CActivationLayerInfo | Activation Layer Information class |
CBorderSize | Container for 2D border size |
CCLCoefficientTable | Structure for storing Spatial Gradient Matrix and the minimum eigenvalue for each keypoint |
CCLKernelLibrary | CLKernelLibrary class |
CCLLKInternalKeypoint | Internal keypoint structure for Lucas-Kanade Optical Flow |
CCLOldValue | Structure for storing ival, ixval and iyval for each point inside the window |
CCLScheduler | Provides global access to a CL context and command queue |
CCoordinates2D | 2D Coordinates structure |
CCoordinates2D | Coordinate type |
CCoordinates3D | Coordinate type |
CCPPScheduler | Pool of threads to automatically split a kernel's execution among several threads |
CDetectionWindow | Detection window used for the object detection |
CWindow::Dimension | Describe one of the image's dimensions with a start, end and step |
CDimensions< T > | Dimensions with dimensionality |
►CDimensions< int > | |
CCoordinates | Coordinates of an item |
►CDimensions< size_t > | |
CStrides | Strides of an item in bytes |
CTensorShape | Shape of a tensor |
►CDimensions< unsigned int > | |
CSteps | Class to describe a number of elements in each dimension |
CHOGInfo | Store the HOG's metadata |
►CIAccessWindow | Interface describing methods to update access window and padding based on kernel parameters |
CAccessWindowAutoPadding | Dummy access window |
►CAccessWindowRectangle | Implementation of a rectangular access pattern |
CAccessWindowHorizontal | Implementation of a row access pattern |
CAccessWindowTranspose | Implementation of a XY-transpose access pattern |
CAccessWindowVertical | Implementation of a column access pattern |
CAccessWindowStatic | Implementation of a static rectangular access pattern |
►CIArray< T > | Array of type T |
CArray< T > | Basic implementation of the IArray interface which allocates a static number of T values |
►CICLArray< T > | Interface for OpenCL Array |
CCLArray< T > | CLArray implementation |
►CIArray< NELKInternalKeypoint > | |
CArray< NELKInternalKeypoint > | |
►CIDistribution | Interface for distribution objects |
►CIDistribution1D | 1D Distribution interface |
CDistribution1D | Basic implementation of the 1D distribution interface |
►CICLDistribution1D | ICLDistribution1D interface class |
CCLDistribution1D | CLDistribution1D object class |
►CIFunction | Base class for all functions |
CCLCannyEdge | Basic function to execute canny edge on OpenCL |
CCLConvolutionLayer | Basic function to compute the convolution layer |
CCLConvolutionSquare< matrix_size > | Basic function to execute square convolution.Currently it supports 5x5, 7x7, 9x9 |
CCLEqualizeHistogram | Basic function to execute histogram equalization |
CCLFastCorners | Basic function to execute fast corners |
CCLFullyConnectedLayer | Basic function to compute a Fully Connected layer on OpenCL |
CCLGaussian5x5 | Basic function to execute gaussian filter 5x5 |
►CCLGaussianPyramid | Common interface for all Gaussian pyramid functions |
CCLGaussianPyramidHalf | Basic function to execute gaussian pyramid with HALF scale factor |
CCLGaussianPyramidOrb | Basic function to execute gaussian pyramid with ORB scale factor |
CCLGEMM | Basic function to execute GEMM on OpenCL |
CCLGEMMLowp | Basic function to execute GEMMLowp on OpenCL |
CCLHarrisCorners | Basic function to execute harris corners detection |
CCLHistogram | Basic function to execute histogram |
CCLIntegralImage | Basic function to execute integral image |
CCLLaplacianPyramid | Basic function to execute laplacian pyramid |
CCLLaplacianReconstruct | Basic function to execute laplacian reconstruction |
CCLMeanStdDev | Basic function to execute mean and standard deviation by calling CLMeanStdDevKernel |
CCLMinMaxLocation | Basic function to execute min and max location |
