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Commit 35d91d13 authored by Gaurav Kukreja's avatar Gaurav Kukreja
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constant kernel based on gaurav's convolution 

Signed-off-by: 's avatarGaurav Kukreja <gmkukreja@gmail.com>
parent fb855284
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gaurav/2_Assign/ex4/main.cu
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// ###
// ###
// ### Practical Course: GPU Programming in Computer Vision
// ###
// ###
// ### Technical University Munich, Computer Vision Group
// ### Winter Semester 2013/2014, March 3 - April 4
// ###
// ###
// ### Evgeny Strekalovskiy, Maria Klodt, Jan Stuehmer, Mohamed Souiai
// ###
// ###
// ###
// ###
// ###
// ### Practical Course: GPU Programming in Computer Vision
// ###
// ###
// ### Technical University Munich, Computer Vision Group
// ### Winter Semester 2013/2014, March 3 - April 4
// ###
// ###
// ### Evgeny Strekalovskiy, Maria Klodt, Jan Stuehmer, Mohamed Souiai
// ###
// ###
// ###
// ###
// ###
// ### TODO: For every student of your group, please provide here:
// ###
// ### Gaurav Kukreja, gaurav.kukreja@tum.de, p058
// ###
// ###
// ###
// ###
// ### TODO: For every student of your group, please provide here:
// ###
// ### Gaurav Kukreja, gaurav.kukreja@tum.de, p058
// ###
// ###
#include "aux.h"
#include <iostream>
#include <math.h>
using namespace std;
#include "aux.h"
#include <iostream>
#include <math.h>
using namespace std;
#define MAX_KERNEL_WIDTH 20
#define MAX_KERNEL_WIDTH 20
__constant__ float constKernel[MAX_KERNEL_WIDTH * MAX_KERNEL_WIDTH];
__constant__ float constKernel[MAX_KERNEL_WIDTH * MAX_KERNEL_WIDTH];
// uncomment to use the camera
//#define CAMERA
// uncomment to use the camera
//#define CAMERA
#define USING_GPU
#define USING_GPU
template<typename T>
__device__ T gpu_min(T a, T b)
{
template<typename T>
__device__ T gpu_min(T a, T b)
{
if (a < b)
return a;
else
return b;
}
}
template<typename T>
__device__ T gpu_max(T a, T b)
{
template<typename T>
__device__ T gpu_max(T a, T b)
{
if (a < b)
return b;
else
return a;
}
}
// Image Gradient
__device__ void convolveImage(float* imgIn, float* imgOut, int rad, int w, int h, int nc)
{
// Image Gradient
__device__ void convolveImage(float* imgIn, float* imgOut, int rad, int w, int h, int nc)
{
int ix = threadIdx.x + blockDim.x * blockIdx.x;
int iy = threadIdx.y + blockDim.y * blockIdx.y;
int iz = threadIdx.z + blockDim.z * blockIdx.z;
......@@ -71,33 +71,33 @@
{
imgOut[idx] = 0; // initialize
float value = 0;
for(int j = -rad; j < rad; j++) // for each row in kernel
for(int j = -rad; j <= rad; j++) // for each row in kernel
{
int iny = gpu_max(0, gpu_min(iy+j, h-1));
for(int i = -rad; i < rad; i++) // for each element in the kernel row
for(int i = -rad; i <= rad; i++) // for each element in the kernel row
{
int inx = gpu_max(0, gpu_min(ix+i, w-1));
int inIdx = inx + (iny * w) + (iz * w * h); // Index of Input Image to be multiplied by corresponding element in kernel
value += imgIn[inIdx] * constKernel[i+rad + ((j+rad) * rad)];
value += imgIn[inIdx] * constKernel[i+rad + ((j+rad) * (2 * rad + 1))];
}
}
imgOut[idx] = value;
}
}
}
__global__ void callKernel(float* imgIn, float* imgOut, int rad, int w, int h, int nc)
{
__global__ void callKernel(float* imgIn, float* imgOut, int rad, int w, int h, int nc)
{
convolveImage(imgIn, imgOut, rad, w, h, nc);
}
}
int main(int argc, char **argv)
{
#ifdef USING_GPU
int main(int argc, char **argv)
{
#ifdef USING_GPU
