RPPT Tensor Operations - Geometric Augmentations.

RPPT Tensor Operations - Geometric Augmentations.#

RPP: RPPT Tensor Operations - Geometric Augmentations.

RPPT Tensor Operations - Geometric Augmentations. More...

Functions
RppStatus	rppt_crop (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Crop augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_crop_mirror_normalize (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32f offsetTensor, Rpp32f multiplierTensor, Rpp32u *mirrorTensor, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Crop mirror normalize augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_warp_affine (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32f *affineTensor, RpptInterpolationType interpolationType, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Warp affine augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_flip (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32u horizontalTensor, Rpp32u verticalTensor, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Flip augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_resize (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptImagePatchPtr dstImgSizes, RpptInterpolationType interpolationType, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Resize augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_resize_mirror_normalize (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptImagePatchPtr dstImgSizes, RpptInterpolationType interpolationType, Rpp32f meanTensor, Rpp32f stdDevTensor, Rpp32u *mirrorTensor, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Resize mirror normalize augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_resize_crop_mirror (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptImagePatchPtr dstImgSizes, RpptInterpolationType interpolationType, Rpp32u *mirrorTensor, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Resize crop mirror augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_rotate (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32f *angle, RpptInterpolationType interpolationType, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Rotate augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_phase (RppPtr_t srcPtr1, RppPtr_t srcPtr2, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Phase augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_slice (RppPtr_t srcPtr, RpptGenericDescPtr srcGenericDescPtr, RppPtr_t dstPtr, RpptGenericDescPtr dstGenericDescPtr, Rpp32s anchorTensor, Rpp32s shapeTensor, RppPtr_t fillValue, bool enablePadding, Rpp32u *roiTensor, rppHandle_t rppHandle, RppBackend executionBackend)
	Slice augmentation on HIP/HOST backend. More...

RppStatus	rppt_crop_and_patch (RppPtr_t srcPtr1, RppPtr_t srcPtr2, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptROIPtr roiTensorPtrDst, RpptROIPtr cropRoiTensor, RpptROIPtr patchRoiTensor, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Crop and Patch augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_flip_voxel (RppPtr_t srcPtr, RpptGenericDescPtr srcGenericDescPtr, RppPtr_t dstPtr, RpptGenericDescPtr dstGenericDescPtr, Rpp32u horizontalTensor, Rpp32u verticalTensor, Rpp32u *depthTensor, RpptROI3DPtr roiGenericPtrSrc, RpptRoi3DType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Flip voxel augmentation on HIP/HOST backend. More...

RppStatus	rppt_remap (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32f rowRemapTable, Rpp32f colRemapTable, RpptDescPtr tableDescPtr, RpptInterpolationType interpolationType, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Remap augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_lens_correction (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32f rowRemapTable, Rpp32f colRemapTable, RpptDescPtr tableDescPtr, Rpp32f cameraMatrixTensor, Rpp32f distortionCoeffsTensor, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Lens correction transformation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_transpose (RppPtr_t srcPtr, RpptGenericDescPtr srcGenericDescPtr, RppPtr_t dstPtr, RpptGenericDescPtr dstGenericDescPtr, Rpp32u permTensor, Rpp32u roiTensor, rppHandle_t rppHandle, RppBackend executionBackend)
	Transpose Generic augmentation on HIP/HOST backend. More...

RppStatus	rppt_warp_perspective (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32f *perspectiveTensor, RpptInterpolationType interpolationType, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Warp perspective augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

RppStatus	rppt_concat (RppPtr_t srcPtr1, RppPtr_t srcPtr2, RpptGenericDescPtr srcPtr1GenericDescPtr, RpptGenericDescPtr srcPtr2GenericDescPtr, RppPtr_t dstPtr, RpptGenericDescPtr dstGenericDescPtr, Rpp32u axisMask, Rpp32u srcPtr1roiTensor, Rpp32u srcPtr2roiTensor, rppHandle_t rppHandle, RppBackend executionBackend)
	Concat Generic augmentation on HIP/HOST backend. More...

RppStatus	rppt_jpeg_compression_distortion (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, Rpp32s *qualityTensor, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	JPEG Compression Distortion on HIP/HOST backend. More...