CCLNormalizationLayer | Basic function to simulate a normalization layer |
CCLOpticalFlow | Basic function to execute optical flow |
CCLSobel5x5 | Basic function to execute sobel 5x5 filter |
CCLSobel7x7 | Basic function to execute sobel 7x7 filter |
CCLSoftmaxLayer | Basic function to compute a SoftmaxLayer |
►CICLSimpleFunction | Basic interface for functions which have a single OpenCL kernel |
CCLAbsoluteDifference | Basic function to run CLAbsoluteDifferenceKernel |
CCLAccumulate | Basic function to run CLAccumulateKernel |
CCLAccumulateSquared | Basic function to run CLAccumulateSquaredKernel |
CCLAccumulateWeighted | Basic function to run CLAccumulateWeightedKernel |
CCLActivationLayer | Basic function to run CLActivationLayerKernel |
CCLArithmeticAddition | Basic function to run CLArithmeticAdditionKernel |
CCLArithmeticSubtraction | Basic function to run CLArithmeticSubtractionKernel |
CCLBitwiseAnd | Basic function to run CLBitwiseAndKernel |
CCLBitwiseNot | Basic function to run CLBitwiseNotKernel |
CCLBitwiseOr | Basic function to run CLBitwiseOrKernel |
CCLBitwiseXor | Basic function to run CLBitwiseXorKernel |
CCLBox3x3 | Basic function to execute box filter 3x3 |
CCLChannelCombine | Basic function to run CLChannelCombineKernel to perform channel combination |
CCLChannelExtract | Basic function to run CLChannelExtractKernel to perform channel extraction |
CCLColorConvert | Basic function to run CLColorConvertKernel |
CCLConvolution3x3 | Basic function to execute convolution of size 3x3 |
CCLConvolutionRectangle | Basic function to execute non-square convolution |
CCLDepthConvert | Basic function to run CLDepthConvertKernel |
CCLDerivative | Basic function to execute first order derivative operator |
CCLDilate | Basic function to execute dilate |
CCLErode | Basic function to execute erode |
CCLFillBorder | Basic function to run CLFillBorderKernel |
CCLGaussian3x3 | Basic function to execute gaussian filter 3x3 |
CCLMagnitude | Basic function to run CLMagnitudePhaseKernel |
CCLMedian3x3 | Basic function to execute median filter |
CCLNonLinearFilter | Basic function to execute non linear filter |
CCLNonMaximaSuppression3x3 | Basic function to execute non-maxima suppression over a 3x3 window |
CCLPhase | Basic function to execute an CLMagnitudePhaseKernel |
CCLPixelWiseMultiplication | Basic function to run CLPixelWiseMultiplicationKernel |
CCLPoolingLayer | Basic function to simulate a pooling layer with the specified pooling operation |
CCLRemap | Basic function to execute remap |
CCLScale | Basic function to run CLScaleKernel |
CCLScharr3x3 | Basic function to execute scharr 3x3 filter |
CCLSobel3x3 | Basic function to execute sobel 3x3 filter |
CCLTableLookup | Basic function to run CLTableLookupKernel |
CCLThreshold | Basic function to run CLThresholdKernel |
CCLTranspose | Basic function to transpose a matrix on OpenCL |
CCLWarpAffine | Basic function to run CLWarpAffineKernel for AFFINE transformation |
CCLWarpPerspective | Basic function to run CLWarpPerspectiveKernel for PERSPECTIVE transformation |
►CINESimpleFunction | Basic interface for functions which have a single NEON kernel |
CNEAbsoluteDifference | Basic function to run NEAbsoluteDifferenceKernel |
CNEAccumulate | Basic function to run NEAccumulateKernel |
CNEAccumulateSquared | Basic function to run NEAccumulateSquaredKernel |
CNEAccumulateWeighted | Basic function to run NEAccumulateWeightedKernel |
CNEActivationLayer | Basic function to run NEActivationLayerKernel |
CNEArithmeticAddition | Basic function to run NEArithmeticAdditionKernel |
CNEArithmeticSubtraction | Basic function to run NEArithmeticSubtractionKernel |
CNEBitwiseAnd | Basic function to run NEBitwiseAndKernel |
CNEBitwiseNot | Basic function to run NEBitwiseNotKernel |
