use singe_cuda::memory::DeviceMemory;
use crate::{
context::StreamContext,
error::Result,
image::view::{ImageView, MaskView},
};
pub trait MaskedScalarStatisticImage<T, L> {
const OUTPUT_CHANNELS: usize;
fn mean_masked(
stream_context: &StreamContext,
source: &ImageView<'_, T, L>,
mask: &MaskView<'_>,
output: &mut DeviceMemory<f64>,
) -> Result<()>;
fn norm_inf_masked(
stream_context: &StreamContext,
source: &ImageView<'_, T, L>,
mask: &MaskView<'_>,
output: &mut DeviceMemory<f64>,
) -> Result<()>;
fn norm_l1_masked(
stream_context: &StreamContext,
source: &ImageView<'_, T, L>,
mask: &MaskView<'_>,
output: &mut DeviceMemory<f64>,
) -> Result<()>;
fn norm_l2_masked(
stream_context: &StreamContext,
source: &ImageView<'_, T, L>,
mask: &MaskView<'_>,
output: &mut DeviceMemory<f64>,
) -> Result<()>;
}
macro_rules! impl_masked_scalar_statistic_image {
($ty:ty, $mean:path, $norm_inf:path, $norm_l1:path, $norm_l2:path) => {
impl<'a> MaskedScalarStatisticImage<$ty, C1> for ImagePipeline<'a, $ty, C1> {
const OUTPUT_CHANNELS: usize = 1;
fn mean_masked(
stream_context: &StreamContext,
source: &ImageView<'_, $ty, C1>,
mask: &MaskView<'_>,
output: &mut DeviceMemory<f64>,
) -> Result<()> {
$mean(stream_context, source, mask, output)
}
fn norm_inf_masked(
stream_context: &StreamContext,
source: &ImageView<'_, $ty, C1>,
mask: &MaskView<'_>,
output: &mut DeviceMemory<f64>,
) -> Result<()> {
$norm_inf(stream_context, source, mask, output)
}
fn norm_l1_masked(
stream_context: &StreamContext,
source: &ImageView<'_, $ty, C1>,
mask: &MaskView<'_>,
output: &mut DeviceMemory<f64>,
) -> Result<()> {
$norm_l1(stream_context, source, mask, output)
}
fn norm_l2_masked(
stream_context: &StreamContext,
source: &ImageView<'_, $ty, C1>,
mask: &MaskView<'_>,
output: &mut DeviceMemory<f64>,
) -> Result<()> {
$norm_l2(stream_context, source, mask, output)
}
}
};
}