RppStatus	rppt_fisheye (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle, RppBackend executionBackend)
	Fisheye augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor. More...

Detailed Description

RPPT Tensor Operations - Geometric Augmentations.

Function Documentation

◆ rppt_concat()

RppStatus rppt_concat	(	RppPtr_t	srcPtr1,
		RppPtr_t	srcPtr2,
		RpptGenericDescPtr	srcPtr1GenericDescPtr,
		RpptGenericDescPtr	srcPtr2GenericDescPtr,
		RppPtr_t	dstPtr,
		RpptGenericDescPtr	dstGenericDescPtr,
		Rpp32u	axisMask,
		Rpp32u *	srcPtr1roiTensor,
		Rpp32u *	srcPtr2roiTensor,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

Concat Generic augmentation on HIP/HOST backend.

Concatenates two 2D, 3D or ND tensors in HIP/HOST memory along a specified axis. It is optimized for 2D and 3D tensors, ensuring that all dimensions except the concatenation axis must match.

Parameters

[in]	srcPtr1	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcPtr2	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcPtr1GenericDescPtr	source tensor descriptor for the input tensor srcPtr1
[in]	srcPtr2GenericDescPtr	source tensor descriptor for the input tensor srcPtr2
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstGenericDescPtr	destination tensor descriptor
[in]	axisMask	axis along which concat needs to be done
[in]	srcPtr1roiTensor	values to represent dimensions of input tensor srcPtr1 in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcPtr2roiTensor	values to represent dimensions of input tensor srcPtr2 in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreateWithBatchSize()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_crop()

RppStatus rppt_crop	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

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

The crop augmentation crops each image to a given ROI, 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 Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_crop_and_patch()

RppStatus rppt_crop_and_patch	(	RppPtr_t	srcPtr1,
		RppPtr_t	srcPtr2,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		RpptROIPtr	roiTensorPtrDst,
		RpptROIPtr	cropRoiTensor,
		RpptROIPtr	patchRoiTensor,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

Crop and Patch augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor.

The crop and patch augmentation crops a ROI from 1st image and patches the cropped region in 2nd image as per the patch co-ordinates for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.

srcPtr1 depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
srcPtr2 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 Input1

Sample Input2

Sample Output

Parameters

[in]	srcPtr1	source tensor1 in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcPtr2	source tensor2 in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	roiTensorPtrDst	ROI data in HIP memory (for HIP backend) or HOST memory (for HOST backend), for each image in destination 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))
[in]	cropRoiTensor	crop co-ordinates 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))
[in]	patchRoiTensor	patch co-ordinates 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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	execution backend to run the augmentation on (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_crop_mirror_normalize()

RppStatus rppt_crop_mirror_normalize	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		Rpp32f *	offsetTensor,
		Rpp32f *	multiplierTensor,
		Rpp32u *	mirrorTensor,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

Crop mirror normalize augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor.

The crop mirror normalize augmentation crops each image to a given ROI, does an optional mirror and/or normalize 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 Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	offsetTensor	offset values for normalization (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with offsetTensor[n] <= 0)
[in]	multiplierTensor	multiplier values for normalization (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with multiplierTensor[n] > 0)
[in]	mirrorTensor	mirror flag values to set mirroring on/off (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with mirrorTensor[n] = 0/1)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_fisheye()

RppStatus rppt_fisheye	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

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

The Fisheye augmentation applies fisheye effect 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 Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_flip()

RppStatus rppt_flip	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		Rpp32u *	horizontalTensor,
		Rpp32u *	verticalTensor,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

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

The flip augmentation performs a mask-controlled horizontal/vertical flip 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 Output

Parameters

[in]	srcPtr	source tensor in HIP/HOST memory
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP/HOST memory
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	horizontalTensor	horizontal flag values to set horizontal flip on/off (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with horizontalTensor[i] = 0/1)
[in]	verticalTensor	vertical flag values to set vertical flip on/off (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with verticalTensor[i] = 0/1)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_flip_voxel()

RppStatus rppt_flip_voxel	(	RppPtr_t	srcPtr,
		RpptGenericDescPtr	srcGenericDescPtr,
		RppPtr_t	dstPtr,
		RpptGenericDescPtr	dstGenericDescPtr,
		Rpp32u *	horizontalTensor,
		Rpp32u *	verticalTensor,
		Rpp32u *	depthTensor,
		RpptROI3DPtr	roiGenericPtrSrc,
		RpptRoi3DType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

Flip voxel augmentation on HIP/HOST backend.

