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MIVisionX: /home/docs/checkouts/readthedocs.org/user_builds/advanced-micro-devices-mivisionx/checkouts/docs-5.7.1/amd_openvx/openvx/include/VX/vxu.h File Reference

The OpenVX Utility Library. More...

Go to the source code of this file.

Functions
VX_API_ENTRY vx_status VX_API_CALL	vxuColorConvert (vx_context context, vx_image input, vx_image output)
	[Immediate] Invokes an immediate Color Conversion. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuChannelExtract (vx_context context, vx_image input, vx_enum channel, vx_image output)
	[Immediate] Invokes an immediate Channel Extract. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuChannelCombine (vx_context context, vx_image plane0, vx_image plane1, vx_image plane2, vx_image plane3, vx_image output)
	[Immediate] Invokes an immediate Channel Combine. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuSobel3x3 (vx_context context, vx_image input, vx_image output_x, vx_image output_y)
	[Immediate] Invokes an immediate Sobel 3x3. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuMagnitude (vx_context context, vx_image grad_x, vx_image grad_y, vx_image mag)
	[Immediate] Invokes an immediate Magnitude. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuPhase (vx_context context, vx_image grad_x, vx_image grad_y, vx_image orientation)
	[Immediate] Invokes an immediate Phase. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuScaleImage (vx_context context, vx_image src, vx_image dst, vx_enum type)
	[Immediate] Scales an input image to an output image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuTableLookup (vx_context context, vx_image input, vx_lut lut, vx_image output)
	[Immediate] Processes the image through the LUT. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuHistogram (vx_context context, vx_image input, vx_distribution distribution)
	[Immediate] Generates a distribution from an image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuEqualizeHist (vx_context context, vx_image input, vx_image output)
	[Immediate] Equalizes the Histogram of a grayscale image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuAbsDiff (vx_context context, vx_image in1, vx_image in2, vx_image out)
	[Immediate] Computes the absolute difference between two images. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuMeanStdDev (vx_context context, vx_image input, vx_float32 mean, vx_float32 stddev)
	[Immediate] Computes the mean value and optionally the standard deviation. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuThreshold (vx_context context, vx_image input, vx_threshold thresh, vx_image output)
	[Immediate] Threshold's an input image and produces a `VX_DF_IMAGE_U8` boolean image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuNonMaxSuppression (vx_context context, vx_image input, vx_image mask, vx_int32 win_size, vx_image output)
	[Immediate] Performs Non-Maxima Suppression on an image, producing an image of the same type. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuIntegralImage (vx_context context, vx_image input, vx_image output)
	[Immediate] Computes the integral image of the input. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuErode3x3 (vx_context context, vx_image input, vx_image output)
	[Immediate] Erodes an image by a 3x3 window. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuDilate3x3 (vx_context context, vx_image input, vx_image output)
	[Immediate] Dilates an image by a 3x3 window. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuMedian3x3 (vx_context context, vx_image input, vx_image output)
	[Immediate] Computes a median filter on the image by a 3x3 window. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuBox3x3 (vx_context context, vx_image input, vx_image output)
	[Immediate] Computes a box filter on the image by a 3x3 window. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuGaussian3x3 (vx_context context, vx_image input, vx_image output)
	[Immediate] Computes a gaussian filter on the image by a 3x3 window. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuNonLinearFilter (vx_context context, vx_enum function, vx_image input, vx_matrix mask, vx_image output)
	[Immediate] Performs Non-linear Filtering. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuConvolve (vx_context context, vx_image input, vx_convolution conv, vx_image output)
	[Immediate] Computes a convolution on the input image with the supplied matrix. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuGaussianPyramid (vx_context context, vx_image input, vx_pyramid gaussian)
	[Immediate] Computes a Gaussian pyramid from an input image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuLaplacianPyramid (vx_context context, vx_image input, vx_pyramid laplacian, vx_image output)
	[Immediate] Computes a Laplacian pyramid from an input image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuLaplacianReconstruct (vx_context context, vx_pyramid laplacian, vx_image input, vx_image output)
	[Immediate] Reconstructs an image from a Laplacian Image pyramid. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuWeightedAverage (vx_context context, vx_image img1, vx_scalar alpha, vx_image img2, vx_image output)
	[Immediate] Computes a weighted average image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuMinMaxLoc (vx_context context, vx_image input, vx_scalar minVal, vx_scalar maxVal, vx_array minLoc, vx_array maxLoc, vx_scalar minCount, vx_scalar maxCount)
	[Immediate] Computes the minimum and maximum values of the image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuMin (vx_context context, vx_image in1, vx_image in2, vx_image out)
	[Immediate] Computes pixel-wise minimum values between two images. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuMax (vx_context context, vx_image in1, vx_image in2, vx_image out)
	[Immediate] Computes pixel-wise maximum values between two images. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuConvertDepth (vx_context context, vx_image input, vx_image output, vx_enum policy, vx_int32 shift)
	[Immediate] Converts the input images bit-depth into the output image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuCannyEdgeDetector (vx_context context, vx_image input, vx_threshold hyst, vx_int32 gradient_size, vx_enum norm_type, vx_image output)
	[Immediate] Computes Canny Edges on the input image into the output image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuHalfScaleGaussian (vx_context context, vx_image input, vx_image output, vx_int32 kernel_size)
	[Immediate] Performs a Gaussian Blur on an image then half-scales it. The interpolation mode used is nearest-neighbor. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuAnd (vx_context context, vx_image in1, vx_image in2, vx_image out)
	[Immediate] Computes the bitwise and between two images. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuOr (vx_context context, vx_image in1, vx_image in2, vx_image out)
	[Immediate] Computes the bitwise inclusive-or between two images. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuXor (vx_context context, vx_image in1, vx_image in2, vx_image out)
	[Immediate] Computes the bitwise exclusive-or between two images. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuNot (vx_context context, vx_image input, vx_image output)
	[Immediate] Computes the bitwise not of an image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuMultiply (vx_context context, vx_image in1, vx_image in2, vx_float32 scale, vx_enum overflow_policy, vx_enum rounding_policy, vx_image out)
	[Immediate] Performs elementwise multiplications on pixel values in the input images and a scale. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuAdd (vx_context context, vx_image in1, vx_image in2, vx_enum policy, vx_image out)
	[Immediate] Performs arithmetic addition on pixel values in the input images. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuSubtract (vx_context context, vx_image in1, vx_image in2, vx_enum policy, vx_image out)
	[Immediate] Performs arithmetic subtraction on pixel values in the input images. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuWarpAffine (vx_context context, vx_image input, vx_matrix matrix, vx_enum type, vx_image output)
	[Immediate] Performs an Affine warp on an image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuWarpPerspective (vx_context context, vx_image input, vx_matrix matrix, vx_enum type, vx_image output)
	[Immediate] Performs an Perspective warp on an image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuHarrisCorners (vx_context context, vx_image input, vx_scalar strength_thresh, vx_scalar min_distance, vx_scalar sensitivity, vx_int32 gradient_size, vx_int32 block_size, vx_array corners, vx_scalar num_corners)
	[Immediate] Computes the Harris Corners over an image and produces the array of scored points. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuFastCorners (vx_context context, vx_image input, vx_scalar strength_thresh, vx_bool nonmax_suppression, vx_array corners, vx_scalar num_corners)
	[Immediate] Computes corners on an image using FAST algorithm and produces the array of feature points. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuOpticalFlowPyrLK (vx_context context, vx_pyramid old_images, vx_pyramid new_images, vx_array old_points, vx_array new_points_estimates, vx_array new_points, vx_enum termination, vx_scalar epsilon, vx_scalar num_iterations, vx_scalar use_initial_estimate, vx_size window_dimension)
	[Immediate] Computes an optical flow on two images. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuMatchTemplate (vx_context context, vx_image src, vx_image templateImage, vx_enum matchingMethod, vx_image output)
	[Immediate] The function compares an image template against overlapped image regions. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuLBP (vx_context context, vx_image in, vx_enum format, vx_int8 kernel_size, vx_image out)
	[Immediate] The function extracts LBP image from an input image More...

