▼Vision Functions | These are the base vision functions supported in OpenVX 1.1 |
Absolute Difference | Computes the absolute difference between two images. The output image dimensions should be the same as the dimensions of the input images |
Accumulate | Accumulates an input image into output image. The accumulation image dimensions should be the same as the dimensions of the input image |
Accumulate Squared | Accumulates a squared value from an input image to an output image. The accumulation image dimensions should be the same as the dimensions of the input image |
Data Object Copy | Copy a data object to another |
Accumulate Weighted | Accumulates a weighted value from an input image to an output image. The accumulation image dimensions should be the same as the dimensions of the input image |
Arithmetic Addition | Performs addition between two images. The output image dimensions should be the same as the dimensions of the input images |
Arithmetic Subtraction | Performs subtraction between two images. The output image dimensions should be the same as the dimensions of the input images |
Bitwise AND | Performs a bitwise AND operation between two VX_DF_IMAGE_U8 images. The output image dimensions should be the same as the dimensions of the input images |
Bitwise EXCLUSIVE OR | Performs a bitwise EXCLUSIVE OR (XOR) operation between two VX_DF_IMAGE_U8 images. The output image dimensions should be the same as the dimensions of the input images |
Bitwise INCLUSIVE OR | Performs a bitwise INCLUSIVE OR operation between two VX_DF_IMAGE_U8 images. The output image dimensions should be the same as the dimensions of the input images |
Bitwise NOT | Performs a bitwise NOT operation on a VX_DF_IMAGE_U8 input image. The output image dimensions should be the same as the dimensions of the input image |
Box Filter | Computes a Box filter over a window of the input image. The output image dimensions should be the same as the dimensions of the input image |
Non-Maxima Suppression | Find local maxima in an image, or otherwise suppress pixels that are not local maxima |
Canny Edge Detector | Provides a Canny edge detector kernel. The output image dimensions should be the same as the dimensions of the input image |
Channel Combine | Implements the Channel Combine Kernel |
Channel Extract | Implements the Channel Extraction Kernel |
Color Convert | Implements the Color Conversion Kernel. The output image dimensions should be the same as the dimensions of the input image |
Convert Bit depth | Converts image bit depth. The output image dimensions should be the same as the dimensions of the input image |
Custom Convolution | Convolves the input with the client supplied convolution matrix. The output image dimensions should be the same as the dimensions of the input image |
Dilate Image | Implements Dilation, which grows the white space in a VX_DF_IMAGE_U8 Boolean image. The output image dimensions should be the same as the dimensions of the input image |
Equalize Histogram | Equalizes the histogram of a grayscale image. The output image dimensions should be the same as the dimensions of the input image |
Erode Image | Implements Erosion, which shrinks the white space in a VX_DF_IMAGE_U8 Boolean image. The output image dimensions should be the same as the dimensions of the input image |
Fast Corners | Computes the corners in an image using a method based upon FAST9 algorithm suggested in [3] and with some updates from [4] with modifications described below |
Gaussian Filter | Computes a Gaussian filter over a window of the input image. The output image dimensions should be the same as the dimensions of the input image |
Non Linear Filter | Computes a non-linear filter over a window of the input image. The output image dimensions should be the same as the dimensions of the input image |
Harris Corners | Computes the Harris Corners of an image |
Histogram | Generates a distribution from an image |
Gaussian Image Pyramid | Computes a Gaussian Image Pyramid from an input image |
Laplacian Image Pyramid | Computes a Laplacian Image Pyramid from an input image |
Reconstruction from a Laplacian Image Pyramid | Reconstructs the original image from a Laplacian Image Pyramid |
Integral Image | Computes the integral image of the input. The output image dimensions should be the same as the dimensions of the input image |
Magnitude | Implements the Gradient Magnitude Computation Kernel. The output image dimensions should be the same as the dimensions of the input images |
Mean and Standard Deviation | Computes the mean pixel value and the standard deviation of the pixels in the input image (which has a dimension width and height) |
Median Filter | Computes a median pixel value over a window of the input image. The output image dimensions should be the same as the dimensions of the input image |