CNEBitwiseOr | Basic function to run NEBitwiseOrKernel |
CNEBitwiseXor | Basic function to run NEBitwiseXorKernel |
CNEBox3x3 | Basic function to execute box filter 3x3 |
CNEChannelCombine | Basic function to run NEChannelCombineKernel to perform channel combination |
CNEChannelExtract | Basic function to run NEChannelExtractKernel to perform channel extraction |
CNEColorConvert | Basic function to run NEColorConvertKernel to perform color conversion |
CNEConvolution3x3 | Basic function to execute convolution of size 3x3 |
CNEConvolutionRectangle | Basic function to execute non-square convolution |
CNEDepthConvert | Basic function to run NEDepthConvertKernel |
CNEDilate | Basic function to execute dilate |
CNEErode | Basic function to execute erode |
CNEGaussian3x3 | Basic function to execute gaussian filter 3x3 |
CNEGEMMInterleave4x4 | Basic function to execute NEGEMMInterleave4x4Kernel |
CNEGEMMTranspose1xW | Basic function to execute NEGEMMTranspose1xWKernel |
CNEHOGDetector | Basic function to execute HOG detector based on linear SVM |
CNEIntegralImage | Basic function to run a NEIntegralImageKernel |
CNEMagnitude | Basic function to run NEMagnitudePhaseKernel |
CNEMedian3x3 | Basic function to execute median filter |
CNENonLinearFilter | Basic function to execute non linear filter |
CNENonMaximaSuppression3x3 | Basic function to execute non-maxima suppression over a 3x3 window |
CNEPhase | Basic function to run NEMagnitudePhaseKernel |
CNEPixelWiseMultiplication | Basic function to run NEPixelWiseMultiplicationKernel |
CNEPoolingLayer | Basic function to simulate a pooling layer with the specified pooling operation |
CNERemap | Basic function to execute remap |
CNEScale | Basic function to run NEScaleKernel |
CNEScharr3x3 | Basic function to execute scharr 3x3 filter |
CNESobel3x3 | Basic function to execute sobel 3x3 filter |
CNETableLookup | Basic function to run NETableLookupKernel |
CNEThreshold | Basic function to run NEThresholdKernel |
CNETranspose | Basic function to transpose a matrix on NEON |
CNEWarpAffine | Basic function to run NEWarpAffineKernel |
CNEWarpPerspective | Basic function to run NEWarpPerspectiveKernel |
CNECannyEdge | Basic function to execute canny edge on NEON |
CNEConvolution5x5 | Basic function to execute convolution of size 5x5 |
CNEConvolution7x7 | Basic function to execute convolution of size 7x7 |
CNEConvolution9x9 | Basic function to execute convolution of size 9x9 |
CNEConvolutionLayer | Basic function to simulate a convolution layer |
CNEDerivative | Basic function to execute first order derivative operator |
CNEEqualizeHistogram | Basic function to execute histogram equalization |
CNEFastCorners | Basic function to execute fast corners |
CNEFillBorder | Basic function to run NEFillBorderKernel |
CNEFullyConnectedLayer | Basic function to compute a Fully Connected layer on NEON |
CNEGaussian5x5 | Basic function to execute gaussian filter 5x5 |
►CNEGaussianPyramid | Common interface for all Gaussian pyramid functions |
CNEGaussianPyramidHalf | Basic function to execute gaussian pyramid with HALF scale factor |
CNEGaussianPyramidOrb | Basic function to execute gaussian pyramid with ORB scale factor |
CNEGEMM | Basic function to execute GEMM on NEON |
CNEGEMMLowp | Basic function to execute GEMMLowp on NEON |
CNEHarrisCorners | Basic function to execute harris corners detection |
CNEHistogram | Basic function to execute histogram |
CNEHOGDescriptor | Basic function to calculate HOG descriptor |
CNEHOGGradient | Basic function to calculate the gradient for HOG |
CNEHOGMultiDetection | Basic function to detect multiple objects (or the same object at different scales) on the same input image using HOG |
CNELaplacianPyramid | Basic function to execute laplacian pyramid |
CNELaplacianReconstruct | Basic function to execute laplacian reconstruction |
