Remap

cvcuda.remap(*args, **kwargs)

Overloaded function.

1. remap(src: nvcv.Tensor, map: nvcv.Tensor, src_interp: cvcuda.Interp = <Interp.NEAREST: 0>, map_interp: cvcuda.Interp = <Interp.NEAREST: 0>, map_type: cvcuda.Remap = <Remap.ABSOLUTE: 0>, align_corners: bool = False, border: cvcuda.Border = <Border.CONSTANT: 0>, border_value: numpy.ndarray[numpy.float32] = array([], dtype=float32), *, stream: Optional[nvcv.cuda.Stream] = None) -> nvcv.Tensor

   cvcuda.remap(src: nvcv.Tensor, map: nvcv.Tensor, src_interp: cvcuda.Interp = cvcuda.Interp.NEAREST, map_interp: cvcuda.Interp = cvcuda.Interp.NEAREST, map_type: cvcuda.Remap = cvcuda.Remap.ABSOLUTE, align_corners: bool = False, border: cvcuda.Border = cvcuda.Border.CONSTANT, border_value: numpy.ndarray = np.ndarray((0,)), stream: Optional[nvcv.cuda.Stream] = None) -> nvcv.Tensor

   Executes the Warp Perspective operation on the given cuda stream.

   See also:

   Refer to the CV-CUDA C API reference for the Remap operator for more details and usage examples.

   Args:

   src (nvcv.Tensor): Input tensor. src_interp (cvcuda.Interp, optional): Interpolation type used when fetching values

   from the source image.

   map_interp (cvcuda.Interp, optional): Interpolation type used when fetching values

   from the map tensor.

   map_type (cvcuda.Remap, optional): This determines how the values inside the map are

   interpreted. If it is cvcuda.Remap.ABSOLUTE the map values are absolute, denormalized positions in the input tensor to fetch values from. If it is cvcuda.Remap.ABSOLUTE_NORMALIZED the map values are absolute, normalized positions in [-1, 1] range to fetch values from the input tensor in a resolution agnostic way. If it is cvcuda.Remap.RELATIVE_NORMALIZED the map values are relative, normalized offsets to be applied to each output position to fetch values from the input tensor, also resolution agnostic.

   align_corners (bool, optional): The remap operation from output to input via the map

   is done in the floating-point domain. If True, they are aligned by the center points of their corner pixels. Otherwise, they are aligned by the corner points of their corner pixels.

   border (cvcuda.Border, optional): pixel extrapolation method (cvcuda.Border.CONSTANT,

   cvcuda.Border.REPLICATE, cvcuda.Border.REFLECT, cvcuda.Border.REFLECT_101, or cvcuda.Border.WRAP).

   border_value (numpy.ndarray, optional): Used to specify values for a constant border,

   should have size <= 4 and dim of 1, where the values specify the border color for each color channel.

   stream (nvcv.cuda.Stream, optional): CUDA Stream on which to perform the operation.

   Returns:

   nvcv.Tensor: The output tensor.

   Caution:

   Restrictions to several arguments may apply. Check the C API references of the CV-CUDA operator.

2. remap(src: nvcv.ImageBatchVarShape, map: nvcv.Tensor, src_interp: cvcuda.Interp = <Interp.NEAREST: 0>, map_interp: cvcuda.Interp = <Interp.NEAREST: 0>, map_type: cvcuda.Remap = <Remap.ABSOLUTE: 0>, align_corners: bool = False, border: cvcuda.Border = <Border.CONSTANT: 0>, border_value: numpy.ndarray[numpy.float32] = array([], dtype=float32), *, stream: Optional[nvcv.cuda.Stream] = None) -> nvcv.ImageBatchVarShape

   cvcuda.remap(src: nvcv.ImageBatchVarShape, map: nvcv.Tensor, src_interp: cvcuda.Interp = cvcuda.Interp.NEAREST, map_interp: cvcuda.Interp = cvcuda.Interp.NEAREST, map_type: cvcuda.Remap = cvcuda.Remap.ABSOLUTE, align_corners: bool = False, border: cvcuda.Border = cvcuda.Border.CONSTANT, border_value: numpy.ndarray = np.ndarray((0,)), stream: Optional[nvcv.cuda.Stream] = None) -> nvcv.ImageBatchVarShape

   Executes the Warp Perspective operation on the given cuda stream.