VX_API_ENTRY vx_status VX_API_CALL	vxuHOGCells (vx_context context, vx_image input, vx_int32 cell_width, vx_int32 cell_height, vx_int32 num_bins, vx_tensor magnitudes, vx_tensor bins)
	[Immediate] Performs cell calculations for the average gradient magnitude and gradient orientation histograms. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuHOGFeatures (vx_context context, vx_image input, vx_tensor magnitudes, vx_tensor bins, const vx_hog_t *params, vx_size hog_param_size, vx_tensor features)
	[Immediate] Computes Histogram of Oriented Gradients features for the W1xW2 window in a sliding window fashion over the whole input image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuHoughLinesP (vx_context context, vx_image input, const vx_hough_lines_p_t *params, vx_array lines_array, vx_scalar num_lines)
	[Immediate] Finds the Probabilistic Hough Lines detected in the input binary image, each line is stored in the output array as a set of points (x1, y1, x2, y2) . More...

VX_API_ENTRY vx_status VX_API_CALL	vxuRemap (vx_context context, vx_image input, vx_remap table, vx_enum policy, vx_image output)
	[Immediate] Remaps an output image from an input image. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuBilateralFilter (vx_context context, vx_tensor src, vx_int32 diameter, vx_float32 sigmaSpace, vx_float32 sigmaValues, vx_tensor dst)
	[Immediate] The function applies bilateral filtering to the input tensor. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuTensorMultiply (vx_context context, vx_tensor input1, vx_tensor input2, vx_scalar scale, vx_enum overflow_policy, vx_enum rounding_policy, vx_tensor output)
	[Immediate] Performs element wise multiplications on element values in the input tensor data with a scale. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuTensorAdd (vx_context context, vx_tensor input1, vx_tensor input2, vx_enum policy, vx_tensor output)
	[Immediate] Performs arithmetic addition on element values in the input tensor data. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuTensorSubtract (vx_context context, vx_tensor input1, vx_tensor input2, vx_enum policy, vx_tensor output)
	[Immediate] Performs arithmetic subtraction on element values in the input tensor data. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuTensorTableLookup (vx_context context, vx_tensor input1, vx_lut lut, vx_tensor output)
	[Immediate] Performs LUT on element values in the input tensor data. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuTensorTranspose (vx_context context, vx_tensor input, vx_tensor output, vx_size dimension1, vx_size dimension2)
	[Immediate] Performs transpose on the input tensor. The tensor is transposed according to a specified 2 indexes in the tensor (0-based indexing) More...

VX_API_ENTRY vx_status VX_API_CALL	vxuTensorConvertDepth (vx_context context, vx_tensor input, vx_enum policy, vx_scalar norm, vx_scalar offset, vx_tensor output)
	[Immediate] Performs a bit-depth conversion. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuTensorMatrixMultiply (vx_context context, vx_tensor input1, vx_tensor input2, vx_tensor input3, const vx_tensor_matrix_multiply_params_t *matrix_multiply_params, vx_tensor output)
	[Immediate] Performs a generalized matrix multiplication. More...

VX_API_ENTRY vx_status VX_API_CALL	vxuCopy (vx_context context, vx_reference input, vx_reference output)
	[Immediate] Copy data from one object to another. More...

Detailed Description

The OpenVX Utility Library.

Function Documentation

◆ vxuAbsDiff()

VX_API_ENTRY vx_status VX_API_CALL vxuAbsDiff	(	vx_context	context,
		vx_image	in1,
		vx_image	in2,
		vx_image	out
	)

[Immediate] Computes the absolute difference between two images.

Parameters

[in]	context	The reference to the overall context.
[in]	in1	An input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.
[in]	in2	An input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.
[out]	out	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuAdd()

VX_API_ENTRY vx_status VX_API_CALL vxuAdd	(	vx_context	context,
		vx_image	in1,
		vx_image	in2,
		vx_enum	policy,
		vx_image	out
	)

[Immediate] Performs arithmetic addition on pixel values in the input images.

Parameters

[in]	context	The reference to the overall context.
[in]	in1	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` input image.
[in]	in2	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` input image.
[in]	policy	A vx_convert_policy_e enumeration.
[out]	out	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuAnd()

VX_API_ENTRY vx_status VX_API_CALL vxuAnd	(	vx_context	context,
		vx_image	in1,
		vx_image	in2,
		vx_image	out
	)

[Immediate] Computes the bitwise and between two images.

Parameters

[in]	context	The reference to the overall context.
[in]	in1	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` input image.
[in]	in2	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` input image.
[out]	out	The `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` output image, which must have the same dimensions and type as the input images.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuBilateralFilter()

VX_API_ENTRY vx_status VX_API_CALL vxuBilateralFilter	(	vx_context	context,
		vx_tensor	src,
		vx_int32	diameter,
		vx_float32	sigmaSpace,
		vx_float32	sigmaValues,
		vx_tensor	dst
	)

[Immediate] The function applies bilateral filtering to the input tensor.

Parameters

[in]	context	The reference to the overall context.
[in]	src	The input data a `vx_tensor`. maximum 3 dimension and minimum 2. The tensor is of type `VX_TYPE_UINT8` or `VX_TYPE_INT16`. dimensions are [radiometric ,width,height] or [width,height]
[in]	diameter	of each pixel neighbourhood that is used during filtering. Values of diameter must be odd. Bigger then 3 and smaller then 10.
[in]	sigmaValues	Filter sigma in the radiometric space. Supported values are bigger then 0 and smaller or equal 20.
[in]	sigmaSpace	Filter sigma in the spatial space. Supported values are bigger then 0 and smaller or equal 20.
[out]	dst	The output data a `vx_tensor`,Of type `VX_TYPE_UINT8` or `VX_TYPE_INT16`. And must be the same type and size of the input.

Note: The border modes VX_NODE_BORDER value VX_BORDER_REPLICATE and VX_BORDER_CONSTANT are supported.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuBox3x3()

VX_API_ENTRY vx_status VX_API_CALL vxuBox3x3	(	vx_context	context,
		vx_image	input,
		vx_image	output
	)

[Immediate] Computes a box filter on the image by a 3x3 window.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` format.
[out]	output	The output image in `VX_DF_IMAGE_U8` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuCannyEdgeDetector()

VX_API_ENTRY vx_status VX_API_CALL vxuCannyEdgeDetector	(	vx_context	context,
		vx_image	input,
		vx_threshold	hyst,
		vx_int32	gradient_size,
		vx_enum	norm_type,
		vx_image	output
	)

[Immediate] Computes Canny Edges on the input image into the output image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input `VX_DF_IMAGE_U8` image.
[in]	hyst	The double threshold for hysteresis. The `VX_THRESHOLD_INPUT_FORMAT` shall be either `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16`. The `VX_THRESHOLD_OUTPUT_FORMAT` is ignored.
[in]	gradient_size	The size of the Sobel filter window, must support at least 3, 5 and 7.
[in]	norm_type	A flag indicating the norm used to compute the gradient, `VX_NORM_L1` or `VX_NORM_L2`.
[out]	output	The binary output image in `VX_DF_IMAGE_U1` or `VX_DF_IMAGE_U8` format with values either 0 and 1 (`VX_DF_IMAGE_U1`), or 0 and 255 (`VX_DF_IMAGE_U8`).

