refactor: Optimize CNN grayscale computation

Compute gray once per fragment using dot() instead of per-layer.
Pass gray as f32 parameter to conv functions instead of vec4 original.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

1 files changed, 5 insertions, 11 deletions

diff --git a/workspaces/main/shaders/cnn/cnn_conv3x3.wgsl b/workspaces/main/shaders/cnn/cnn_conv3x3.wgsl
index 96ddf5b..79b0350 100644
--- a/workspaces/main/shaders/cnn/cnn_conv3x3.wgsl
+++ b/workspaces/main/shaders/cnn/cnn_conv3x3.wgsl
@@ -15,7 +15,7 @@ fn cnn_conv3x3_7to4_src(
 
   // Compute grayscale from original (converted in [-1,1])
   let original = (textureSample(tex, samp, uv) - 0.5) * 2.0;
-  let gray = 0.2126*original.r + 0.7152*original.g + 0.0722*original.b;
+  let gray = dot(original.rgb, vec3<f32>(0.2126, 0.7152, 0.0722));
 
   // Normalize UV to [-1,1]
   let uv_norm = (uv - 0.5) * 2.0;
@@ -52,7 +52,7 @@ fn cnn_conv3x3_7to4_src(
 }
 
 // Inner layers: 7→4 channels (RGBD output)
-// Assumes 'tex' and 'original' are already normalized to [-1,1]
+// Assumes 'tex' is already normalized to [-1,1]
 // UV coordinates remain in [0,1] and are normalized internally
 // weights: array<array<f32, 8>, 36> (9 positions × 4 channels, each with 7 weights + bias)
 fn cnn_conv3x3_7to4(
@@ -60,14 +60,11 @@ fn cnn_conv3x3_7to4(
   samp: sampler,
   uv: vec2<f32>,
   resolution: vec2<f32>,
-  original: vec4<f32>,
+  gray: f32,
   weights: array<array<f32, 8>, 36>
 ) -> vec4<f32> {
   let step = 1.0 / resolution;
 
-  // Compute grayscale from original (already in [-1,1])
-  let gray = 0.2126*original.r + 0.7152*original.g + 0.0722*original.b;
-
   // Normalize UV to [-1,1]
   let uv_norm = (uv - 0.5) * 2.0;
 
@@ -103,7 +100,7 @@ fn cnn_conv3x3_7to4(
 }
 
 // Final layer: 7→1 channel (scalar output)
-// Assumes 'tex' and 'original' are already normalized to [-1,1]
+// Assumes 'tex' is already normalized to [-1,1]
 // UV coordinates remain in [0,1] and are normalized internally
 // weights: array<array<f32, 8>, 9> (9 positions, each with 7 weights + bias)
 fn cnn_conv3x3_7to1(
@@ -111,14 +108,11 @@ fn cnn_conv3x3_7to1(
   samp: sampler,
   uv: vec2<f32>,
   resolution: vec2<f32>,
-  original: vec4<f32>,
+  gray: f32,
   weights: array<array<f32, 8>, 9>
 ) -> f32 {
   let step = 1.0 / resolution;
 
-  // Compute grayscale from original (already in [-1,1])
-  let gray = 0.2126*original.r + 0.7152*original.g + 0.0722*original.b;
-
   // Normalize UV to [-1,1]
   let uv_norm = (uv - 0.5) * 2.0;