View Source Evision.CUDA (Evision v0.1.9)

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cv.cuda

Creates a continuous matrix.

Creates a continuous matrix.

Ensures that the size of a matrix is big enough and the matrix has a proper type.

Ensures that the size of a matrix is big enough and the matrix has a proper type.

Returns the number of installed CUDA-enabled devices.

Returns the current device index set by cuda::setDevice or initialized by default.

Positional Arguments
  • device: int

Python prototype (for reference):

Positional Arguments
  • device: int

Python prototype (for reference):

Page-locks the memory of matrix and maps it for the device(s).

Explicitly destroys and cleans up all resources associated with the current device in the current process.

Positional Arguments
  • deviceId: int
  • stackSize: size_t
  • stackCount: int

Python prototype (for reference):

Positional Arguments
  • on: bool

Python prototype (for reference):

Sets a device and initializes it for the current thread.

Unmaps the memory of matrix and makes it pageable again.

Link to this section cv.cuda

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createContinuous(rows, cols, type)

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Creates a continuous matrix.

Positional Arguments
  • rows: int.

    Row count.

  • cols: int.

    Column count.

  • type: int.

    Type of the matrix.

Return
  • arr: Evision.Mat.

    Destination matrix. This parameter changes only if it has a proper type and area ( \f$\texttt{rows} \times \texttt{cols}\f$ ).

Matrix is called continuous if its elements are stored continuously, that is, without gaps at the end of each row.

Python prototype (for reference):

createContinuous(rows, cols, type[, arr]) -> arr
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createContinuous(rows, cols, type, opts)

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Creates a continuous matrix.

Positional Arguments
  • rows: int.

    Row count.

  • cols: int.

    Column count.

  • type: int.

    Type of the matrix.

Return
  • arr: Evision.Mat.

    Destination matrix. This parameter changes only if it has a proper type and area ( \f$\texttt{rows} \times \texttt{cols}\f$ ).

Matrix is called continuous if its elements are stored continuously, that is, without gaps at the end of each row.

Python prototype (for reference):

createContinuous(rows, cols, type[, arr]) -> arr
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ensureSizeIsEnough(rows, cols, type)

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Ensures that the size of a matrix is big enough and the matrix has a proper type.

Positional Arguments
  • rows: int.

    Minimum desired number of rows.

  • cols: int.

    Minimum desired number of columns.

  • type: int.

    Desired matrix type.

Return

The function does not reallocate memory if the matrix has proper attributes already.

Python prototype (for reference):

ensureSizeIsEnough(rows, cols, type[, arr]) -> arr
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ensureSizeIsEnough(rows, cols, type, opts)

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Ensures that the size of a matrix is big enough and the matrix has a proper type.

Positional Arguments
  • rows: int.

    Minimum desired number of rows.

  • cols: int.

    Minimum desired number of columns.

  • type: int.

    Desired matrix type.

Return

The function does not reallocate memory if the matrix has proper attributes already.

Python prototype (for reference):

ensureSizeIsEnough(rows, cols, type[, arr]) -> arr
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getCudaEnabledDeviceCount()

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Returns the number of installed CUDA-enabled devices.

Use this function before any other CUDA functions calls. If OpenCV is compiled without CUDA support, this function returns 0. If the CUDA driver is not installed, or is incompatible, this function returns -1.

Python prototype (for reference):

getCudaEnabledDeviceCount() -> retval

Returns the current device index set by cuda::setDevice or initialized by default.

Python prototype (for reference):

getDevice() -> retval
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printCudaDeviceInfo(device)

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Positional Arguments
  • device: int

Python prototype (for reference):

printCudaDeviceInfo(device) -> None
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printShortCudaDeviceInfo(device)

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Positional Arguments
  • device: int

Python prototype (for reference):

printShortCudaDeviceInfo(device) -> None

Page-locks the memory of matrix and maps it for the device(s).

Positional Arguments

Python prototype (for reference):

registerPageLocked(m) -> None

Explicitly destroys and cleans up all resources associated with the current device in the current process.

Any subsequent API call to this device will reinitialize the device.

Python prototype (for reference):

resetDevice() -> None
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setBufferPoolConfig(deviceId, stackSize, stackCount)

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Positional Arguments
  • deviceId: int
  • stackSize: size_t
  • stackCount: int

Python prototype (for reference):

setBufferPoolConfig(deviceId, stackSize, stackCount) -> None
Positional Arguments
  • on: bool

Python prototype (for reference):

setBufferPoolUsage(on) -> None

Sets a device and initializes it for the current thread.

Positional Arguments
  • device: int.

    System index of a CUDA device starting with 0.

If the call of this function is omitted, a default device is initialized at the fist CUDA usage.

Python prototype (for reference):

setDevice(device) -> None

Unmaps the memory of matrix and makes it pageable again.

Positional Arguments

Python prototype (for reference):

unregisterPageLocked(m) -> None

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createContinuous!(rows, cols, type)

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Raising version of createContinuous/3.

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createContinuous!(rows, cols, type, opts)

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Raising version of createContinuous/4.

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ensureSizeIsEnough!(rows, cols, type)

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Raising version of ensureSizeIsEnough/3.

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ensureSizeIsEnough!(rows, cols, type, opts)

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Raising version of ensureSizeIsEnough/4.

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getCudaEnabledDeviceCount!()

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Raising version of getCudaEnabledDeviceCount/0.

Raising version of getDevice/0.

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printCudaDeviceInfo!(device)

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Raising version of printCudaDeviceInfo/1.

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printShortCudaDeviceInfo!(device)

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Raising version of printShortCudaDeviceInfo/1.

Raising version of registerPageLocked/1.

Raising version of resetDevice/0.

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setBufferPoolConfig!(deviceId, stackSize, stackCount)

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Raising version of setBufferPoolConfig/3.

Raising version of setBufferPoolUsage/1.

Raising version of setDevice/1.

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unregisterPageLocked!(m)

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Raising version of unregisterPageLocked/1.