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuChannelCombine()

VX_API_ENTRY vx_status VX_API_CALL vxuChannelCombine	(	vx_context	context,
		vx_image	plane0,
		vx_image	plane1,
		vx_image	plane2,
		vx_image	plane3,
		vx_image	output
	)

[Immediate] Invokes an immediate Channel Combine.

Parameters

[in]	context	The reference to the overall context.
[in]	plane0	The plane that forms channel 0. Must be `VX_DF_IMAGE_U8`.
[in]	plane1	The plane that forms channel 1. Must be `VX_DF_IMAGE_U8`.
[in]	plane2	[optional] The plane that forms channel 2. Must be `VX_DF_IMAGE_U8`.
[in]	plane3	[optional] The plane that forms channel 3. Must be `VX_DF_IMAGE_U8`.
[out]	output	The output image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuChannelExtract()

VX_API_ENTRY vx_status VX_API_CALL vxuChannelExtract	(	vx_context	context,
		vx_image	input,
		vx_enum	channel,
		vx_image	output
	)

[Immediate] Invokes an immediate Channel Extract.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image. Must be one of the defined `vx_df_image_e` multi-channel formats.
[in]	channel	The `vx_channel_e` enumeration to extract.
[out]	output	The output image. Must be `VX_DF_IMAGE_U8`.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuColorConvert()

VX_API_ENTRY vx_status VX_API_CALL vxuColorConvert	(	vx_context	context,
		vx_image	input,
		vx_image	output
	)

[Immediate] Invokes an immediate Color Conversion.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image.
[out]	output	The output image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuConvertDepth()

VX_API_ENTRY vx_status VX_API_CALL vxuConvertDepth	(	vx_context	context,
		vx_image	input,
		vx_image	output,
		vx_enum	policy,
		vx_int32	shift
	)

[Immediate] Converts the input images bit-depth into the output image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image.
[out]	output	The output image.
[in]	policy	A `VX_TYPE_ENUM` of the `vx_convert_policy_e` enumeration.
[in]	shift	A scalar containing a `VX_TYPE_INT32` of the shift value.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`..

◆ vxuConvolve()

VX_API_ENTRY vx_status VX_API_CALL vxuConvolve	(	vx_context	context,
		vx_image	input,
		vx_convolution	conv,
		vx_image	output
	)

[Immediate] Computes a convolution on the input image with the supplied matrix.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` format.
[in]	conv	The `vx_int16` convolution matrix.
[out]	output	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuCopy()

VX_API_ENTRY vx_status VX_API_CALL vxuCopy	(	vx_context	context,
		vx_reference	input,
		vx_reference	output
	)

[Immediate] Copy data from one object to another.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input data object.
[out]	output	The output data object.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuDilate3x3()

VX_API_ENTRY vx_status VX_API_CALL vxuDilate3x3	(	vx_context	context,
		vx_image	input,
		vx_image	output
	)

[Immediate] Dilates an image by a 3x3 window.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` format.
[out]	output	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` format, which must have the same dimensions and type as the input image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuEqualizeHist()

VX_API_ENTRY vx_status VX_API_CALL vxuEqualizeHist	(	vx_context	context,
		vx_image	input,
		vx_image	output
	)

[Immediate] Equalizes the Histogram of a grayscale image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The grayscale input image in `VX_DF_IMAGE_U8`
[out]	output	The grayscale output image of type `VX_DF_IMAGE_U8` with equalized brightness and contrast.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuErode3x3()

VX_API_ENTRY vx_status VX_API_CALL vxuErode3x3	(	vx_context	context,
		vx_image	input,
		vx_image	output
	)

[Immediate] Erodes an image by a 3x3 window.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` format.
[out]	output	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` format, which must have the same dimensions and type as the input image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuFastCorners()

VX_API_ENTRY vx_status VX_API_CALL vxuFastCorners	(	vx_context	context,
		vx_image	input,
		vx_scalar	strength_thresh,
		vx_bool	nonmax_suppression,
		vx_array	corners,
		vx_scalar	num_corners
	)

[Immediate] Computes corners on an image using FAST algorithm and produces the array of feature points.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input `VX_DF_IMAGE_U8` image.
[in]	strength_thresh	Threshold on difference between intensity of the central pixel and pixels on Bresenham's circle of radius 3 (`VX_TYPE_FLOAT32` scalar), with a value in the range of 0.0 $\le$ strength_thresh < 256.0. Any fractional value will be truncated to an integer.
[in]	nonmax_suppression	If true, non-maximum suppression is applied to detected corners before being places in the `vx_array` of `VX_TYPE_KEYPOINT` structs.
[out]	corners	Output corner `vx_array` of `VX_TYPE_KEYPOINT`. The order of the keypoints in this array is implementation dependent.
[out]	num_corners	[optional] The total number of detected corners in image. Use a VX_TYPE_SIZE scalar.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuGaussian3x3()

VX_API_ENTRY vx_status VX_API_CALL vxuGaussian3x3	(	vx_context	context,
		vx_image	input,
		vx_image	output
	)

[Immediate] Computes a gaussian filter on the image by a 3x3 window.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` format.
[out]	output	The output image in `VX_DF_IMAGE_U8` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuGaussianPyramid()

VX_API_ENTRY vx_status VX_API_CALL vxuGaussianPyramid	(	vx_context	context,
		vx_image	input,
		vx_pyramid	gaussian
	)

[Immediate] Computes a Gaussian pyramid from an input image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8`
[out]	gaussian	The Gaussian pyramid with `VX_DF_IMAGE_U8` to construct.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuHalfScaleGaussian()

VX_API_ENTRY vx_status VX_API_CALL vxuHalfScaleGaussian	(	vx_context	context,
		vx_image	input,
		vx_image	output,
		vx_int32	kernel_size
	)

[Immediate] Performs a Gaussian Blur on an image then half-scales it. The interpolation mode used is nearest-neighbor.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input `VX_DF_IMAGE_U8` image.
[out]	output	The output `VX_DF_IMAGE_U8` image.
[in]	kernel_size	The input size of the Gaussian filter. Supported values are 1, 3 and 5.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuHarrisCorners()

VX_API_ENTRY vx_status VX_API_CALL vxuHarrisCorners	(	vx_context	context,
		vx_image	input,
		vx_scalar	strength_thresh,
		vx_scalar	min_distance,
		vx_scalar	sensitivity,
		vx_int32	gradient_size,
		vx_int32	block_size,
		vx_array	corners,
		vx_scalar	num_corners
	)