The flip voxel augmentation performs a mask-controlled horizontal/vertical/depth flip on a generic 4D tensor.
Support added for f32 -> f32 and u8 -> u8 dataypes.

Sample Input

Sample Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcGenericDescPtr	source tensor descriptor (Restrictions - numDims = 5, offsetInBytes >= 0, dataType = U8/F32, layout = NCDHW/NDHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstGenericDescPtr	destination tensor descriptor (Restrictions - numDims = 5, offsetInBytes >= 0, dataType = U8/F32, layout = NCDHW/NDHWC, c = 1/3)
[in]	horizontalTensor	horizontal flag values to set horizontal flip on/off (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with horizontalTensor[i] = 0/1)
[in]	verticalTensor	vertical flag values to set vertical flip on/off (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with verticalTensor[i] = 0/1)
[in]	depthTensor	depth flag values to set depth flip on/off (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with depthTensor[i] = 0/1)
[in]	roiGenericPtrSrc	ROI data for each image in source tensor (tensor of batchSize RpptRoiGeneric values)
[in]	roiType	ROI type used (RpptRoi3DType::XYZWHD or RpptRoi3DType::LTFRBB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	execution backend to run the augmentation on (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_jpeg_compression_distortion()

RppStatus rppt_jpeg_compression_distortion	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		Rpp32s *	qualityTensor,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

JPEG Compression Distortion on HIP/HOST backend.

This function simulates JPEG compression distortion on an image tensor. It introduces artifacts seen in lossy JPEG compression by converting the image to the frequency domain using the Discrete Cosine Transform (DCT), applying quantization, and then reconstructing the image using the inverse DCT (IDCT). This process introduces compression-related distortions similar to those in JPEG images.

Sample Input

Sample Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcGenericDescPtr	source tensor descriptor
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstGenericDescPtr	destination tensor descriptor
[in]	qualityTensor	JPEG quality factor controlling the level of compression (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend)). Valid range is 1 to 99 (inclusive).
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_lens_correction()

RppStatus rppt_lens_correction	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		Rpp32f *	rowRemapTable,
		Rpp32f *	colRemapTable,
		RpptDescPtr	tableDescPtr,
		Rpp32f *	cameraMatrixTensor,
		Rpp32f *	distortionCoeffsTensor,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

Lens correction transformation on HIP/HOST backend for a NCHW/NHWC layout tensor.

Performs lens correction transforms on an image to compensate barrel lens distortion 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. Note: Returns a black image if the passed camera matrix has a 0 determinant

Sample Input

Sample Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	rowRemapTable	Rpp32f row numbers in HIP memory (for HIP backend) or HOST memory (for HOST backend) for every pixel in the input batch of images (1D tensor of size width * height * batchSize)
[in]	colRemapTable	Rpp32f column numbers in HIP memory (for HIP backend) or HOST memory (for HOST backend) for every pixel in the input batch of images (1D tensor of size width * height * batchSize)
[in]	tableDescPtr	table tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = F32, layout = NHWC, c = 1)
[in]	cameraMatrixTensor	contains camera intrinsic parameters required to compute lens corrected image. (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size 9 * batchSize)
[in]	distortionCoeffsTensor	contains distortion coefficients required to compute lens corrected image. (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size 8 * batchSize)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_phase()

RppStatus rppt_phase	(	RppPtr_t	srcPtr1,
		RppPtr_t	srcPtr2,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

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

The phase augmentation computes phase of corresponding pixels 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 Input1

Sample Input2

Sample Output

Parameters

[in]	srcPtr1	source1 tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcPtr2	source2 tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	execution backend to run the augmentation on (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_remap()

RppStatus rppt_remap	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		Rpp32f *	rowRemapTable,
		Rpp32f *	colRemapTable,
		RpptDescPtr	tableDescPtr,
		RpptInterpolationType	interpolationType,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

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

Performs a remap operation using user specified remap tables for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout. For each image, the output(x,y) = input(mapx(x, y), mapy(x, y)) for every (x,y) in the destination image.