   See also:

   Refer to the CV-CUDA C API reference for the Remap operator for more details and usage examples.

   Args:

   src (nvcv.ImageBatchVarShape): Input image batch. src_interp (cvcuda.Interp, optional): Interpolation type used when fetching values

   from the source image.

   map_interp (cvcuda.Interp, optional): Interpolation type used when fetching values

   from the map tensor.

   map_type (cvcuda.Remap, optional): This determines how the values inside the map are

   interpreted. If it is cvcuda.Remap.ABSOLUTE the map values are absolute, denormalized positions in the input tensor to fetch values from. If it is cvcuda.Remap.ABSOLUTE_NORMALIZED the map values are absolute, normalized positions in [-1, 1] range to fetch values from the input tensor in a resolution agnostic way. If it is cvcuda.Remap.RELATIVE_NORMALIZED the map values are relative, normalized offsets to be applied to each output position to fetch values from the input tensor, also resolution agnostic.

   align_corners (bool, optional): The remap operation from output to input via the map

   is done in the floating-point domain. If True, they are aligned by the center points of their corner pixels. Otherwise, they are aligned by the corner points of their corner pixels.

   border (cvcuda.Border, optional): pixel extrapolation method (cvcuda.Border.CONSTANT,

   cvcuda.Border.REPLICATE, cvcuda.Border.REFLECT, cvcuda.Border.REFLECT_101, or cvcuda.Border.WRAP).

   border_value (numpy.ndarray, optional): Used to specify values for a constant border,

   should have size <= 4 and dim of 1, where the values specify the border color for each color channel.

   stream (nvcv.cuda.Stream, optional): CUDA Stream on which to perform the operation.

   Returns:

   nvcv.ImageBatchVarShape: The output image batch.

   Caution:

   Restrictions to several arguments may apply. Check the C API references of the CV-CUDA operator.

cvcuda.remap_into(*args, **kwargs)

Overloaded function.

1. remap_into(dst: nvcv.Tensor, src: nvcv.Tensor, map: nvcv.Tensor, src_interp: cvcuda.Interp = <Interp.NEAREST: 0>, map_interp: cvcuda.Interp = <Interp.NEAREST: 0>, map_type: cvcuda.Remap = <Remap.ABSOLUTE: 0>, align_corners: bool = False, border: cvcuda.Border = <Border.CONSTANT: 0>, border_value: numpy.ndarray[numpy.float32] = array([], dtype=float32), *, stream: Optional[nvcv.cuda.Stream] = None) -> nvcv.Tensor

   cvcuda.remap_into(dst: nvcv.Tensor, src: nvcv.Tensor, map: nvcv.Tensor, src_interp: cvcuda.Interp = cvcuda.Interp.NEAREST, map_interp: cvcuda.Interp = cvcuda.Interp.NEAREST, map_type: cvcuda.Remap = cvcuda.Remap.ABSOLUTE, align_corners: bool = False, border: cvcuda.Border = cvcuda.Border.CONSTANT, border_value: numpy.ndarray = np.ndarray((0,)), stream: Optional[nvcv.cuda.Stream] = None)

   Executes the Warp Perspective operation on the given cuda stream.

   See also:

   Refer to the CV-CUDA C API reference for the Remap operator for more details and usage examples.

   Args:

   dst (nvcv.Tensor): Output tensor. src (nvcv.Tensor): Input tensor. src_interp (cvcuda.Interp, optional): Interpolation type used when fetching values

   from the source image.

   map_interp (cvcuda.Interp, optional): Interpolation type used when fetching values

   from the map tensor.

   map_type (cvcuda.Remap, optional): This determines how the values inside the map are

   interpreted. If it is cvcuda.Remap.ABSOLUTE the map values are absolute, denormalized positions in the input tensor to fetch values from. If it is cvcuda.Remap.ABSOLUTE_NORMALIZED the map values are absolute, normalized positions in [-1, 1] range to fetch values from the input tensor in a resolution agnostic way. If it is cvcuda.Remap.RELATIVE_NORMALIZED the map values are relative, normalized offsets to be applied to each output position to fetch values from the input tensor, also resolution agnostic.

