ColorChannel::ColorChannel(const cv::Mat& Image)
{
// cv::imshow("To Convert", Image);
// cv::waitKey(0);
// Should check on width and height compatible with shrinking ...
//Convert from bgr to rgb
cv::Mat I_rgbO = Image.clone();
cv::Mat I_rgb;
cv::cvtColor(I_rgbO, I_rgb, CV_BGR2RGB);
//Convert to float-image
cv::Mat doubleImage;
I_rgb.convertTo(doubleImage, CV_32FC3, 1 / 255.0);
float* MImage = Convert_ToMatlab(doubleImage, 1.0f);
//r is radius
int r = 1;
float RR = 12.0 / (r * (r + 2)) - 2;
float* rgbImage = rgbConvert(MImage, Image.rows * Image.cols, Image.channels(), 2, 1.0f);
this->setColorSpace("luv");
float* rgbImage_smooth = (float*)malloc(sizeof(float) * Image.cols * Image.rows * I_rgb.channels());
// Last argument was 1 for Inria-model, is 0 for CalltechModel
convTri1(rgbImage, rgbImage_smooth, Image.rows, Image.cols, Image.channels(), RR, 1);
free(MImage);
free(rgbImage);
setChanneldata(rgbImage_smooth, Image.cols, Image.rows, Image.channels());
}
pyrOutput* chnsPyramid(float *image, pyrInput *input){
/*
* Declaring variables
*/
float *I;
int height = input->sz[0],
width = input->sz[1],
heightO = input->sz[0],
widthO = input->sz[1],
channels = input->sz[2];
int heightOriginal = height, widthOriginal = width;
int misalign = 1;
int sOfF = sizeof(float);
/*
* Get default parameters pPyramid
*/
if ( !input->complete ){
if(input->nApprox<0)
input->nApprox = input->nPerOct - 1;
input->pchns->pGradHist->binSize = input->shrink;
input->pad[0] = round(input->pad[0]/input->shrink) * input->shrink;
input->pad[1] = round(input->pad[1]/input->shrink) * input->shrink;
input->minDs[0] = max(input->minDs[0], input->shrink * 4);
input->minDs[1] = max(input->minDs[1], input->shrink * 4);
input->complete = true;
}
/*
* Convert I to appropriate color space (or simply normalize)
*/
int cs = input->pchns->pColor->colorSpace;
I = rgbConvert(image, height*width, channels, cs, 1.0f);
input->pchns->pColor->colorSpace = orig;
/*
* Get scales at which to compute features and list of real/approx scales
*/
float *scales = 0;
float *scaleshw = 0;
int nScales = getScales(scales, scaleshw, input->nPerOct, input->nOctUp,
input->minDs, input->shrink, input->sz);
//TODO :: WARNING :: This was done in the Dollar's Code
int isRMax;
if(true)
isRMax = 0;
else
isRMax = 0 + input->nOctUp * input->nPerOct;
//TODO :: WARNING :: END
int *isR, *isA, *isN;
//isR Vector Allocation
int countIsR = 0;
for ( int i = isRMax; i < nScales; i += (input->nApprox + 1) )
countIsR++;
isR = new int[countIsR];
for ( int i = isRMax, j = 0; i < nScales; j++, i += (input->nApprox + 1) )
isR[j] = i;
//isA and isN Vector Allocation
int countIsA = nScales - countIsR;
int countIsN = nScales;
isA = new int[countIsA];
isN = new int[countIsN];
for ( int i = 0, auxI = 0; i < nScales; i++){
bool ok = true;
for (int j = 0; j < countIsR; j++)
if(i == isR[j]){
ok = false;
break;
}
if (ok){
isA[auxI] = i;
auxI++;
}
isN[i] = i;
}
int *auxIsJ;
auxIsJ = new int[countIsR + 1];
auxIsJ[0] = 0;
auxIsJ[countIsR] = nScales;
for (int i = 0; i < countIsR - 1; i++)
auxIsJ[i+1] = floor((isR[i] + 1 + isR[i+1] + 1) / 2);
// " +1 " because we are in c++ and the vector already assumes the first
// element to be index 0.
for (int i = 0; i < countIsR; i++){
int minJ = auxIsJ[i];
int maxJ = auxIsJ[i+1];
for (int j = minJ; j < maxJ; j++)
isN[j] = isR[i];
}
/*
* Compute image pyramid [real scales]
*/
int nTypes = 0;
imgWrap ***data = (imgWrap ***) wrCalloc(nScales, sizeof(imgWrap**));
int shrink = input->shrink;
float shr[3] = { 0, 0, 0};
for (int it = 0, i = isR[0]; it < countIsR; it++, i=isR[it]){
float scale = scales[i];
int newHeight = round((float) heightO * (float) scale /
(float) shrink) * shrink;
int newWidth = round((float) widthO * (float) scale /
(float) shrink) * shrink;
float *I1;
if ( height == newHeight && width == newWidth){
//TODO :: WARNING :: Should I copy it over?
