1 files changed, 18 insertions, 17 deletions
diff --git a/workspaces/main/shaders/cnn/cnn_layer.wgsl b/workspaces/main/shaders/cnn/cnn_layer.wgsl
index 5834f78..1b1b539 100644
--- a/workspaces/main/shaders/cnn/cnn_layer.wgsl
+++ b/workspaces/main/shaders/cnn/cnn_layer.wgsl
@@ -8,6 +8,7 @@
 #include "common_uniforms"
 #include "cnn_activation"
 #include "cnn_conv3x3"
+#include "cnn_conv5x5"
 #include "cnn_weights_generated"
 
 struct CNNLayerParams {
@@ -29,28 +30,28 @@ struct CNNLayerParams {
 
 @fragment fn fs_main(@builtin(position) p: vec4<f32>) -> @location(0) vec4<f32> {
     let uv = p.xy / uniforms.resolution;
-    let input = textureSample(txt, smplr, uv);
-    let original = textureSample(original_input, smplr, uv);
+    let original = (textureSample(original_input, smplr, uv) - 0.5) * 2.0;  // Normalize to [-1,1]
     var result = vec4<f32>(0.0);
 
-    // Layer 0 uses coordinate-aware convolution
+    // Layer 0: 7→4 (RGBD output)
     if (params.layer_index == 0) {
-        result = cnn_conv3x3_with_coord(txt, smplr, uv, uniforms.resolution,
-                                        rgba_weights_layer0, coord_weights_layer0, bias_layer0);
-        result = cnn_tanh(result);
+        result = cnn_conv3x3_7to4_src(txt, smplr, uv, uniforms.resolution, weights_layer0);
+        result = cnn_tanh(result);  // Keep in [-1,1]
     }
     else if (params.layer_index == 1) {
-        result = cnn_conv3x3(txt, smplr, uv, uniforms.resolution,
-                                   weights_layer1, bias_layer1);
-        result = cnn_tanh(result);
-    }
-    else if (params.layer_index == 2) {
-        result = cnn_conv3x3(txt, smplr, uv, uniforms.resolution,
-                                   weights_layer2, bias_layer2);
-    }
-    else {
-        result = input;
+        result = cnn_conv5x5_7to4(txt, smplr, uv, uniforms.resolution,
+                                   original, weights_layer1);
+	result = cnn_tanh(result);  // Keep in [-1,1]
     }
+    else if (params.layer_index == 2) {  // last layer
+        let gray_out = cnn_conv3x3_7to1(txt, smplr, uv, uniforms.resolution,
+                                        original, weights_layer2);
 
-    return mix(original, result, params.blend_amount);
+        // At this point here, 'gray_out' is what the training script should have learned.
+        // Below is some extra code for visual output, excluded from training:
+        result = vec4<f32>(gray_out, gray_out, gray_out, 1.0);  // Keep in [-1,1]
+        let blended = mix(original, result, params.blend_amount);
+        return (blended + 1.0) * 0.5;  // Denormalize to [0,1] for display
+    }
+    return result;
 }