[Immediate] Computes the Harris Corners over an image and produces the array of scored points.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input `VX_DF_IMAGE_U8` image.
[in]	strength_thresh	The `VX_TYPE_FLOAT32` minimum threshold which to eliminate Harris Corner scores (computed using the normalized Sobel kernel).
[in]	min_distance	The `VX_TYPE_FLOAT32` radial Euclidean distance for non-maximum suppression.
[in]	sensitivity	The `VX_TYPE_FLOAT32` scalar sensitivity threshold from the Harris-Stephens equation.
[in]	gradient_size	The gradient window size to use on the input. The implementation must support at least 3, 5, and 7.
[in]	block_size	The block window size used to compute the harris corner score. The implementation must support at least 3, 5, and 7.
[out]	corners	The array of `VX_TYPE_KEYPOINT` structs. The order of the keypoints in this array is implementation dependent.
[out]	num_corners	[optional] The total number of detected corners in image. Use a VX_TYPE_SIZE scalar

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuHistogram()

VX_API_ENTRY vx_status VX_API_CALL vxuHistogram	(	vx_context	context,
		vx_image	input,
		vx_distribution	distribution
	)

[Immediate] Generates a distribution from an image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8`
[out]	distribution	The output distribution.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuHOGCells()

VX_API_ENTRY vx_status VX_API_CALL vxuHOGCells	(	vx_context	context,
		vx_image	input,
		vx_int32	cell_width,
		vx_int32	cell_height,
		vx_int32	num_bins,
		vx_tensor	magnitudes,
		vx_tensor	bins
	)

[Immediate] Performs cell calculations for the average gradient magnitude and gradient orientation histograms.

Firstly, the gradient magnitude and gradient orientation are computed for each pixel in the input image. Two 1-D centred, point discrete derivative masks are applied to the input image in the horizontal and vertical directions.

$M_h = [-1, 0, 1]$

and

$M_v = [-1, 0, 1]^T$

$G_v$ is the result of applying mask $M_v$ to the input image, and $G_h$ is the result of applying mask $M_h$ to the input image. The border mode used for the gradient calculation is implementation dependent. Its behavior should be similar to VX_BORDER_UNDEFINED. The gradient magnitudes and gradient orientations for each pixel are then calculated in the following manner.

$G(x,y) = \sqrt{G_v(x,y)^2 + G_h(x,y)^2}$

$\theta(x,y) = arctan(G_v(x,y), G_h(x,y))$

where $arctan(v, h)$ is $tan^{-1}(v/h)$ when $h!=0$ ,

$ -pi/2 $ if $v<0$ and $h==0$ ,

$ pi/2 $ if $v>0$ and $h==0$

and $ 0 $ if $v==0$ and $h==0$

Secondly, the gradient magnitudes and orientations are used to compute the bins output tensor and optional magnitudes output tensor. These tensors are computed on a cell level where the cells are rectangular in shape. The magnitudes tensor contains the average gradient magnitude for each cell.

$magnitudes(c) = \frac{1}{(cell\_width * cell\_height)}\sum\limits_{w=0}^{cell\_width} \sum\limits_{h=0}^{cell\_height} G_c(w,h)$

where $G_c$ is the gradient magnitudes related to cell $c$ . The bins tensor contains histograms of gradient orientations for each cell. The gradient orientations at each pixel range from 0 to 360 degrees. These are quantised into a set of histogram bins based on the num_bins parameter. Each pixel votes for a specific cell histogram bin based on its gradient orientation. The vote itself is the pixel's gradient magnitude.

$bins(c, n) = \sum\limits_{w=0}^{cell\_width} \sum\limits_{h=0}^{cell\_height} G_c(w,h) * 1[B_c(w, h, num\_bins) == n]$

where $B_c$ produces the histogram bin number based on the gradient orientation of the pixel at location ( $w$ , $h$ ) in cell $c$ based on the $num\_bins$ and

$1[B_c(w, h, num\_bins) == n]$

is a delta-function with value 1 when $B_c(w, h, num\_bins) == n$ or 0 otherwise.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image of type `VX_DF_IMAGE_U8`.
[in]	cell_width	The histogram cell width of type `VX_TYPE_INT32`.
[in]	cell_height	The histogram cell height of type `VX_TYPE_INT32`.
[in]	num_bins	The histogram size of type `VX_TYPE_INT32`.
[out]	magnitudes	The output average gradient magnitudes per cell of `vx_tensor` of type `VX_TYPE_INT16` of size $[floor(image_{width}/cell_{width}) ,floor(image_{height}/cell_{height}) ]$ .
[out]	bins	The output gradient orientation histograms per cell of `vx_tensor` of type `VX_TYPE_INT16` of size $[floor(image_{width}/cell_{width}) ,floor(image_{height}/cell_{height}), num_{bins}]$ .

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuHOGFeatures()

VX_API_ENTRY vx_status VX_API_CALL vxuHOGFeatures	(	vx_context	context,
		vx_image	input,
		vx_tensor	magnitudes,
		vx_tensor	bins,
		const vx_hog_t *	params,
		vx_size	hog_param_size,
		vx_tensor	features
	)

[Immediate] Computes Histogram of Oriented Gradients features for the W1xW2 window in a sliding window fashion over the whole input image.

Firstly if a magnitudes tensor is provided the cell histograms in the bins tensor are normalised by the average cell gradient magnitudes.

$bins(c,n) = \frac{bins(c,n)}{magnitudes(c)}$

To account for changes in illumination and contrast the cell histograms must be locally normalized which requires grouping the cell histograms together into larger spatially connected blocks. Blocks are rectangular grids represented by three parameters: the number of cells per block, the number of pixels per cell, and the number of bins per cell histogram. These blocks typically overlap, meaning that each cell histogram contributes more than once to the final descriptor. To normalize a block its cell histograms $h$ are grouped together to form a vector $v = [h_1, h_2, h_3, ... , h_n]$ . This vector is normalised using L2-Hys which means performing L2-norm on this vector; clipping the result (by limiting the maximum values of v to be threshold) and renormalizing again. If the threshold is equal to zero then L2-Hys normalization is not performed.

$L2norm(v) = \frac{v}{\sqrt{\|v\|_2^2 + \epsilon^2}}$

where $\|v\|_k$ be its k-norm for k=1, 2, and $\epsilon$ be a small constant. For a specific window its HOG descriptor is then the concatenated vector of the components of the normalized cell histograms from all of the block regions contained in the window. The W1xW2 window starting position is at coordinates 0x0. If the input image has dimensions that are not an integer multiple of W1xW2 blocks with the specified stride, then the last positions that contain only a partial W1xW2 window will be calculated with the remaining part of the W1xW2 window padded with zeroes. The Window W1xW2 must also have a size so that it contains an integer number of cells, otherwise the node is not well-defined. The final output tensor will contain HOG descriptors equal to the number of windows in the input image. The output features tensor has 3 dimensions, given by:

$[ (floor((image_{width}-window_{width})/window_{stride}) + 1),$

$(floor((image_{height}-window_{height})/window_{stride}) + 1),$

$floor((window_{width} - block_{width})/block_{stride} + 1) * floor((window_{height} - block_{height})/block_{stride} + 1) *$

$(((block_{width} * block_{height}) / (cell_{width} * cell_{height})) * num_{bins})]$

See vxCreateTensor and vxCreateVirtualTensor. The output tensor from this function may be very large. For this reason, is it not recommended that this "immediate mode" version of the function be used. The preferred method to perform this function is as graph node with a virtual tensor as the output.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image of type `VX_DF_IMAGE_U8`.
[in]	magnitudes	The averge gradient magnitudes per cell of `vx_tensor` of type `VX_TYPE_INT16`. It is the output of `vxuHOGCells`.
[in]	bins	The gradient orientation histogram per cell of `vx_tensor` of type `VX_TYPE_INT16`. It is the output of `vxuHOGCells`.
[in]	params	The parameters of type `vx_hog_t`.
[in]	hog_param_size	Size of `vx_hog_t` in bytes.
[out]	features	The output HOG features of `vx_tensor` of type `VX_TYPE_INT16`.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuHoughLinesP()

VX_API_ENTRY vx_status VX_API_CALL vxuHoughLinesP	(	vx_context	context,
		vx_image	input,
		const vx_hough_lines_p_t *	params,
		vx_array	lines_array,
		vx_scalar	num_lines
	)

[Immediate] Finds the Probabilistic Hough Lines detected in the input binary image, each line is stored in the output array as a set of points (x1, y1, x2, y2) .