CNEMeanStdDev | Basic function to execute mean and std deviation |
CNEMinMaxLocation | Basic function to execute min and max location |
CNENormalizationLayer | Basic function to simulate a normalization layer |
CNEOpticalFlow | Basic function to execute optical flow |
CNESobel5x5 | Basic function to execute sobel 5x5 filter |
CNESobel7x7 | Basic function to execute sobel 7x7 filter |
CNESoftmaxLayer | Basic function to compute a SoftmaxLayer |
►CIHOG | Interface for HOG data-object |
CHOG | CPU implementation of HOG data-object |
►CIKernel | Common information for all the kernels |
►CICLKernel | Common interface for all the OpenCL kernels |
CCLAbsoluteDifferenceKernel | Interface for the absolute difference kernel |
CCLArithmeticAdditionKernel | Interface for the arithmetic addition kernel |
CCLArithmeticSubtractionKernel | Interface for the arithmetic subtraction kernel |
CCLBitwiseAndKernel | Interface for the bitwise AND operation kernel |
CCLBitwiseOrKernel | Interface for the bitwise OR operation kernel |
CCLBitwiseXorKernel | Interface for the bitwise XOR operation kernel |
CCLChannelCombineKernel | Interface for the channel combine kernel |
CCLChannelExtractKernel | Interface for the channel extract kernel |
CCLCol2ImKernel | Interface for the col2im reshaping kernel |
CCLColorConvertKernel | Interface for the color convert kernel |
CCLConvolutionLayerWeightsReshapeKernel | Interface for the weights reshape kernel used by convolution and fully connected layers |
CCLConvolutionRectangleKernel | Kernel for the running convolution on a rectangle matrix |
CCLCopyToArrayKernel | CL kernel to copy keypoints information to ICLKeyPointArray and counts the number of key points |
CCLDerivativeKernel | Interface for the derivative kernel |
CCLEdgeNonMaxSuppressionKernel | OpenCL kernel to perform Non-Maxima suppression for Canny Edge |
CCLEdgeTraceKernel | OpenCL kernel to perform Edge tracing |
CCLFastCornersKernel | CL kernel to perform fast corners |
CCLFillBorderKernel | Interface for filling the border of a kernel |
CCLGEMMInterleave4x4Kernel | OpenCL kernel which interleaves the elements of a matrix A in chunk of 4x4 |
CCLGEMMLowpMatrixMultiplyKernel | OpenCL kernel to compute low precision matrix multiplication kernel |
CCLGEMMMatrixAccumulateBiasesKernel | Interface to add a bias to each row of the input tensor |
CCLGEMMMatrixAdditionKernel | OpenCL kernel to perform the in-place matrix addition between 2 matrices, taking into account that the second matrix might be weighted by a scalar value beta |
CCLGEMMMatrixMultiplyKernel | OpenCL kernel to multiply two input matrices "A" and "B" or to multiply a vector "A" by a matrix "B" |
CCLGradientKernel | OpenCL kernel to perform Gradient computation |
CCLHarrisScoreKernel | Interface for the harris score kernel |
CCLHistogramBorderKernel | Interface to run the histogram kernel to handle the leftover part of image |
CCLHistogramKernel | Interface to run the histogram kernel |
CCLIm2ColKernel | Interface for the im2col reshape kernel |
CCLIntegralImageVertKernel | Interface to run the vertical pass of the integral image kernel |
CCLLKTrackerFinalizeKernel | Interface to run the finalize step of LKTracker, where it truncates the coordinates stored in new_points array |
CCLLKTrackerInitKernel | Interface to run the initialization step of LKTracker |
CCLLKTrackerStage0Kernel | Interface to run the first stage of LKTracker, where A11, A12, A22, min_eig, ival, ixval and iyval are computed |
CCLLKTrackerStage1Kernel | Interface to run the second stage of LKTracker, where the motion vectors of the given points are computed |
CCLLogits1DNormKernel | Interface for calculating the final step of the Softmax Layer where each logit value is multiplied by the inverse of the sum of the logits |