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 Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	rowRemapTable	Rpp32f row numbers in HIP memory (for HIP backend) or HOST memory (for HOST backend) for every pixel in the input batch of images (Restrictions - rois in the rowRemapTable data for each image in batch must match roiTensorPtrSrc)
[in]	colRemapTable	Rpp32f column numbers in HIP memory (for HIP backend) or HOST memory (for HOST backend) for every pixel in the input batch of images (Restrictions - rois in the colRemapTable data for each image in batch must match roiTensorPtrSrc)
[in]	tableDescPtr	rowRemapTable and colRemapTable common tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = F32, layout = NHWC, c = 1)
[in]	interpolationType	Interpolation type used in `RpptInterpolationType` (Restrictions - Supports only NEAREST_NEIGHBOR and BILINEAR)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_resize()

RppStatus rppt_resize	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		RpptImagePatchPtr	dstImgSizes,
		RpptInterpolationType	interpolationType,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

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

The resize augmentation performs an image resize 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 Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	dstImgSizes	destination image sizes ( `RpptImagePatchPtr` type pointer to array, in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize)
[in]	interpolationType	Interpolation type used in `RpptInterpolationType`
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_resize_crop_mirror()

RppStatus rppt_resize_crop_mirror	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		RpptImagePatchPtr	dstImgSizes,
		RpptInterpolationType	interpolationType,
		Rpp32u *	mirrorTensor,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

Resize crop mirror augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor.

The resize crop mirror augmentation performs an image resized crop, with an optional mirror, 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 Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	dstImgSizes	destination image sizes ( `RpptImagePatchPtr` type pointer to array, in HOST memory, of size batchSize)
[in]	interpolationType	Interpolation type used in `RpptInterpolationType`
[in]	mirrorTensor	mirror flag value to set mirroring on/off (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with mirrorTensor[n] = 0/1)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_resize_mirror_normalize()

RppStatus rppt_resize_mirror_normalize	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		RpptImagePatchPtr	dstImgSizes,
		RpptInterpolationType	interpolationType,
		Rpp32f *	meanTensor,
		Rpp32f *	stdDevTensor,
		Rpp32u *	mirrorTensor,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

Resize mirror normalize augmentation on HIP/HOST backend for a NCHW/NHWC layout tensor.

The resize mirror normalize augmentation performs an image resize, an optional mirror and/or normalize, 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 Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	dstImgSizes	destination image sizes ( `RpptImagePatchPtr` type pointer to array, in HOST memory, of size batchSize)
[in]	interpolationType	Interpolation type used in `RpptInterpolationType`
[in]	meanTensor	mean value for each image in the batch (meanTensor[n] >= 0, 1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size = batchSize for greyscale images, size = batchSize * 3 for RGB images))
[in]	stdDevTensor	standard deviation value for each image in the batch (stdDevTensor[n] >= 0, 1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size = batchSize for greyscale images, size = batchSize * 3 for RGB images)
[in]	mirrorTensor	mirror flag value to set mirroring on/off (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize, with mirrorTensor[n] = 0/1)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_rotate()

RppStatus rppt_rotate	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		Rpp32f *	angle,
		RpptInterpolationType	interpolationType,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

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

The rotate augmentation performs a rotate transformations 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 Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	angle	image rotation angle in degrees - positive deg-anticlockwise/negative deg-clockwise (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize)
[in]	interpolationType	Interpolation type used (RpptInterpolationType::XYWH or RpptRoiType::LTRB)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	execution backend to run the augmentation on (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_slice()

RppStatus rppt_slice	(	RppPtr_t	srcPtr,
		RpptGenericDescPtr	srcGenericDescPtr,
		RppPtr_t	dstPtr,
		RpptGenericDescPtr	dstGenericDescPtr,
		Rpp32s *	anchorTensor,
		Rpp32s *	shapeTensor,
		RppPtr_t	fillValue,
		bool	enablePadding,
		Rpp32u *	roiTensor,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

Slice augmentation on HIP/HOST backend.

This function performs slice augmentation on a generic 4D tensor. Slice augmentation involves selecting a region of interest (ROI) from the source tensor and copying it to the destination tensor. Support added for f32 -> f32 and u8 -> u8 dataypes.