Some implementations of the algorithm may have a random or non-deterministic element. If the target application is in a safety-critical environment this should be borne in mind and steps taken in the implementation, the application or both to achieve the level of determinism required by the system design.

Parameters

[in]	context	The reference to the overall context.
[in]	input	A single channel binary source image of type `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1`.
[in]	params	parameters of the struct `vx_hough_lines_p_t`
[out]	lines_array	lines_array contains array of lines, see `vx_line2d_t` The order of lines in implementation dependent
[out]	num_lines	[optional] The total number of detected lines in image. Use a VX_TYPE_SIZE scalar

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuIntegralImage()

VX_API_ENTRY vx_status VX_API_CALL vxuIntegralImage	(	vx_context	context,
		vx_image	input,
		vx_image	output
	)

[Immediate] Computes the integral image of the input.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` format.
[out]	output	The output image in `VX_DF_IMAGE_U32` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuLaplacianPyramid()

VX_API_ENTRY vx_status VX_API_CALL vxuLaplacianPyramid	(	vx_context	context,
		vx_image	input,
		vx_pyramid	laplacian,
		vx_image	output
	)

[Immediate] Computes a Laplacian pyramid from an input image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.
[out]	laplacian	The Laplacian pyramid with `VX_DF_IMAGE_S16` to construct.
[out]	output	The lowest resolution image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format necessary to reconstruct the input image from the pyramid. The output image format should be same as input image format.

See also: group_pyramid

Returns: A vx_status enumeration.

Return values

VX_SUCCESS	Success.
*	An error occured. See `vx_status_e`

◆ vxuLaplacianReconstruct()

VX_API_ENTRY vx_status VX_API_CALL vxuLaplacianReconstruct	(	vx_context	context,
		vx_pyramid	laplacian,
		vx_image	input,
		vx_image	output
	)

[Immediate] Reconstructs an image from a Laplacian Image pyramid.

Parameters

[in]	context	The reference to the overall context.
[in]	laplacian	The Laplacian pyramid with `VX_DF_IMAGE_S16` format.
[in]	input	The lowest resolution image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format for the Laplacian pyramid.
[out]	output	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format with the highest possible resolution reconstructed from the Laplacian pyramid. The output image format should be same as input image format.

See also: group_pyramid

Returns: A vx_status enumeration.

Return values

VX_SUCCESS	Success.
*	An error occured. See `vx_status_e`

◆ vxuLBP()

VX_API_ENTRY vx_status VX_API_CALL vxuLBP	(	vx_context	context,
		vx_image	in,
		vx_enum	format,
		vx_int8	kernel_size,
		vx_image	out
	)

[Immediate] The function extracts LBP image from an input image

Parameters

[in]	context	The reference to the overall context.
[in]	in	An input image in `vx_image`. Or in the equations. the image is of type `VX_DF_IMAGE_U8`
[in]	format	A variation of LBP like original LBP and mLBP. see `vx_lbp_format_e`
[in]	kernel_size	Kernel size. Only size of 3 and 5 are supported
[out]	out	An output image in `vx_image`.Or in the equations. the image is of type `VX_DF_IMAGE_U8`

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuMagnitude()

VX_API_ENTRY vx_status VX_API_CALL vxuMagnitude	(	vx_context	context,
		vx_image	grad_x,
		vx_image	grad_y,
		vx_image	mag
	)

[Immediate] Invokes an immediate Magnitude.

Parameters

[in]	context	The reference to the overall context.
[in]	grad_x	The input x image. This must be in `VX_DF_IMAGE_S16` format.
[in]	grad_y	The input y image. This must be in `VX_DF_IMAGE_S16` format.
[out]	mag	The magnitude image. This will be in `VX_DF_IMAGE_S16` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuMatchTemplate()

VX_API_ENTRY vx_status VX_API_CALL vxuMatchTemplate	(	vx_context	context,
		vx_image	src,
		vx_image	templateImage,
		vx_enum	matchingMethod,
		vx_image	output
	)

[Immediate] The function compares an image template against overlapped image regions.

The detailed equation to the matching can be found in vx_comp_metric_e. The output of the template matching node is a comparison map as described in vx_comp_metric_e. The Node have a limitation on the template image size (width*height). It should not be larger then 65535. If the valid region of the template image is smaller than the entire template image, the result in the destination image is implementation-dependent.

Parameters

[in]	context	The reference to the overall context.
[in]	src	The input image of type `VX_DF_IMAGE_U8`.
[in]	templateImage	Searched template of type `VX_DF_IMAGE_U8`.
[in]	matchingMethod	attribute specifying the comparison method `vx_comp_metric_e`. This function support only `VX_COMPARE_CCORR_NORM` and `VX_COMPARE_L2`.
[out]	output	Map of comparison results. The output is an image of type `VX_DF_IMAGE_S16`

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuMax()

VX_API_ENTRY vx_status VX_API_CALL vxuMax	(	vx_context	context,
		vx_image	in1,
		vx_image	in2,
		vx_image	out
	)

[Immediate] Computes pixel-wise maximum values between two images.

Parameters

[in]	context	The reference to the overall context.
[in]	in1	The first input image. Must be of type `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16`.
[in]	in2	The second input image. Must be of type `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16`.
[out]	out	The output image which will hold the result of max.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuMeanStdDev()

VX_API_ENTRY vx_status VX_API_CALL vxuMeanStdDev	(	vx_context	context,
		vx_image	input,
		vx_float32 *	mean,
		vx_float32 *	stddev
	)

[Immediate] Computes the mean value and optionally the standard deviation.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image. `VX_DF_IMAGE_U8` and `VX_DF_IMAGE_U1` are supported.
[out]	mean	The average pixel value.
[out]	stddev	[optional] The standard deviation of the pixel values.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuMedian3x3()

VX_API_ENTRY vx_status VX_API_CALL vxuMedian3x3	(	vx_context	context,
		vx_image	input,
		vx_image	output
	)

[Immediate] Computes a median filter on the image by a 3x3 window.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` format.
[out]	output	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` format, which must have the same dimensions and type as the input image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuMin()

VX_API_ENTRY vx_status VX_API_CALL vxuMin	(	vx_context	context,
		vx_image	in1,
		vx_image	in2,
		vx_image	out
	)

[Immediate] Computes pixel-wise minimum values between two images.

