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Wenjun_H_

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11-25-2014
04:20 AM

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Getting started with IPP

Hi,

I have not used IPP before and was tasked to do benchmarking of 2D correlation/convolution function with IPP. I have some questions which will aid in my development works.

1. How do I get a copy of the IPP? I need to use IPP on both Ubuntu and Windows machine, does it mean I need to get 2 license of IPP? How much does it cost?

2. Installation guide. Is there a easy-to-follow installation guide to install IPP on Windows and Ubuntu

3. What IPP functions is available for doing 2D correlation/convolution?

4. I intend to divide a image into overlapping image blocks and apply 2D correlation on each image blocks to achieve some performance boost. Is there similar works done previously?

Thanks.

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Pavel_B_Intel1

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11-26-2014
11:47 AM

114 Views

Hi Wenjun,

Here you can download trial version of Intel Composer XE which contain IPP libraries inside: https://software.intel.com/en-us/intel-parallel-studio-xe/try-buy also on the page you can find information about cost.

Regarding installation guide - install is very simple, I guess you don't meet any problems with install.

Documentation for image processing (2D) functions is here: https://software.intel.com/en-us/node/503692#702422F6-C4B4-464F-A2CF-4E3ADCAD2C49

Regarding p.4 your question I will ask Intel guys to help you.

Pavel

Igor_A_Intel

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11-27-2014
12:10 AM

114 Views

2D conv/crosscorr APIs are defined in ippi.h (and documented in the IPP manual):

/* ////////////////////////////////////////////////////////////////////////////

// Names: ippiConv_32f_C1R, ippiConv_32f_C3R, ippiConv_32f_C4R

// ippiConv_16s_C1R, ippiConv_16s_C3R, ippiConv_16s_C4R

// ippiConv_8u_C1R, ippiConv_8u_C3R, ippiConv_8u_C4R

// Purpose: Performs full or valid 2-D convolution of two images.

// The result image size depends on operation shape selected in algType mask as follows:

// (Wa+Wb-1)*(Ha+Hb-1) for ippiROIFull mask

// (Wa-Wb+1)*(Ha-Hb+1) for ippiROIValid mask,

// where Wa*Ha and Wb*Hb are the sizes of the image and template, respectively.

// If the IppAlgMask value in algType is equal to ippAlgAuto, the optimal algorithm is selected

// automatically. For big data size, the function uses 2D FFT algorithm.

// Parameters:

// pSrc1, pSrc2 - Pointers to the source images ROI.

// src1Step, src2Step - Distances, in bytes, between the starting points of consecutive lines in the source images.

// src1Size, src2Size - Size, in pixels, of the source images.

// pDst - Pointer to the destination image ROI.

// dstStep - Distance, in bytes, between the starting points of consecutive lines in the destination image.

// divisor - The integer value by which the computed result is divided (for operations on integer data only).

// algType - Bit-field mask for the algorithm type definition. Possible values are the results of composition of the IppAlgType and IppiROIShape values.

// Usage example: algType=(ippiROIFull|ippAlgFFT); - full-shaped convolution will be calculated using 2D FFT.

// pBuffer - Pointer to the buffer for internal calculations.

// Returns:

// ippStsNoErr - OK.

// ippStsNullPtrErr - Error when any of the specified pointers is NULL.

// ippStsStepErr - Error when src1Step, src2Step, or dstStep has a zero or negative value.

// ippStsSizeErr - Error when src1Size or src2Size has a zero or negative value.

// ippStsDivisorErr - Error when divisor has the zero value.

// ippStsAlgTypeErr - Error when :

// The result of the bitwise AND operation between algType and ippAlgMask differs from the ippAlgAuto, ippAlgDirect, or ippAlgFFT values.

// The result of the bitwise AND operation between algType and ippiROIMask differs from the ippiROIFull or ippiROIValid values.

*/

/* ////////////////////////////////////////////////////////////////////////////

// Names: ippiCrossCorrNorm_32f_C1R

// ippiCrossCorrNorm_16u32f_C1R

// ippiCrossCorrNorm_8u32f_C1R

// ippiCrossCorrNorm_8u_C1RSfs

// Purpose: Computes normalized cross-correlation between an image and a template.

