RPP filter augmentations

RppStatus rppt_box_filter(RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32u kernelSize, RpptImageBorderType borderType, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)

Box Filter augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor.

The box filter augmentation runs for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.

• srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).

• dstPtr depth ranges - Will be same depth as srcPtr.

  

  Sample Input

  

  Sample 3x3 Output

  

  Sample 5x5 Output

  

  Sample 7x7 Output

  

  Sample 9x9 Output

Parameters:

• srcPtr – [in] source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• srcDescPtr – [in] source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)

• dstPtr – [out] destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• dstDescPtr – [in] destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)

• kernelSize – [in] kernel size for box filter (a single Rpp32u number with kernelSize > 0 that applies to all images in the batch. kernelSize = 3/5/7/9 are optimized to run faster)

• borderType – [in] border type for padding during filtering (Restrictions - RpptImageBorderType::REPLICATE only mode supported)

• roiTensorPtrSrc – [in] ROI data in HIP memory (for HIP backend) or HOST memory (for HOST backend), for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y))

• roiType – [in] ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)

• rppHandle – [in] RPP HIP/HOST handle created with rppCreate()

• executionBackend – [in] backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Return values:

• RPP_SUCCESS – Successful completion.

• RPP_ERROR* – Unsuccessful completion.

Returns:

A RppStatus enumeration.

RppStatus rppt_median_filter(RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32u kernelSize, RpptImageBorderType borderType, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)

Median Filter augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor.

The median filter replaces each pixel’s value with the median of its surrounding pixels in a square window of size kernel size x kernel size. The Median filter augmentation runs for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.

• srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).

• dstPtr depth ranges - Will be same depth as srcPtr.

  

  Sample Input

  

  Sample 3x3 Output

  

  Sample 5x5 Output

  

  Sample 7x7 Output

  

  Sample 9x9 Output

Parameters:

• srcPtr – [in] source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• srcDescPtr – [in] source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)

• dstPtr – [out] destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• dstDescPtr – [in] destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)

• kernelSize – [in] kernel size for median filter (a single Rpp32u number with kernelSize > 0 that applies to all images in the batch. kernelSize = 3/5/7/9 are optimized to run faster)

• borderType – [in] Border type for padding in the median filter (currently, only RpptImageBorderType::REPLICATE is supported)

• roiTensorPtrSrc – [in] ROI data in HIP memory (for HIP backend) or HOST memory (for HOST backend), for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y))

• roiType – [in] ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)

• rppHandle – [in] RPP HIP/HOST handle created with rppCreate()

• executionBackend – [in] backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Return values:

• RPP_SUCCESS – Successful completion.

• RPP_ERROR* – Unsuccessful completion.

Returns:

A RppStatus enumeration.

RppStatus rppt_gaussian_filter(RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32f *stdDevTensor, Rpp32u kernelSize, RpptImageBorderType borderType, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)

Gaussian Filter augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor.

The Gaussian filter augmentation runs for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.

• srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).

• dstPtr depth ranges - Will be same depth as srcPtr.

  

  Sample Input

  

  Sample 3x3 Output

  

  Sample 5x5 Output

  

  Sample 7x7 Output

  

  Sample 9x9 Output

Parameters:

• srcPtr – [in] source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• srcDescPtr – [in] source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)

• dstPtr – [out] destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• dstDescPtr – [in] destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)

• stdDevTensor – [in] stdDev values for gaussian calculation (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, for each image in batch)

• kernelSize – [in] kernel size for gaussian filter (a single Rpp32u number with kernelSize > 0 that applies to all images in the batch. kernelSize = 3/5/7/9 are optimized to run faster)

• borderType – [in] border type for padding during filtering (Restrictions - RpptImageBorderType::REPLICATE only mode supported)

• roiTensorPtrSrc – [in] ROI data in HIP memory (for HIP backend) or HOST memory (for HOST backend), for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y))

• roiType – [in] ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)

• rppHandle – [in] RPP HIP/HOST handle created with rppCreate()

• executionBackend – [in] backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Return values:

• RPP_SUCCESS – Successful completion.

• RPP_ERROR* – Unsuccessful completion.

Returns:

A RppStatus enumeration.

RppStatus rppt_sobel_filter(RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32u sobelType, Rpp32u kernelSize, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)

Sobel Filter augmentation on HIP/HOST backend for a NHWC/NCHW layout tensor.

The sobel filter augmentation runs for a batch of RGB(3 channel) / greyscale(1 channel) images with NHWC/NCHW tensor layout.

• srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).

• dstPtr depth ranges - Will be same depth as srcPtr.

  

  Sample Input

  

  Sample 3x3 Output

  

  Sample 5x5 Output

  

  Sample 7x7 Output

  

  Sample 3x3 Output

  

  Sample 5x5 Output

  

  Sample 7x7 Output

  

  Sample 3x3 Output

  

  Sample 5x5 Output

  

  Sample 7x7 Output

Parameters:

• srcPtr – [in] source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• srcDescPtr – [in] source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)

• dstPtr – [out] destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• dstDescPtr – [in] destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW, c = 1)

• sobelType – [in] sobel type for sobel filter (a single Rpp32u number with sobelType = 0 (X Gradient) / 1 (Y Gradient) / 2 (XY Gradient) that applies to all images in the batch)

• kernelSize – [in] kernel size for sobel filter (a single Rpp32u odd number with kernelSize = 3/5/7 that applies to all images in the batch)

• roiTensorPtrSrc – [in] ROI data in HIP memory (for HIP backend) or HOST memory (for HOST backend), for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y))

• roiType – [in] ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)

• rppHandle – [in] RPP HIP/HOST handle created with rppCreate()

• executionBackend – [in] backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Return values:

• RPP_SUCCESS – Successful completion.

• RPP_ERROR* – Unsuccessful completion.

Returns:

A RppStatus enumeration.

RppStatus rppt_emboss(RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32f *strength, Rpp32u kernelSize, RpptImageBorderType borderType, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)

Emboss augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor.

The emboss augmentation runs for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.

• srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).

• dstPtr depth ranges - Will be same depth as srcPtr.

  

  Sample Input

  

  Sample 3x3 Output

  

  Sample 5x5 Output

  

  Sample 7x7 Output

  

  Sample 9x9 Output

Parameters:

• srcPtr – [in] source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• srcDescPtr – [in] source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)

• dstPtr – [out] destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)

• dstDescPtr – [in] destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)

• strength – [in] strength values for emboss calculation (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, for each image in batch)

• kernelSize – [in] kernel size for emboss (a single Rpp32u odd number with kernelSize = 3/5/7/9 that applies to all images in the batch)

• borderType – [in] border type for padding during filtering (Restrictions - RpptImageBorderType::REPLICATE only mode supported)

• roiTensorPtrSrc – [in] ROI data in HIP memory (for HIP backend) or HOST memory (for HOST backend), for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y))

• roiType – [in] ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)

• rppHandle – [in] RPP HIP/HOST handle created with rppCreate()

• executionBackend – [in] backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Return values:

• RPP_SUCCESS – Successful completion.

• RPP_ERROR* – Unsuccessful completion.

Returns:

A RppStatus enumeration.