@Namespace(value="cv::cuda") public static class opencv_cudaarithm.Convolution extends opencv_core.Algorithm
| Constructor and Description |
|---|
Convolution(org.bytedeco.javacpp.Pointer p)
Pointer cast constructor.
|
| Modifier and Type | Method and Description |
|---|---|
void |
convolve(opencv_core.GpuMat image,
opencv_core.GpuMat templ,
opencv_core.GpuMat result) |
void |
convolve(opencv_core.GpuMat image,
opencv_core.GpuMat templ,
opencv_core.GpuMat result,
boolean ccorr,
opencv_core.Stream stream) |
void |
convolve(opencv_core.Mat image,
opencv_core.Mat templ,
opencv_core.Mat result) |
void |
convolve(opencv_core.Mat image,
opencv_core.Mat templ,
opencv_core.Mat result,
boolean ccorr,
opencv_core.Stream stream)
\brief Computes a convolution (or cross-correlation) of two images.
|
void |
convolve(opencv_core.UMat image,
opencv_core.UMat templ,
opencv_core.UMat result) |
void |
convolve(opencv_core.UMat image,
opencv_core.UMat templ,
opencv_core.UMat result,
boolean ccorr,
opencv_core.Stream stream) |
clear, empty, getDefaultName, position, read, save, save, write, write, writeaddress, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zeropublic Convolution(org.bytedeco.javacpp.Pointer p)
Pointer.Pointer(Pointer).public void convolve(@ByVal
opencv_core.Mat image,
@ByVal
opencv_core.Mat templ,
@ByVal
opencv_core.Mat result,
@Cast(value="bool")
boolean ccorr,
@ByRef(nullValue="cv::cuda::Stream::Null()")
opencv_core.Stream stream)
image - Source image. Only CV_32FC1 images are supported for now.templ - Template image. The size is not greater than the image size. The type is the same as
image .result - Result image. If image is *W x H* and templ is *w x h*, then result must be *W-w+1 x
H-h+1*.ccorr - Flags to evaluate cross-correlation instead of convolution.stream - Stream for the asynchronous version.public void convolve(@ByVal
opencv_core.Mat image,
@ByVal
opencv_core.Mat templ,
@ByVal
opencv_core.Mat result)
public void convolve(@ByVal
opencv_core.UMat image,
@ByVal
opencv_core.UMat templ,
@ByVal
opencv_core.UMat result,
@Cast(value="bool")
boolean ccorr,
@ByRef(nullValue="cv::cuda::Stream::Null()")
opencv_core.Stream stream)
public void convolve(@ByVal
opencv_core.UMat image,
@ByVal
opencv_core.UMat templ,
@ByVal
opencv_core.UMat result)
public void convolve(@ByVal
opencv_core.GpuMat image,
@ByVal
opencv_core.GpuMat templ,
@ByVal
opencv_core.GpuMat result,
@Cast(value="bool")
boolean ccorr,
@ByRef(nullValue="cv::cuda::Stream::Null()")
opencv_core.Stream stream)
public void convolve(@ByVal
opencv_core.GpuMat image,
@ByVal
opencv_core.GpuMat templ,
@ByVal
opencv_core.GpuMat result)
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