CCLLogits1DShiftExpSumKernel | Interface for shifting the logits values around the max value and exponentiating the result |
CCLMagnitudePhaseKernel | Template interface for the kernel to compute magnitude and phase |
CCLMeanStdDevKernel | Interface for the kernel to calculate mean and standard deviation of input image pixels |
CCLMinMaxKernel | Interface for the kernel to perform min max search on an image |
CCLMinMaxLocationKernel | Interface for the kernel to find min max locations of an image |
CCLNormalizationLayerKernel | Interface for the normalization layer kernel |
CCLPixelWiseMultiplicationKernel | Interface for the pixelwise multiplication kernel |
CCLPoolingLayerKernel | Interface for the pooling layer kernel |
CCLRemapKernel | OpenCL kernel to perform a remap on a tensor |
CCLScharr3x3Kernel | Interface for the kernel to run a 3x3 Scharr filter on a tensor |
CCLSobel3x3Kernel | Interface for the kernel to run a 3x3 Sobel filter on a tensor |
CCLSobel5x5HorKernel | Interface for the kernel to run the horizontal pass of 5x5 Sobel filter on a tensor |
CCLSobel5x5VertKernel | Interface for the kernel to run the vertical pass of 5x5 Sobel filter on a tensor |
CCLSobel7x7HorKernel | Interface for the kernel to run the horizontal pass of 7x7 Sobel filter on a tensor |
CCLSobel7x7VertKernel | Interface for the kernel to run the vertical pass of 7x7 Sobel filter on a tensor |
►CICLSimpleKernel | Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output |
CCLGaussianPyramidHorKernel | OpenCL kernel to perform a Gaussian filter and half scaling across width (horizontal pass) |
CCLGaussianPyramidVertKernel | OpenCL kernel to perform a Gaussian filter and half scaling across height (vertical pass) |
►CICLSimple2DKernel | Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output |
CCLAccumulateKernel | Interface for the accumulate kernel |
CCLAccumulateSquaredKernel | Interface for the accumulate squared kernel |
CCLAccumulateWeightedKernel | Interface for the accumulate weighted kernel |
CCLActivationLayerKernel | Interface for the activation layer kernel |
CCLBitwiseNotKernel | Interface for the bitwise NOT operation kernel |
CCLBox3x3Kernel | Interface for the box 3x3 filter kernel |
CCLConvolutionKernel< matrix_size > | Interface for the kernel to run an arbitrary size convolution on a tensor |
CCLDepthConvertKernel | Interface for the depth conversion kernel |
CCLDilateKernel | Interface for the dilate kernel |
CCLErodeKernel | Interface for the erode kernel |
CCLGaussian3x3Kernel | Interface for the Gaussian 3x3 filter kernel |
CCLGEMMTranspose1xWKernel | OpenCL kernel which transposes the elements of a matrix in chunks of 1x4 if the input data type is F32 or in chunks of 1x8 if the input data type is F16 |
CCLIntegralImageHorKernel | Interface to run the horizontal pass of the integral image kernel |
CCLLogits1DMaxKernel | Interface for the identifying the max value of 1D Logits |
CCLMedian3x3Kernel | Interface for the median 3x3 filter kernel |
CCLNonLinearFilterKernel | Interface for the kernel to apply a non-linear filter |
CCLNonMaximaSuppression3x3Kernel | Interface to perform Non-Maxima suppression over a 3x3 window using OpenCL |
CCLScaleKernel | Interface for the warp affine kernel |
►CCLSeparableConvolutionHorKernel< matrix_size > | Kernel for the Horizontal pass of a Separable Convolution |
CCLGaussian5x5HorKernel | Interface for the kernel to run the horizontal pass of 5x5 Gaussian filter on a tensor |
►CCLSeparableConvolutionVertKernel< matrix_size > | Kernel for the Vertical pass of a Separable Convolution |
CCLGaussian5x5VertKernel | Interface for the kernel to run the vertical pass of 5x5 Gaussian filter on a tensor |
CCLTableLookupKernel | Interface for the kernel to perform table lookup calculations |