Min, Max Location | Finds the minimum and maximum values in an image and a location for each |
Min | Implements a pixel-wise minimum kernel. The output image dimensions should be the same as the dimensions of the input image |
Max | Implements a pixel-wise maximum kernel. The output image dimensions should be the same as the dimensions of the input image |
Optical Flow Pyramid (LK) | Computes the optical flow using the Lucas-Kanade method between two pyramid images |
Phase | Implements the Gradient Phase Computation Kernel. The output image dimensions should be the same as the dimensions of the input images |
Pixel-wise Multiplication | Performs element-wise multiplication between two images and a scalar value. The output image dimensions should be the same as the dimensions of the input images |
Remap | Maps output pixels in an image from input pixels in an image |
Scale Image | Implements the Image Resizing Kernel |
Sobel 3x3 | Implements the Sobel Image Filter Kernel. The output images dimensions should be the same as the dimensions of the input image |
TableLookup | Implements the Table Lookup Image Kernel. The output image dimensions should be the same as the dimensions of the input image |
Thresholding | Thresholds an input image and produces an output Boolean image. The output image dimensions should be the same as the dimensions of the input image |
Warp Affine | Performs an affine transform on an image |
Warp Perspective | Performs a perspective transform on an image |
Bilateral Filter | The function applies bilateral filtering to the input tensor |
MatchTemplate | Compares an image template against overlapped image regions |
LBP | Extracts LBP image from an input image. The output image dimensions should be the same as the dimensions of the input image |
HOG | Extracts Histogram of Oriented Gradients features from the input grayscale image |
HoughLinesP | Finds the Probabilistic Hough Lines detected in the input binary image |
Tensor Multiply | Performs element wise multiplications on element values in the input tensor data with a scale |
Tensor Add | Performs arithmetic addition on element values in the input tensor data |
Tensor Subtract | Performs arithmetic subtraction on element values in the input tensor data |
Tensor TableLookUp | Performs LUT on element values in the input tensor data |
Tensor Transpose | Performs transpose on the input tensor |
Tensor Convert Bit-Depth | Creates a bit-depth conversion node |
Tensor Matrix Multiply | Creates a generalized matrix multiplication node |
Control Flow | Defines the predicated execution model of OpenVX |
▼Basic Features | The basic parts of OpenVX needed for computation |
▼Objects | Defines the basic objects within OpenVX |
Object: Reference | Defines the Reference Object interface |
Object: Context | Defines the Context Object Interface |
Object: Graph | Defines the Graph Object interface |
Object: Node | Defines the Node Object interface |
Object: Array | Defines the Array Object Interface |
Object: Convolution | Defines the Image Convolution Object interface |
Object: Distribution | Defines the Distribution Object Interface |
Object: Image | Defines the Image Object interface |
Object: LUT | Defines the Look-Up Table Interface |
Object: Matrix | Defines the Matrix Object Interface |
Object: Pyramid | Defines the Image Pyramid Object Interface |
Object: Remap | Defines the Remap Object Interface |
Object: Scalar | Defines the Scalar Object interface |
Object: Threshold | Defines the Threshold Object Interface |
Object: ObjectArray | An opaque array object that could be an array of any data-object (not data-type) of OpenVX except Delay and ObjectArray objects |
Object: Tensor | Defines The Tensor Object Interface |
▼Administrative Features | Defines the Administrative Features of OpenVX |
▼Advanced Objects | Defines the Advanced Objects of OpenVX |
Object: Array (Advanced) | Defines the advanced features of the Array Interface |
▼Object: Node (Advanced) | Defines the advanced features of the Node Interface |
Node: Border Modes | Defines the border mode behaviors |
Object: Delay | Defines the Delay Object interface |
Object: Kernel | Defines the Kernel Object and Interface |
Object: Parameter | Defines the Parameter Object interface |
▼Advanced Framework API | Describes components that are considered to be advanced |
Framework: Node Callbacks | Allows Clients to receive a callback after a specific node has completed execution |
Framework: Performance Measurement | Defines Performance measurement and reporting interfaces |
Framework: Log | Defines the debug logging interface |
Framework: Hints | Defines the Hints Interface |
Framework: Directives | Defines the Directives Interface |
Framework: User Kernels | Defines the User Kernels, which are a method to extend OpenVX with new vision functions |
Framework: Graph Parameters | Defines the Graph Parameter API |