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcGenericDescPtr	source tensor descriptor
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstGenericDescPtr	destination tensor descriptor
[in]	anchorTensor	starting index of the slice for each dimension in input (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size = batchSize * numberOfDimensions)
[in]	shapeTensor	length of the slice for each dimension in input (1D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size = batchSize * numberOfDimensions)
[in]	fillValue	fill value that is used to fill output if enablePadding is set to true
[in]	enablePadding	boolean flag to specify if padding is enabled or not
[in]	roiTensor	roi data in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend) (1D tensor of size = batchSize * numberOfDimensions * 2)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	execution backend to run the augmentation on (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_transpose()

RppStatus rppt_transpose	(	RppPtr_t	srcPtr,
		RpptGenericDescPtr	srcGenericDescPtr,
		RppPtr_t	dstPtr,
		RpptGenericDescPtr	dstGenericDescPtr,
		Rpp32u *	permTensor,
		Rpp32u *	roiTensor,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

Transpose Generic augmentation on HIP/HOST backend.

The transpose augmentation performs an input-permutation based transpose on a generic ND Tensor.

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcGenericDescPtr	source tensor descriptor
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstGenericDescPtr	destination tensor descriptor
[in]	permTensor	permutation tensor for transpose operation in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	roiTensor	ROI data in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend) for each element in source tensor (tensor of batchSize * number of dimensions * 2 values)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_warp_affine()

RppStatus rppt_warp_affine	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		Rpp32f *	affineTensor,
		RpptInterpolationType	interpolationType,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

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

The warp affine augmentation performs affine transformations 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 Output

Parameters

[in]	srcPtr	source tensor in HIP/HOST memory
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP/HOST memory
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	affineTensor	affine matrix values for transformation calculation (2D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize * 6 for each image in batch)
[in]	interpolationType	Interpolation type used (RpptInterpolationType::XYWH or RpptRoiType::LTRB)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

◆ rppt_warp_perspective()

RppStatus rppt_warp_perspective	(	RppPtr_t	srcPtr,
		RpptDescPtr	srcDescPtr,
		RppPtr_t	dstPtr,
		RpptDescPtr	dstDescPtr,
		Rpp32f *	perspectiveTensor,
		RpptInterpolationType	interpolationType,
		RpptROIPtr	roiTensorPtrSrc,
		RpptRoiType	roiType,
		rppHandle_t	rppHandle,
		RppBackend	executionBackend
	)

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

The warp perspective performs perspective transformations 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 Output

Parameters

[in]	srcPtr	source tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	srcDescPtr	source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
[out]	dstPtr	destination tensor in HIP memory (for HIP backend) or HOST memory (for HOST backend)
[in]	dstDescPtr	destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
[in]	perspectiveTensor	perspective matrix values for transformation calculation (2D tensor in pinned / HIP memory (for HIP backend) or HOST memory (for HOST backend), of size batchSize * 9 for each image in batch)
[in]	interpolationType	Interpolation type used (RpptInterpolationType::BILINEAR or RpptRoiType::NEAREST_NEIGHBOR)
[in]	roiTensorPtrSrc	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))
[in]	roiType	ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
[in]	rppHandle	RPP HIP/HOST handle created with `rppCreate()`
[in]	executionBackend	backend for execution (RppBackend::RPP_HOST_BACKEND or RppBackend::RPP_HIP_BACKEND)

Returns: A RppStatus enumeration.

Return values

RPP_SUCCESS	Successful completion.
RPP_ERROR*	Unsuccessful completion.

RPPT Tensor Operations - Geometric Augmentations.

RPPT Tensor Operations - Geometric Augmentations.#

Functions

Detailed Description

Function Documentation

◆ rppt_concat()

◆ rppt_crop()

◆ rppt_crop_and_patch()

◆ rppt_crop_mirror_normalize()

◆ rppt_fisheye()

◆ rppt_flip()

◆ rppt_flip_voxel()

◆ rppt_jpeg_compression_distortion()

◆ rppt_lens_correction()

◆ rppt_phase()

◆ rppt_remap()

◆ rppt_resize()

◆ rppt_resize_crop_mirror()

◆ rppt_resize_mirror_normalize()

◆ rppt_rotate()

◆ rppt_slice()

◆ rppt_transpose()

◆ rppt_warp_affine()

◆ rppt_warp_perspective()