CCLThresholdKernel | Interface for the thresholding kernel |
CCLTransposeKernel | OpenCL kernel which transposes the elements of a matrix |
CCLWarpAffineKernel | Interface for the warp affine kernel |
CCLWarpPerspectiveKernel | Interface for the warp perspective kernel |
CICLSimple3DKernel | Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output |
►CICPPKernel | Common interface for all kernels implemented in C++ |
CCPPCornerCandidatesKernel | CPP kernel to perform corner candidates |
CCPPSortEuclideanDistanceKernel | CPP kernel to perform sorting and euclidean distance |
►CICPPSimpleKernel | Interface for simple NEON kernels having 1 tensor input and 1 tensor output |
CNEAccumulateKernel | Interface for the accumulate kernel |
CNEAccumulateSquaredKernel | Interface for the accumulate squared kernel |
►CNEAccumulateWeightedKernel | Interface for the accumulate weighted kernel |
CNEAccumulateWeightedFP16Kernel | Interface for the accumulate weighted kernel using F16 |
CNEActivationLayerKernel | Interface for the activation layer kernel |
►CNEBox3x3Kernel | NEON kernel to perform a Box 3x3 filter |
CNEBox3x3FP16Kernel | NEON kernel to perform a Box 3x3 filter using F16 simd |
CNEChannelExtractKernel | Interface for the channel extract kernel |
CNEConvolutionKernel< matrix_size > | Interface for the kernel to run an arbitrary size convolution on a tensor |
CNEDepthConvertKernel | Depth conversion kernel |
CNEDilateKernel | Interface for the kernel to perform boolean image dilatation |
CNEErodeKernel | Interface for the kernel to perform boolean image erosion |
CNEGaussian3x3Kernel | NEON kernel to perform a Gaussian 3x3 filter |
CNEGaussian5x5HorKernel | NEON kernel to perform a Gaussian 5x5 filter (horizontal pass) |
CNEGaussian5x5VertKernel | NEON kernel to perform a Gaussian 5x5 filter (vertical pass) |
CNEGaussianPyramidHorKernel | NEON kernel to perform a GaussianPyramid (horizontal pass) |
CNEGaussianPyramidVertKernel | NEON kernel to perform a GaussianPyramid (vertical pass) |
CNEGEMMInterleave4x4Kernel | NEON kernel to interleave the elements of a matrix |
CNEGEMMMatrixAdditionKernel | NEON kernel to perform the in-place matrix addition between 2 matrices taking into account that the second matrix might be weighted by a scalar value beta: |
CNEGEMMTranspose1xWKernel | NEON kernel which transposes the elements of a matrix in chunks of 1x4 if the input data type is F32 or in chunks of 1x8 if the input data type is F16 |
CNEIntegralImageKernel | Kernel to perform an image integral on an image |
CNELogits1DMaxKernel | Interface for the identifying the max value of 1D Logits |
CNEMedian3x3Kernel | Kernel to perform a median filter on a tensor |
CNESeparableConvolutionHorKernel< matrix_size > | Kernel for the Horizontal pass of a Separable Convolution |
CNESeparableConvolutionVertKernel< matrix_size > | Kernel for the Vertical pass of a Separable Convolution |
CNETableLookupKernel | Interface for the kernel to perform table lookup calculations |
CNEConvolutionKernel< 5 > | |
CNEConvolutionKernel< 7 > | |
CNEConvolutionKernel< 9 > | |
CNESeparableConvolutionHorKernel< 5 > | |
CNESeparableConvolutionHorKernel< 7 > | |
CNESeparableConvolutionHorKernel< 9 > | |
CNESeparableConvolutionVertKernel< 5 > | |
CNESeparableConvolutionVertKernel< 7 > | |
CNESeparableConvolutionVertKernel< 9 > | |
►CINEHarrisScoreKernel | Common interface for all Harris Score kernels |
CNEHarrisScoreFP16Kernel< block_size > | Interface for the accumulate Weighted kernel using F16 |
CNEHarrisScoreKernel< block_size > | Template NEON kernel to perform Harris Score |
►CINEWarpKernel | Common interface for warp affine and warp perspective |
CNEWarpAffineKernel< interpolation > | Template interface for the kernel to compute warp affine |
