nvidia.dali.fn.gaussian_blur¶
- nvidia.dali.fn.gaussian_blur(*inputs, **kwargs)¶
Applies a Gaussian Blur to the input.
Gaussian blur is calculated by applying a convolution with a Gaussian kernel, which can be parameterized with
windows_size
andsigma
. If only the sigma is specified, the radius of the Gaussian kernel defaults toceil(3 * sigma)
, so the kernel window size is2 * ceil(3 * sigma) + 1
.If only the window size is provided, the sigma is calculated by using the following formula:
radius = (window_size - 1) / 2 sigma = (radius - 1) * 0.3 + 0.8
The sigma and kernel window size can be specified as one value for all data axes or a value per data axis.
When specifying the sigma or window size per axis, the axes are provided same as layouts, from outermost to innermost.
Note
The channel
C
and frameF
dimensions are not considered data axes. If channels are present, only channel-first or channel-last inputs are supported.For example, with
HWC
input, you can providesigma=1.0
orsigma=(1.0, 2.0)
because there are two data axes, H and W.The same input can be provided as per-sample tensors.
This operator allows sequence inputs and supports volumetric data.
- Supported backends
‘cpu’
‘gpu’
- Parameters:
input (TensorList) – Input to the operator.
- Keyword Arguments:
bytes_per_sample_hint (int or list of int, optional, default = [0]) –
Output size hint, in bytes per sample.
If specified, the operator’s outputs residing in GPU or page-locked host memory will be preallocated to accommodate a batch of samples of this size.
dtype (
nvidia.dali.types.DALIDataType
, optional) –Output data type.
Supported type: FLOAT. If not set, the input type is used.
preserve (bool, optional, default = False) – Prevents the operator from being removed from the graph even if its outputs are not used.
seed (int, optional, default = -1) –
Random seed.
If not provided, it will be populated based on the global seed of the pipeline.
sigma (float or list of float or TensorList of float, optional, default = [0.0]) –
Sigma value for the Gaussian Kernel.
Supports
per-frame
inputs.window_size (int or list of int or TensorList of int, optional, default = [0]) –
The diameter of the kernel.
Supports
per-frame
inputs.