV_8U );
for( auto i = 0 ; i < IMG->width ; i++)
{
for ( auto j = 0 ; j < IMG->height ; j++)
{
if( cv::pointPolygonTest(cv::Mat(contour),cv::Point(i,j),true) < 0 )
{
tmp.at<double>(i,j) = 255;
}
}
}
Here is the source picture I'm using:
And this what I get with my loop (it's the tmp matrix):
So after I'm trying to erode the picture using this code:
int erosion_elem = 1;
int erosion_size = 8;
int erosion_type;
if( erosion_elem == 0 ){ erosion_type = MORPH_RECT; }
else if( erosion_elem == 1 ){ erosion_type = MORPH_CROSS; }
else if( erosion_elem == 2) { erosion_type = MORPH_ELLIPSE; }
Mat element = getStructuringElement( erosion_type,
Size( 2*erosion_size + 1, 2*erosion_size+1 ),
Point( erosion_size, erosion_size ) );
/// Apply the erosion operation
erode( binary, erosion_dst, element );`
So it compiles well but I get an exception on this line:
erode( binary, erosion_dst, element );`
It says it's an unsupported data type.
Does anyone have an idea why do I get this exception?
I tried to change the data type of the matrix tmp but I have the same error.
Thanks for your help !
Your binary image pixels are stored as unsigned char (CV_8U -> on 8bits -> 1 byte),
you should store your pixels' value as unsigned char too
cv::Mat tmp = cv::Mat::zeros( IMG->width, IMG->height, CV_8U );
for( auto i = 0 ; i < IMG->width ; i++)
{
for ( auto j = 0 ; j < IMG->height ; j++)
{
if( cv::pointPolygonTest(cv::Mat(contour),cv::Point(i,j),true) < 0 )
{
tmp.at<unsigned char>(i,j) = 255;
}
}
}
(made answer from comment)