CNEWarpPerspectiveKernel< interpolation > | Template interface for the kernel to compute warp perspective |
CNEAbsoluteDifferenceKernel | Interface for the absolute difference kernel |
CNEArithmeticAdditionKernel | Interface for the kernel to perform addition between two tensors |
CNEArithmeticSubtractionKernel | Interface for the kernel to perform subtraction between two tensors |
CNEBitwiseAndKernel | Interface for the kernel to perform bitwise AND between XY-planes of two tensors |
CNEBitwiseNotKernel | Interface for the kernel to perform bitwise NOT operation |
CNEBitwiseOrKernel | Interface for the kernel to perform bitwise inclusive OR between two tensors |
CNEBitwiseXorKernel | Interface for the kernel to perform bitwise exclusive OR (XOR) between two tensors |
CNEChannelCombineKernel | Interface for the channel combine kernel |
CNECol2ImKernel | NEON kernel to perform col2im reshaping |
CNEColorConvertKernel | Interface for the color convert kernel |
CNEConvolutionLayerWeightsReshapeKernel | NEON kernel to perform reshaping on the weights used by convolution layer |
CNEConvolutionRectangleKernel | Kernel for the running convolution on a rectangle matrix |
CNECumulativeDistributionKernel | Interface for the cumulative distribution (cummulative summmation) calculation kernel |
CNEDerivativeKernel | Interface for the kernel to run the derivative along the X/Y directions on a tensor |
CNEEdgeNonMaxSuppressionKernel | NEON kernel to perform Non-Maxima suppression for Canny Edge |
CNEEdgeTraceKernel | NEON kernel to perform Edge tracing |
CNEFastCornersKernel | NEON kernel to perform fast corners |
CNEFillArrayKernel | This kernel adds all texels greater than or equal to the threshold value to the keypoint array |
CNEFillBorderKernel | Interface for the kernel to fill borders |
CNEFillInnerBorderKernel | Interface for the kernel to fill the interior borders |
CNEGEMMLowpMatrixMultiplyKernel | NEON kernel to multiply matrices |
CNEGEMMMatrixAccumulateBiasesKernel | NEON kernel to add a bias to each row of the input tensor |
CNEGEMMMatrixMultiplyKernel | NEON kernel to multiply two input matrices "A" and "B" |
►CNEGradientKernel | Computes magnitude and quantised phase from inputs gradients |
CNEGradientFP16Kernel | NEON kernel to perform Gradient computation |
CNEHistogramBorderKernel | Interface for the histogram border handling kernel |
CNEHistogramKernel | Interface for the histogram kernel |
CNEHOGBlockNormalizationKernel | NEON kernel to perform HOG block normalization |
CNEHOGDetectorKernel | NEON kernel to perform HOG detector kernel using linear SVM |
CNEHOGNonMaximaSuppressionKernel | NEON kernel to perform in-place computation of euclidean distance based non-maxima suppression for HOG |
CNEHOGOrientationBinningKernel | NEON kernel to perform HOG Orientation Binning |
CNEIm2ColKernel | Interface for the im2col reshape kernel |
CNELKTrackerKernel | Interface for the Lucas-Kanade tracker kernel |
CNELogits1DNormKernel | Interface for calculating the final step of the Softmax Layer where each logit value is multiplied by the inverse of the sum of the logits |
CNELogits1DShiftExpSumKernel | Interface for shifting the logits values around the max value and exponentiating the result |
CNEMagnitudePhaseFP16Kernel< mag_type, phase_type > | Template interface for the kernel to compute magnitude and phase |
CNEMagnitudePhaseKernel< mag_type, phase_type > | Template interface for the kernel to compute magnitude and phase |
CNEMeanStdDevKernel | Interface for the kernel to calculate mean and standard deviation of input image pixels |
CNEMinMaxKernel | Interface for the kernel to perform min max search on an image |
CNEMinMaxLocationKernel | Interface for the kernel to find min max locations of an image |
CNENonLinearFilterKernel | Interface for the kernel to apply a non-linear filter |