Parameters

[in]	context	The reference to the overall context.
[in]	in1	The first input image. Must be of type `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16`.
[in]	in2	The second input image. Must be of type `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16`.
[out]	out	The output image which will hold the result of min.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuMinMaxLoc()

VX_API_ENTRY vx_status VX_API_CALL vxuMinMaxLoc	(	vx_context	context,
		vx_image	input,
		vx_scalar	minVal,
		vx_scalar	maxVal,
		vx_array	minLoc,
		vx_array	maxLoc,
		vx_scalar	minCount,
		vx_scalar	maxCount
	)

[Immediate] Computes the minimum and maximum values of the image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.
[out]	minVal	The minimum value in the image, which corresponds to the type of the input.
[out]	maxVal	The maximum value in the image, which corresponds to the type of the input.
[out]	minLoc	[optional] The minimum `VX_TYPE_COORDINATES2D` locations. If the input image has several minimums, the kernel will return up to the capacity of the array.
[out]	maxLoc	[optional] The maximum `VX_TYPE_COORDINATES2D` locations. If the input image has several maximums, the kernel will return up to the capacity of the array.
[out]	minCount	[optional] The total number of detected minimums in image. Use a `VX_TYPE_SIZE` scalar.
[out]	maxCount	[optional] The total number of detected maximums in image. Use a `VX_TYPE_SIZE` scalar.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuMultiply()

VX_API_ENTRY vx_status VX_API_CALL vxuMultiply	(	vx_context	context,
		vx_image	in1,
		vx_image	in2,
		vx_float32	scale,
		vx_enum	overflow_policy,
		vx_enum	rounding_policy,
		vx_image	out
	)

[Immediate] Performs elementwise multiplications on pixel values in the input images and a scale.

Parameters

[in]	context	The reference to the overall context.
[in]	in1	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` input image.
[in]	in2	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` input image.
[in]	scale	A non-negative `VX_TYPE_FLOAT32` multiplied to each product before overflow handling.
[in]	overflow_policy	A `vx_convert_policy_e` enumeration.
[in]	rounding_policy	A `vx_round_policy_e` enumeration.
[out]	out	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuNonLinearFilter()

VX_API_ENTRY vx_status VX_API_CALL vxuNonLinearFilter	(	vx_context	context,
		vx_enum	function,
		vx_image	input,
		vx_matrix	mask,
		vx_image	output
	)

[Immediate] Performs Non-linear Filtering.

Parameters

[in]	context	The reference to the overall context.
[in]	function	The non-linear filter function. See `vx_non_linear_filter_e`.
[in]	input	The input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` format.
[in]	mask	The mask to be applied to the Non-linear function. `VX_MATRIX_ORIGIN` attribute is used to place the mask appropriately when computing the resulting image. See `vxCreateMatrixFromPattern` and `vxCreateMatrixFromPatternAndOrigin`.
[out]	output	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` format, which must have the same dimensions and type as the input image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuNonMaxSuppression()

VX_API_ENTRY vx_status VX_API_CALL vxuNonMaxSuppression	(	vx_context	context,
		vx_image	input,
		vx_image	mask,
		vx_int32	win_size,
		vx_image	output
	)

[Immediate] Performs Non-Maxima Suppression on an image, producing an image of the same type.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.
[in]	mask	[optional] Constrict suppression to a ROI. The mask image is of type `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` and must be the same dimensions as the input image.
[in]	win_size	The size of window over which to perform the localized non-maxima suppression. Must be odd, and less than or equal to the smallest dimension of the input image.
[out]	output	The output image, of the same type as the input, that has been non-maxima suppressed.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuNot()

VX_API_ENTRY vx_status VX_API_CALL vxuNot	(	vx_context	context,
		vx_image	input,
		vx_image	output
	)

[Immediate] Computes the bitwise not of an image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` input image.
[out]	output	The `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` output image, which must have the same dimensions and type as the input image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuOpticalFlowPyrLK()

VX_API_ENTRY vx_status VX_API_CALL vxuOpticalFlowPyrLK	(	vx_context	context,
		vx_pyramid	old_images,
		vx_pyramid	new_images,
		vx_array	old_points,
		vx_array	new_points_estimates,
		vx_array	new_points,
		vx_enum	termination,
		vx_scalar	epsilon,
		vx_scalar	num_iterations,
		vx_scalar	use_initial_estimate,
		vx_size	window_dimension
	)

[Immediate] Computes an optical flow on two images.

Parameters

[in]	context	The reference to the overall context.
[in]	old_images	Input of first (old) image pyramid in `VX_DF_IMAGE_U8`.
[in]	new_images	Input of destination (new) image pyramid in `VX_DF_IMAGE_U8`
[in]	old_points	an array of key points in a vx_array of `VX_TYPE_KEYPOINT` those key points are defined at the old_images high resolution pyramid
[in]	new_points_estimates	an array of estimation on what is the output key points in a `vx_array` of `VX_TYPE_KEYPOINT` those keypoints are defined at the new_images high resolution pyramid
[out]	new_points	an output array of key points in a `vx_array` of `VX_TYPE_KEYPOINT` those key points are defined at the new_images high resolution pyramid
[in]	termination	termination can be `VX_TERM_CRITERIA_ITERATIONS` or `VX_TERM_CRITERIA_EPSILON` or `VX_TERM_CRITERIA_BOTH`
[in]	epsilon	is the `vx_float32` error for terminating the algorithm
[in]	num_iterations	is the number of iterations. Use a `VX_TYPE_UINT32` scalar.
[in]	use_initial_estimate	Can be set to either `vx_false_e` or `vx_true_e`.
[in]	window_dimension	The size of the window on which to perform the algorithm. See `VX_CONTEXT_OPTICAL_FLOW_MAX_WINDOW_DIMENSION`

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuOr()

VX_API_ENTRY vx_status VX_API_CALL vxuOr	(	vx_context	context,
		vx_image	in1,
		vx_image	in2,
		vx_image	out
	)

[Immediate] Computes the bitwise inclusive-or between two images.

Parameters

[in]	context	The reference to the overall context.
[in]	in1	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` input image.
[in]	in2	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` input image.
[out]	out	The `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` output image, which must have the same dimensions and type as the input images.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuPhase()

VX_API_ENTRY vx_status VX_API_CALL vxuPhase	(	vx_context	context,
		vx_image	grad_x,
		vx_image	grad_y,
		vx_image	orientation
	)

[Immediate] Invokes an immediate Phase.

Parameters

[in]	context	The reference to the overall context.
[in]	grad_x	The input x image. This must be in `VX_DF_IMAGE_S16` format.
[in]	grad_y	The input y image. This must be in `VX_DF_IMAGE_S16` format.
[out]	orientation	The phase image. This will be in `VX_DF_IMAGE_U8` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuRemap()

VX_API_ENTRY vx_status VX_API_CALL vxuRemap	(	vx_context	context,
		vx_image	input,
		vx_remap	table,
		vx_enum	policy,
		vx_image	output
	)

[Immediate] Remaps an output image from an input image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input `VX_DF_IMAGE_U8` image.
[in]	table	The remap table object.
[in]	policy	The interpolation policy from vx_interpolation_type_e. VX_INTERPOLATION_AREA is not supported.
[out]	output	The output `VX_DF_IMAGE_U8` image.

Returns: A vx_status_e enumeration.

◆ vxuScaleImage()

VX_API_ENTRY vx_status VX_API_CALL vxuScaleImage	(	vx_context	context,
		vx_image	src,
		vx_image	dst,
		vx_enum	type
	)

[Immediate] Scales an input image to an output image.

Parameters

[in]	context	The reference to the overall context.
[in]	src	The source image of type `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1`.
[out]	dst	The destination image of type `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1`. Must be of the same format as the input image.
[in]	type	The interpolation type.