   align_corners (bool, optional): The remap operation from output to input via the map

   is done in the floating-point domain. If True, they are aligned by the center points of their corner pixels. Otherwise, they are aligned by the corner points of their corner pixels.

   border (cvcuda.Border, optional): pixel extrapolation method (cvcuda.Border.CONSTANT,

   cvcuda.Border.REPLICATE, cvcuda.Border.REFLECT, cvcuda.Border.REFLECT_101, or cvcuda.Border.WRAP).

   border_value (numpy.ndarray, optional): Used to specify values for a constant border,

   should have size <= 4 and dim of 1, where the values specify the border color for each color channel.

   stream (nvcv.cuda.Stream, optional): CUDA Stream on which to perform the operation.

   Returns:

   None

   Caution:

   Restrictions to several arguments may apply. Check the C API references of the CV-CUDA operator.

2. remap_into(dst: nvcv.ImageBatchVarShape, src: nvcv.ImageBatchVarShape, map: nvcv.Tensor, src_interp: cvcuda.Interp = <Interp.NEAREST: 0>, map_interp: cvcuda.Interp = <Interp.NEAREST: 0>, map_type: cvcuda.Remap = <Remap.ABSOLUTE: 0>, align_corners: bool = False, border: cvcuda.Border = <Border.CONSTANT: 0>, border_value: numpy.ndarray[numpy.float32] = array([], dtype=float32), *, stream: Optional[nvcv.cuda.Stream] = None) -> nvcv.ImageBatchVarShape

   cvcuda.remap_into(dst: nvcv.ImageBatchVarShape, src: nvcv.ImageBatchVarShape, map: nvcv.Tensor, src_interp: cvcuda.Interp = cvcuda.Interp.NEAREST, map_interp: cvcuda.Interp = cvcuda.Interp.NEAREST, map_type: cvcuda.Remap = cvcuda.Remap.ABSOLUTE, align_corners: bool = False, border: cvcuda.Border = cvcuda.Border.CONSTANT, border_value: numpy.ndarray = np.ndarray((0,)), stream: Optional[nvcv.cuda.Stream] = None)

   Executes the Warp Perspective operation on the given cuda stream.

   See also:

   Refer to the CV-CUDA C API reference for the Remap operator for more details and usage examples.

   Args:

   dst (nvcv.ImageBatchVarShape): Output image batch. src (nvcv.ImageBatchVarShape): Input image batch. src_interp (cvcuda.Interp, optional): Interpolation type used when fetching values

   from the source image.

   map_interp (cvcuda.Interp, optional): Interpolation type used when fetching values

   from the map tensor.

   map_type (cvcuda.Remap, optional): This determines how the values inside the map are

   interpreted. If it is cvcuda.Remap.ABSOLUTE the map values are absolute, denormalized positions in the input tensor to fetch values from. If it is cvcuda.Remap.ABSOLUTE_NORMALIZED the map values are absolute, normalized positions in [-1, 1] range to fetch values from the input tensor in a resolution agnostic way. If it is cvcuda.Remap.RELATIVE_NORMALIZED the map values are relative, normalized offsets to be applied to each output position to fetch values from the input tensor, also resolution agnostic.

   align_corners (bool, optional): The remap operation from output to input via the map

   is done in the floating-point domain. If True, they are aligned by the center points of their corner pixels. Otherwise, they are aligned by the corner points of their corner pixels.

   border (cvcuda.Border, optional): pixel extrapolation method (cvcuda.Border.CONSTANT,

   cvcuda.Border.REPLICATE, cvcuda.Border.REFLECT, cvcuda.Border.REFLECT_101, or cvcuda.Border.WRAP).

   border_value (numpy.ndarray, optional): Used to specify values for a constant border,

   should have size <= 4 and dim of 1, where the values specify the border color for each color channel.

   stream (nvcv.cuda.Stream, optional): CUDA Stream on which to perform the operation.

   Returns:

   None

   Caution:

   Restrictions to several arguments may apply. Check the C API references of the CV-CUDA operator.