I1 = (float*) wrCalloc(height*width*channels + misalign,
sOfF) + misalign;
int lengthArray = height*width*channels;
for (int j = 0; j < lengthArray; j++)
I1[j] = I[j];
}else{
I1 = (float*) wrCalloc(newHeight*newWidth*channels + misalign,
sOfF) + misalign;
//TODO :: WARNING :: Hardcoded value :: 1.f
resample(I, I1, height, newHeight, width, newWidth, channels, 1.f);
}
if (scale == 0.5f && (input->nApprox > 0 || input->nPerOct == 1)){
//TODO :: WARNING :: Should I free "I"?
// I replace old I with new I1, as I reduced the image to half size
free(I);
I = I1;
height = newHeight;
width = newWidth;
}
//TODO :: WARNING :: Hardcoded value :: downsample
float *I2 = 0;
int downsample = 1;
convTriAux(I1, I2, misalign, newHeight, newWidth, channels,
input->smoothIm, downsample
);
/*
* Channels Compute for this isR[i] scale
*/
infoOut *chns = chnsCompute(I2, newHeight, newWidth, channels,
input->pchns
);
imgWrap **data1 = chns->data;
wrFree(I2-misalign);
nTypes = chns->nTypes;
if (i == isR[0]){
/*
* This is checking the size of each transformation. By design only
* the H channel will have the correct dimensions.
*/
for (int j = 0; j < nTypes; j++){
shr[j] = data1[j]->height;
shr[j] = newHeight / shr[j];
if (shr[j] > shrink || (int)shr[j] % 1 > 0){
cout << "Something went wrong with the shrinking."
<< endl << "Source code line: " << __FILE__ << " @ "
<< __LINE__ << endl;
return NULL; //This should never happen
}
shr[j]=shr[j]/shrink;
}
}
for(int j = 0; j < nTypes; j++){
if (shr[j] == 1)
continue;
int nH = newHeight*shr[j],
nW = newWidth*shr[j],
chnsTransform = data1[j]->channels;
float *chnTypeData = (float*) wrCalloc(nH*nW*channels + misalign,
sOfF) + misalign;
//TODO :: WARNING :: Hardcoded value :: 1.f
resample(data1[j]->image, chnTypeData, newHeight, nH, newWidth, nW,
chnsTransform, 1.f
);
data1[j]->height = nH;
data1[j]->width = nW;
wrFree(data1[j]->image - misalign);
data1[j]->image = chnTypeData;
}
data[i] = data1;
}
// In case I changed it when scale = 0.5f
height = heightO;
width = widthO;
/*
* If lambdas not specified compute image specific lambdas
*/
int nApprox = input->nApprox;
float *lambdas = input->lambdas;
if ( nApprox > 0 && !lambdas){
int nOctUp = input->nOctUp;
int nPerOct = input->nPerOct;
//TODO :: WARNING :: Yet again I start at 0.
// The is Vector :: is=1 + nOctUp*nPerOct:nApprox+1:nScales;
int countIs = 0;
int *isTemp = new int[nScales];
for (int i = nOctUp*nPerOct; i < nScales; i += nApprox + 1){
isTemp[countIs] = i;
countIs++;
}
if (countIs > 2){
isTemp[0] = isTemp[1];
isTemp[1] = isTemp[2];
}else{
cout << "Couldn't calculate lambdas. Not enough scales to use."