See also: vx_interpolation_type_e.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuSobel3x3()

VX_API_ENTRY vx_status VX_API_CALL vxuSobel3x3	(	vx_context	context,
		vx_image	input,
		vx_image	output_x,
		vx_image	output_y
	)

[Immediate] Invokes an immediate Sobel 3x3.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` format.
[out]	output_x	[optional] The output gradient in the x direction in `VX_DF_IMAGE_S16`.
[out]	output_y	[optional] The output gradient in the y direction in `VX_DF_IMAGE_S16`.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuSubtract()

VX_API_ENTRY vx_status VX_API_CALL vxuSubtract	(	vx_context	context,
		vx_image	in1,
		vx_image	in2,
		vx_enum	policy,
		vx_image	out
	)

[Immediate] Performs arithmetic subtraction on pixel values in the input images.

Parameters

[in]	context	The reference to the overall context.
[in]	in1	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` input image, the minuend.
[in]	in2	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` input image, the subtrahend.
[in]	policy	A vx_convert_policy_e enumeration.
[out]	out	The output image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16` format.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuTableLookup()

VX_API_ENTRY vx_status VX_API_CALL vxuTableLookup	(	vx_context	context,
		vx_image	input,
		vx_lut	lut,
		vx_image	output
	)

[Immediate] Processes the image through the LUT.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image in `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_S16`.
[in]	lut	The LUT which is of type `VX_TYPE_UINT8` if input image is `VX_DF_IMAGE_U8` or `VX_TYPE_INT16` if input image is `VX_DF_IMAGE_S16`.
[out]	output	The output image of the same size as the input image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuTensorAdd()

VX_API_ENTRY vx_status VX_API_CALL vxuTensorAdd	(	vx_context	context,
		vx_tensor	input1,
		vx_tensor	input2,
		vx_enum	policy,
		vx_tensor	output
	)

[Immediate] Performs arithmetic addition on element values in the input tensor data.

Parameters

[in]	context	The reference to the overall context.
[in]	input1	Input tensor data. Implementations must support input tensor data type `VX_TYPE_INT16` with fixed_point_position 8, and tensor data types `VX_TYPE_UINT8` and `VX_TYPE_INT8`, with fixed_point_position 0.
[in]	input2	Input tensor data. The dimensions and sizes of input2 match those of input1, unless the vx_tensor of one or more dimensions in input2 is 1. In this case, those dimensions are treated as if this tensor was expanded to match the size of the corresponding dimension of input1, and data was duplicated on all terms in that dimension. After this expansion, the dimensions will be equal. The data type must match the data type of Input1.
[in]	policy	A `vx_convert_policy_e` enumeration.
[out]	output	The output tensor data with the same dimensions as the input tensor data.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuTensorConvertDepth()

VX_API_ENTRY vx_status VX_API_CALL vxuTensorConvertDepth	(	vx_context	context,
		vx_tensor	input,
		vx_enum	policy,
		vx_scalar	norm,
		vx_scalar	offset,
		vx_tensor	output
	)

[Immediate] Performs a bit-depth conversion.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input tensor. Implementations must support input tensor data type `VX_TYPE_INT16` with fixed_point_position 8, and tensor data types `VX_TYPE_UINT8` and `VX_TYPE_INT8`, with fixed_point_position 0.
[in]	policy	A `VX_TYPE_ENUM` of the `vx_convert_policy_e` enumeration.
[in]	norm	A scalar containing a `VX_TYPE_FLOAT32` of the normalization value.
[in]	offset	A scalar containing a `VX_TYPE_FLOAT32` of the offset value subtracted before normalization.
[out]	output	The output tensor. Implementations must support input tensor data type `VX_TYPE_INT16`. with fixed_point_position 8. And `VX_TYPE_UINT8` with fixed_point_position 0.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuTensorMatrixMultiply()

VX_API_ENTRY vx_status VX_API_CALL vxuTensorMatrixMultiply	(	vx_context	context,
		vx_tensor	input1,
		vx_tensor	input2,
		vx_tensor	input3,
		const vx_tensor_matrix_multiply_params_t *	matrix_multiply_params,
		vx_tensor	output
	)

[Immediate] Performs a generalized matrix multiplication.

Parameters

[in]	context	The reference to the overall context.
[in]	input1	The first input 2D tensor of type `VX_TYPE_INT16` with fixed_point_pos 8, or tensor data types `VX_TYPE_UINT8` or `VX_TYPE_INT8`, with fixed_point_pos 0.
[in]	input2	The second 2D tensor. Must be in the same data type as input1.
[in]	input3	The third 2D tensor. Must be in the same data type as input1. [optional].
[in]	matrix_multiply_params	Matrix multiply parameters, see `vx_tensor_matrix_multiply_params_t` .
[out]	output	The output 2D tensor. Must be in the same data type as input1. Output dimension must agree the formula in the description.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuTensorMultiply()

VX_API_ENTRY vx_status VX_API_CALL vxuTensorMultiply	(	vx_context	context,
		vx_tensor	input1,
		vx_tensor	input2,
		vx_scalar	scale,
		vx_enum	overflow_policy,
		vx_enum	rounding_policy,
		vx_tensor	output
	)

[Immediate] Performs element wise multiplications on element values in the input tensor data with a scale.

Parameters

[in]	context	The reference to the overall context.
[in]	input1	Input tensor data. Implementations must support input tensor data type `VX_TYPE_INT16` with fixed_point_position 8, and tensor data types `VX_TYPE_UINT8` and `VX_TYPE_INT8`, with fixed_point_position 0.
[in]	input2	Input tensor data. The dimensions and sizes of input2 match those of input1, unless the vx_tensor of one or more dimensions in input2 is 1. In this case, those dimensions are treated as if this tensor was expanded to match the size of the corresponding dimension of input1, and data was duplicated on all terms in that dimension. After this expansion, the dimensions will be equal. The data type must match the data type of Input1.
[in]	scale	A non-negative `VX_TYPE_FLOAT32` multiplied to each product before overflow handling.
[in]	overflow_policy	A `vx_convert_policy_e` enumeration.
[in]	rounding_policy	A `vx_round_policy_e` enumeration.
[out]	output	The output tensor data with the same dimensions as the input tensor data.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuTensorSubtract()

VX_API_ENTRY vx_status VX_API_CALL vxuTensorSubtract	(	vx_context	context,
		vx_tensor	input1,
		vx_tensor	input2,
		vx_enum	policy,
		vx_tensor	output
	)

[Immediate] Performs arithmetic subtraction on element values in the input tensor data.

Parameters

[in]	context	The reference to the overall context.
[in]	input1	Input tensor data. Implementations must support input tensor data type `VX_TYPE_INT16` with fixed_point_position 8, and tensor data types `VX_TYPE_UINT8` and `VX_TYPE_INT8`, with fixed_point_position 0.
[in]	input2	Input tensor data. The dimensions and sizes of input2 match those of input1, unless the vx_tensor of one or more dimensions in input2 is 1. In this case, those dimensions are treated as if this tensor was expanded to match the size of the corresponding dimension of input1, and data was duplicated on all terms in that dimension. After this expansion, the dimensions will be equal. The data type must match the data type of Input1.
[in]	policy	A `vx_convert_policy_e` enumeration.
[out]	output	The output tensor data with the same dimensions as the input tensor data.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuTensorTableLookup()

VX_API_ENTRY vx_status VX_API_CALL vxuTensorTableLookup	(	vx_context	context,
		vx_tensor	input1,
		vx_lut	lut,
		vx_tensor	output
	)

[Immediate] Performs LUT on element values in the input tensor data.

