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// 5x5 convolution with 25 samples
// Applies mat4 weights per sample
fn cnn_conv5x5(
tex: texture_2d<f32>,
samp: sampler,
uv: vec2<f32>,
resolution: vec2<f32>,
weights: array<mat4x4<f32>, 25>,
bias: vec4<f32>
) -> vec4<f32> {
let step = 1.0 / resolution;
var sum = bias;
var idx = 0;
for (var dy = -2; dy <= 2; dy++) {
for (var dx = -2; dx <= 2; dx++) {
let offset = vec2<f32>(f32(dx), f32(dy)) * step;
let sample = textureSample(tex, samp, uv + offset);
sum += weights[idx] * sample;
idx++;
}
}
return sum;
}
fn cnn_conv5x5_with_coord(
tex: texture_2d<f32>,
samp: sampler,
uv: vec2<f32>,
resolution: vec2<f32>,
rgba_weights: array<mat4x4<f32>, 25>,
coord_weights: mat2x4<f32>,
bias: vec4<f32>
) -> vec4<f32> {
let step = 1.0 / resolution;
var sum = bias;
sum += coord_weights * uv;
var idx = 0;
for (var dy = -2; dy <= 2; dy++) {
for (var dx = -2; dx <= 2; dx++) {
let offset = vec2<f32>(f32(dx), f32(dy)) * step;
let rgba = textureSample(tex, samp, uv + offset);
sum += rgba_weights[idx] * rgba;
idx++;
}
}
return sum;
}
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