<< endl << "Source code line: " << __FILE__ << " @ "
<< __LINE__ << endl;
return NULL;
}
float *f0 = new float[nTypes];
float *f1 = new float[nTypes];
imgWrap **d0 = data[isTemp[0]];
imgWrap **d1 = data[isTemp[1]];
for (int i = 0; i < nTypes; i++){
float numElem = (float)
(d0[i]->width * d0[i]->height * d0[i]->channels);
float sumElem = 0.f;
for (int j = 0; j < numElem; j++)
sumElem += d0[i]->image[j];
f0[i] = sumElem / numElem;
}
for (int i = 0; i < nTypes; i++){
float numElem = (float)
(d1[i]->width * d1[i]->height * d1[i]->channels);
float sumElem = 0.f;
for (int j = 0; j < numElem; j++)
sumElem += d1[i]->image[j];
f1[i] = sumElem / numElem;
}
lambdas = new float[nTypes];
float lambdaValue = log2(scales[isTemp[0]] / scales[isTemp[1]]);
for (int i = 0; i < nTypes; i++)
lambdas[i] = -log2(f0[i] / f1[i]) / lambdaValue;
}
/*
* Compute image pyramid [approximated scales]
*/
shrink = input->shrink;
for (int it = 0, i = isA[0]; it < countIsA; it++, i=isA[it]){
int iR = isN[i];
float scale = scales[i];
//TODO :: WARNING :: The value height may have been modified to half of
// it, hence using heightOriginal (width)
int newHeight = round((float) heightOriginal * (float) scale /
(float) shrink);
int newWidth = round((float) widthOriginal * (float) scale /
(float) shrink);
float scaleRatio = (scale / scales[iR]);
float *rs = new float[nTypes];
for (int j = 0; j < nTypes; j++)
rs[j] = pow(scaleRatio, -lambdas[j] );
imgWrap **dataImgA = (imgWrap **) wrCalloc(nTypes, sizeof(imgWrap*));
imgWrap **dataImgR = data[iR];
for (int j = 0; j < nTypes; j++){
int ijChannels = dataImgR[j]->channels;
float *isAimage = (float*) wrCalloc(newHeight*newWidth*ijChannels +
misalign, sOfF) + misalign;
//TODO :: WARNING :: Hardcoded value
resample(dataImgR[j]->image, isAimage, dataImgR[j]->height,
newHeight, dataImgR[j]->width, newWidth, ijChannels, rs[j]);
dataImgA[j] = new imgWrap(isAimage, newWidth, newHeight,ijChannels);
}
data[i] = dataImgA;
delete [] rs;
}
/*
* Smooth channels, optionally pad and concatenate channels
*/
int downSample = 1; // WARNING : This is the default by dollar
int s = downSample;
for (int i = 0; i < nScales; i++){
for (int j = 0; j < nTypes; j++){
float *S;
int height = data[i][j]->height;
int width = data[i][j]->width;
int channel = data[i][j]->channels;
/*
* Smoothing Channels
*/
convTriAux(data[i][j]->image, S, misalign, height, width, channel,
input->smoothChns, s
);
wrFree(data[i][j]->image - misalign);
/*
* Padding according to the scale. Then change the shrink value.
*/
int padTB = input->pad[0] / shrink,
padLR = input->pad[1] / shrink;
if (padTB > 0 || padLR > 0){
int newHeight = height + padTB * 2;
int newWidth = width + padLR * 2;
float *P = (float*) wrCalloc(newHeight*newWidth*channel +
misalign, sOfF) + misalign;
imPad(S, P, height, width, channel, padTB, padTB, padLR, padLR,
padvalue, 0.f
);
wrFree(S - misalign);
data[i][j]->height = newHeight;
data[i][j]->width = newWidth;
S = P;
}
data[i][j]->image = S;
}
}
/*
* Concatenate.
*/
int totalChannels = 0;
for (int j = 0; j < nTypes; j++)
totalChannels += data[0][j]->channels;
if(input->concat){
int chnsArr[nTypes];
for (int j = 0; j < nTypes; j++)
chnsArr[j] = data[0][j]->channels;
for (int i = 0; i < nScales; i++){
int height = data[i][0]->height;
int width = data[i][0]->width;
float *imgC = (float*) wrCalloc(height*width*totalChannels +
misalign, sOfF) + misalign;
int totalSize = 0;
for (int j = 0; j < nTypes; j++){
float *imgO = data[i][j]->image;
copy(imgO, imgO + height*width*chnsArr[j], imgC + totalSize);
totalSize += height*width*chnsArr[j];
}
for (int j=1; j < nTypes; j++){
wrFree(data[i][j]->image - misalign);
wrFree(data[i][j]);
}
wrFree(data[i][0]->image - misalign);
data[i][0]->image = imgC;
data[i][0]->channels = totalChannels;
}
}
/*
* Create output struct
*/
pyrOutput *output = new pyrOutput();
output->input = input;
output->chnsPerScale = data;
output->nScales = nScales;
output->scales = scales;
output->nChannels = totalChannels;
/*
* Clean Memory
*/
delete [] isR;
delete [] isA;
delete [] isN;
delete [] lambdas;
delete [] scaleshw;
/*
* Output
*/
return output;
}