// Before the GPU can process your kernels, a so called "CUDA context" must be initialized
// This happens on the very first call to a CUDA function, and takes some time (around half a second)
// We will do it right here, so that the run time measurements are accurate
cudaDeviceSynchronize(); CUDA_CHECK;
#endif // USING_GPU
#endif // USING_GPU
......@@ -107,14 +107,14 @@
//
// return value: getParam("param", ...) returns true if "-param" is specified, and false otherwise
#ifdef CAMERA
#else
#ifdef CAMERA
#else
// input image
string image = "";
bool ret = getParam("i", image, argc, argv);
if (!ret) cerr << "ERROR: no image specified" << endl;
if (argc <= 1) { cout << "Usage: " << argv[0] << " -i <image> [-repeats <repeats>] [-gray] [-sigma <sigma>]" << endl << "\t Default Value of sigma = 0.5" << endl; return 1; }
#endif
#endif
// number of computation repetitions to get a better run time measurement
int repeats = 1;
......@@ -133,7 +133,7 @@
// ### Define your own parameters here as needed
// Init camera / Load input image
#ifdef CAMERA
#ifdef CAMERA
// Init camera
cv::VideoCapture camera(0);
......@@ -146,14 +146,14 @@
cv::Mat mIn;
camera >> mIn;
#else
#else
// Load the input image using opencv (load as grayscale if "gray==true", otherwise as is (may be color or grayscale))
cv::Mat mIn = cv::imread(image.c_str(), (gray? CV_LOAD_IMAGE_GRAYSCALE : -1));
// check
if (mIn.data == NULL) { cerr << "ERROR: Could not load image " << image << endl; return 1; }
#endif
#endif
// convert to float representation (opencv loads image values as single bytes by default)
mIn.convertTo(mIn,CV_32F);
......@@ -195,7 +195,7 @@
float *imgOut = new float[(size_t)w*h*mOut.channels()];
int rad = ceil(3 * sigma); // kernel radius
int kw = 2 * rad; // kernel width
int kw = 2 * rad + 1; // kernel width
if (kw > MAX_KERNEL_WIDTH)
{
......@@ -243,13 +243,13 @@
}
// Display Kernel
cv::Mat cvKernelOut(2*rad, 2*rad, CV_32F);
cv::Mat cvKernelOut(kw, kw, CV_32F);
convert_layered_to_mat(cvKernelOut, kernelOut);
showImage("Kernel", cvKernelOut, 100, 10);
// For camera mode: Make a loop to read in camera frames
#ifdef CAMERA
#ifdef CAMERA
// Read a camera image frame every 30 milliseconds:
// cv::waitKey(30) waits 30 milliseconds for a keyboard input,
// returns a value <0 if no key is pressed during this time, returns immediately with a value >=0 if a key is pressed
......@@ -261,7 +261,7 @@
mIn.convertTo(mIn,CV_32F);
// convert range of each channel to [0,1] (opencv default is [0,255])
mIn /= 255.f;
#endif
#endif
// Init raw input image array
// opencv images are interleaved: rgb rgb rgb... (actually bgr bgr bgr...)
......@@ -335,10 +335,10 @@
int idx = ix + (iy * w) + (iz * w * h);
imgOut[idx] = 0; // initialize
float value = 0;
for(int j = -rad; j < rad; j++) // for each row in kernel
for(int j = -rad; j <= rad; j++) // for each row in kernel
{
int iny = max(0, min(iy+j, h-1));
for(int i = -rad; i < rad; i++) // for each element in the kernel row
for(int i = -rad; i <= rad; i++) // for each element in the kernel row
{
int inx = max(0, min(ix+i, w-1));
int inIdx = inx + (iny * w) + (iz * w * h); // Index of Input Image to be multiplied by corresponding element in kernel
......@@ -368,13 +368,13 @@
// ### Display your own output images here as needed
#ifdef CAMERA
#ifdef CAMERA
// end of camera loop
}
#else
#else
// wait for key inputs
cv::waitKey(0);
#endif
#endif
......@@ -392,7 +392,7 @@
// close all opencv windows
cvDestroyAllWindows();
return 0;
}
}
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