Opencl learning step by step (8) grayscale image histogram computing (2)

Now we use the method in the previous tutorial to count the number of pixels in a pair of rgba images (This pixel satisfies the arbitrary components of R, G, B, And a> = 5 )? The method I want to consider is to create a histogram of 256 bin. For a pixel, calculate max (R, G, B, A) and use this value to determine the pixel to enter the bin, after obtaining the histogram, the width * Height-hostbin [0]-hostbin [1]-hostbin [2]-hostbin [3]-hostbin [4], that is, the result we want.

The code in this tutorial is basically the same as that in the previous tutorial. The differences mainly include the following two points:

1. We have installed the rgba color chart.

// Load the image
Unsigned char * src_image = 0;
Gfreeimage IMG;
If (! IMG. LoadImage ("../lenna.jpg "))
{
Printf ("can't load lenna.jpg \ n ");
Exit (0 );
}
Src_image = IMG. getimagedata (width, height );

2. There is a slight change in the kernel code. The kernel code is as follows:

# Define linear_mem_access
# Pragma opencl extension cl_khr_byte_addressable_store: Enable

# Define binary size 256

/**
* Calculate the histogram. The value of bins is 256.
* Data Input Data
* Memory shared by all threads in a workgroup,
* Histogram of each workgroup
*/

_ KERNEL
Void histogram256 (_ global const uchar4 * data,
_ Local uchar * sharedarray,
_ Global uint * binresult)
{
Size_t localid = get_local_id (0 );
Size_t globalid = get_global_id (0 );
Size_t groupid = get_group_id (0 );
Size_t groupsize = get_local_size (0 );

// Initialize the shared memory
For (INT I = 0; I <bin_size; ++ I)
Sharedarray [localid * bin_size + I] = 0;

Barrier (clk_local_mem_fence );

Uchar R, G, B, A, T;
// Calculate the thread Histogram
For (INT I = 0; I <bin_size; ++ I)
{
# Ifdef linear_mem_access
R = (uint) data [groupid * groupsize * bin_size + I * groupsize + localid]. X;
G = (uint) data [groupid * groupsize * bin_size + I * groupsize + localid]. Y;
B = (uint) data [groupid * groupsize * bin_size + I * groupsize + localid]. Z;
A = (uint) data [groupid * groupsize * bin_size + I * groupsize + localid]. W;
Uint value = (uint) max (R, G), max (B, ));
# Else
Uint value = data [globalid * bin_size + I];
# Endif // linear_mem_access
Sharedarray [localid * bin_size + value] ++;
}

Barrier (clk_local_mem_fence );

// Merge the histograms of all threads in the workgroup to generate the workgroup histogram.
For (INT I = 0; I <bin_size/groupsize; ++ I)
{
Uint bincount = 0;
For (Int J = 0; j <groupsize; ++ J)
Bincount + = sharedarray [J * bin_size + I * groupsize + localid];

Binresult [groupid * bin_size + I * groupsize + localid] = bincount;
}
}

 

Complete code can be found:

Project File gcltutorial8

Download Code:

Http://files.cnblogs.com/mikewolf2002/gclTutorial.zip