// The result image size depends on operation shape selected in algType mask as follows :

// (Wa+Wb-1)*(Ha+Hb-1) for ippiROIFull mask,

// (Wa)*(Ha) for ippiROISame mask,

// (Wa-Wb+1)*(Ha-Hb+1) for ippiROIValid mask,

// where Wa*Ha and Wb*Hb are the sizes of the image and template correspondingly.

// Support of normalization operations (set in the algType mask) is set by selecting the following masks:

// ippiNormNone - the cross-correlation without normalization.

// ippiNorm - the normalized cross-correlation.

// ippiNormCoefficient - the normalized correlation coefficients.

// If the IppAlgMask value in algType is equal to ippAlgAuto, the optimal algorithm is selected automatically.

// For big data size, the function uses 2D FFT algorithm.

// Parameters:

// pSrc - Pointer to the source image ROI.

// srcStep - Distance, in bytes, between the starting points of consecutive lines in the source image.

// srcRoiSize - Size of the source ROI in pixels.

// pTpl - Pointer to the template image.

// tplStep - Distance, in bytes, between the starting points of consecutive lines in the template image.

// tplRoiSize - Size of the template ROI in pixels.

// pDst - Pointer to the destination image ROI.

// dstStep - Distance, in bytes, between the starting points of consecutive lines in the destination image.

// scaleFactor - Scale factor.

// algType - Bit-field mask for the algorithm type definition. Possible values are the results of composition of the IppAlgType, IppiROIShape, and IppiNormOp values.

// Usage example: algType=(ippiROIFull|ippAlgFFT|ippiNormNone); - full-shaped cross-correlation will be calculated using 2D FFT without result normalization.

// pBuffer - Pointer to the work buffer.

// Returns:

// ippStsNoErr OK.

// ippStsNullPtrErr Error when any of the specified pointers is NULL.

// ippStsStepErr Error when the value of srcStep, tplStep, or dstStep is negative, or equal to zero.

// ippStsSizeErr Error when :

// srcRoiSize or tplRoiSize is negative, or equal to zero.

// The value of srcRoiSize is less than the corresponding value of tplRoiSize.

// ippStsAlgTypeErr Error when :

// The result of the bitwise AND operation between the algType and ippAlgMask differs from the ippAlgAuto, ippAlgDirect, or ippAlgFFT values.

// The result of the bitwise AND operation between the algType and ippiROIMask differs from the ippiROIFull, ippiROISame, or ippiROIValid values.

// The result of the bitwise AND operation between the algType and ippiNormMask differs from the ippiNormNone, ippiNorm, or ippiNormCoefficient values.

*/

both functions already use internally overlapping image blocks algorithm - therefore no sense to apply the same externally

regards, Igor

Wenjun_H_

Beginner

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11-27-2014
05:47 AM

114 Views

__Pavel Berdnikov__:

Is it possible to buy just the IPP, in which case it will be more affordable?

__Igor Astakhov__:

The IPP manual did not mention how the 2D convolution/ NCC is implemented. How does the function decides what size is each image block?

To be clear about my meaning of overlapping image blocks:

I want to find the correlation between a full image [eg. 720 x 480] and a template image [eg. 40 x 40]. I intend to divide the full image into overlapping image block of size [eg. 120 x 120] with overlap border of 40 pixels. Hence I would have 9 x 6 image blocks. For each block, I would do 2D convolution/ NCC. I would then merge the results to get the correlation of the full image and template image.

Chao_Y_Intel

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11-27-2014
04:06 PM

114 Views

Hello,

For Intel IPP purchase, it is available by the following components:

Intel® Parallel Studio XE Suites/ Intel® System Studio Suite

The Composer Edition for these products including the Intel IPP, they are started from $699.

Intel® Parallel Studio Composer Edition: https://software.intel.com/en-us/intel-parallel-studio-xe/try-buy

Intel® System Studio Composer Edition for Windows*: https://software.intel.com/en-us/intel-parallel-studio-xe/try-buy

Thanks,

Chao

Igor_A_Intel

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11-28-2014
12:28 AM

114 Views

Hi Wenjun,

for example MSDN doesn't provide any info on functions' internals - why do you expect such description from the IPP manual? For your particular case - 40x40 template - block size will be 64x64 or 128x128 (depends on the architecture) - the nearest power of two (or +1) - and function will use 2D FFT internally.

regards, Igor

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