Parameters

[in]	context	The reference to the overall context.
[in]	input1	Input tensor data. Implementations must support input tensor data type `VX_TYPE_INT16` with fixed_point_position 8, and tensor data types `VX_TYPE_UINT8`, with fixed_point_position 0.
[in]	lut	The look-up table to use, of type `vx_lut`. The elements of input1 are treated as unsigned integers to determine an index into the look-up table. The data type of the items in the look-up table must match that of the output tensor.
[out]	output	The output tensor data with the same dimensions as the input tensor data.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuTensorTranspose()

VX_API_ENTRY vx_status VX_API_CALL vxuTensorTranspose	(	vx_context	context,
		vx_tensor	input,
		vx_tensor	output,
		vx_size	dimension1,
		vx_size	dimension2
	)

[Immediate] Performs transpose on the input tensor. The tensor is transposed according to a specified 2 indexes in the tensor (0-based indexing)

Parameters

[in]	context	The reference to the overall context.
[in]	input	Input tensor data, Implementations must support input tensor data type `VX_TYPE_INT16` with fixed_point_position 8, and tensor data types `VX_TYPE_UINT8` and `VX_TYPE_INT8`, with fixed_point_position 0.
[out]	output	output tensor data,
[in]	dimension1	Dimension index that is transposed with dim 2.
[in]	dimension2	Dimension index that is transposed with dim 1.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuThreshold()

VX_API_ENTRY vx_status VX_API_CALL vxuThreshold	(	vx_context	context,
		vx_image	input,
		vx_threshold	thresh,
		vx_image	output
	)

[Immediate] Threshold's an input image and produces a VX_DF_IMAGE_U8 boolean image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input image. Only images with format `VX_DF_IMAGE_U8` and `VX_DF_IMAGE_S16` are supported.
[in]	thresh	The thresholding object that defines the parameters of the operation. The `VX_THRESHOLD_INPUT_FORMAT` must be the same as the input image format and the `VX_THRESHOLD_OUTPUT_FORMAT` must be the same as the output image format.
[out]	output	The output image, that will contain as pixel values true and false values defined by `thresh`. Only images with format `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` are supported. Must be of the same size as the input image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuWarpAffine()

VX_API_ENTRY vx_status VX_API_CALL vxuWarpAffine	(	vx_context	context,
		vx_image	input,
		vx_matrix	matrix,
		vx_enum	type,
		vx_image	output
	)

[Immediate] Performs an Affine warp on an image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input `VX_DF_IMAGE_U1` or `VX_DF_IMAGE_U8` image.
[in]	matrix	The affine matrix. Must be 2x3 of type VX_TYPE_FLOAT32.
[in]	type	The interpolation type from vx_interpolation_type_e. VX_INTERPOLATION_AREA is not supported.
[out]	output	The output `VX_DF_IMAGE_U1` or `VX_DF_IMAGE_U8` image of the same format as the input image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuWarpPerspective()

VX_API_ENTRY vx_status VX_API_CALL vxuWarpPerspective	(	vx_context	context,
		vx_image	input,
		vx_matrix	matrix,
		vx_enum	type,
		vx_image	output
	)

[Immediate] Performs an Perspective warp on an image.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input `VX_DF_IMAGE_U8` image.
[in]	matrix	The perspective matrix. Must be 3x3 of type VX_TYPE_FLOAT32.
[in]	type	The interpolation type from vx_interpolation_type_e. VX_INTERPOLATION_AREA is not supported.
[out]	output	The output `VX_DF_IMAGE_U8` image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuWeightedAverage()

VX_API_ENTRY vx_status VX_API_CALL vxuWeightedAverage	(	vx_context	context,
		vx_image	img1,
		vx_scalar	alpha,
		vx_image	img2,
		vx_image	output
	)

[Immediate] Computes a weighted average image.

Parameters

[in]	context	The reference to the overall context.
[in]	img1	The first `VX_DF_IMAGE_U8` image.
[in]	alpha	A `VX_TYPE_FLOAT32` type, the input value with the range $0.0 \le \alpha \le 1.0$ .
[in]	img2	The second `VX_DF_IMAGE_U8` image.
[out]	output	The output `VX_DF_IMAGE_U8` image.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

◆ vxuXor()

VX_API_ENTRY vx_status VX_API_CALL vxuXor	(	vx_context	context,
		vx_image	in1,
		vx_image	in2,
		vx_image	out
	)

[Immediate] Computes the bitwise exclusive-or between two images.

Parameters

[in]	context	The reference to the overall context.
[in]	in1	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` input image.
[in]	in2	A `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` input image.
[out]	out	The `VX_DF_IMAGE_U8` or `VX_DF_IMAGE_U1` output image, which must have the same dimensions and type as the input images.

Returns: A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See `vx_status_e`.

/home/docs/checkouts/readthedocs.org/user_builds/advanced-micro-devices-mivisionx/checkouts/docs-5.7.1/amd_openvx/openvx/include/VX/vxu.h File Reference

/home/docs/checkouts/readthedocs.org/user_builds/advanced-micro-devices-mivisionx/checkouts/docs-5.7.1/amd_openvx/openvx/include/VX/vxu.h File Reference#

Functions

Detailed Description

Function Documentation

◆ vxuAbsDiff()

◆ vxuAdd()

◆ vxuAnd()

◆ vxuBilateralFilter()

◆ vxuBox3x3()

◆ vxuCannyEdgeDetector()

◆ vxuChannelCombine()

◆ vxuChannelExtract()

◆ vxuColorConvert()

◆ vxuConvertDepth()

◆ vxuConvolve()

◆ vxuCopy()

◆ vxuDilate3x3()

◆ vxuEqualizeHist()

◆ vxuErode3x3()

◆ vxuFastCorners()

◆ vxuGaussian3x3()

◆ vxuGaussianPyramid()

◆ vxuHalfScaleGaussian()

◆ vxuHarrisCorners()

◆ vxuHistogram()

◆ vxuHOGCells()

◆ vxuHOGFeatures()

◆ vxuHoughLinesP()

◆ vxuIntegralImage()

◆ vxuLaplacianPyramid()

◆ vxuLaplacianReconstruct()

◆ vxuLBP()

◆ vxuMagnitude()

◆ vxuMatchTemplate()

◆ vxuMax()

◆ vxuMeanStdDev()

◆ vxuMedian3x3()

◆ vxuMin()

◆ vxuMinMaxLoc()

◆ vxuMultiply()

◆ vxuNonLinearFilter()

◆ vxuNonMaxSuppression()

◆ vxuNot()

◆ vxuOpticalFlowPyrLK()

◆ vxuOr()

◆ vxuPhase()

◆ vxuRemap()

◆ vxuScaleImage()

◆ vxuSobel3x3()

◆ vxuSubtract()

◆ vxuTableLookup()

◆ vxuTensorAdd()

◆ vxuTensorConvertDepth()

◆ vxuTensorMatrixMultiply()

◆ vxuTensorMultiply()

◆ vxuTensorSubtract()

◆ vxuTensorTableLookup()

◆ vxuTensorTranspose()

◆ vxuThreshold()

◆ vxuWarpAffine()

◆ vxuWarpPerspective()

◆ vxuWeightedAverage()

◆ vxuXor()