►CNENonMaximaSuppression3x3Kernel | Interface to perform Non-Maxima suppression over a 3x3 window using NEON |
CNENonMaximaSuppression3x3FP16Kernel | NEON kernel to perform Non-Maxima suppression 3x3 |
CNENormalizationLayerKernel | Interface for the normalization layer kernel |
CNEPixelWiseMultiplicationKernel | Interface for the kernel to perform addition between two tensors |
CNEPoolingLayerKernel | Interface for the pooling layer kernel |
CNERemapKernel | NEON kernel to perform a remap on a tensor |
CNEScaleKernel | NEON kernel to perform scaling on a tensor |
CNEScharr3x3Kernel | Interface for the kernel to run a 3x3 Scharr filter on a tensor |
CNESobel3x3Kernel | Interface for the kernel to run a 3x3 Sobel X filter on a tensor |
CNESobel5x5HorKernel | Interface for the kernel to run the horizontal pass of 5x5 Sobel filter on a tensor |
CNESobel5x5VertKernel | Interface for the kernel to run the vertical pass of 5x5 Sobel Y filter on a tensor |
CNESobel7x7HorKernel | Interface for the kernel to run the horizontal pass of 7x7 Sobel filter on a tensor |
CNESobel7x7VertKernel | Interface for the kernel to run the vertical pass of 7x7 Sobel Y filter on a tensor |
CNEThresholdKernel | Interface for the thresholding kernel |
CNETransposeKernel | NEON kernel which transposes the elements of a matrix |
►CILut | Lookup Table object interface |
►CICLLut | Interface for OpenCL LUT |
CCLLut | Basic implementation of the OpenCL lut interface |
CLut | Basic implementation of the LUT interface |
►CILutAllocator | Basic interface to allocate LUTs' |
CCLLutAllocator | Basic implementation of a CL memory LUT allocator |
CLutAllocator | Basic implementation of a CPU memory LUT allocator |
CImage | Structure to hold Image information |
►CIMultiHOG | Interface for storing multiple HOG data-objects |
CMultiHOG | CPU implementation of multi HOG data-object |
►CIMultiImage | Interface for multi-planar images |
►CICLMultiImage | Interface for OpenCL multi-planar images |
CCLMultiImage | Basic implementation of the CL multi-planar image interface |
CMultiImage | Basic implementation of the multi-planar image interface |
CInternalKeypoint | |
CIOFormatInfo | IO formatting information class |
►CIPyramid | Interface for pyramid data-object |
CCLPyramid | Basic implementation of the OpenCL pyramid interface |
CPyramid | Basic implementation of the pyramid interface |
►CITensor | Interface for NEON tensor |
►CICLTensor | Interface for OpenCL tensor |
CCLTensor | Basic implementation of the OpenCL tensor interface |
CTensor | Basic implementation of the tensor interface |
►CITensorAllocator | Interface to allocate tensors |
CCLTensorAllocator | Basic implementation of a CL memory tensor allocator |
CTensorAllocator | Basic implementation of a CPU memory tensor allocator |
CIterator | Iterator updated by execute_window_loop for each window element |
CKernel | Kernel class |
CKeypoint | |
CKeyPoint | Keypoint type |
CMultiImageInfo | Store the multi-planar image's metadata |
CNELKInternalKeypoint | Internal keypoint class for Lucas-Kanade Optical Flow |
CNormalizationLayerInfo | Normalization Layer Information class |
CPadStrideInfo | Padding and stride information class |
CPixelValue | Class describing the value of a pixel for any image format |
CPoolingLayerInfo | Pooling Layer Information class |
CPPMLoader | Class to load the content of a PPM file into an Image |
CProgram | Program class |
CPyramidInfo | Store the Pyramid's metadata |
CRectangle | Rectangle type |
CSize2D | Class for specifying the size of an image or rectangle |
CTensor3D | Structure to hold 3D tensor information |
CTensorInfo | Store the tensor's metadata |
CValidRegion | |
CVector | Structure to hold Vector information |
CWindow | Describe a multidimensional execution window |