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Vide-coded 64k demo system
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31 hours
opt: Move invariant in1 calculation outside CNN convolution loops
skal
32 hours
opt: Vec4-optimize CNN convolution shaders for SIMD
skal
33 hours
chore: Update CNN architecture to 3×3×3 with new trained weights
skal
34 hours
fix: Correct UV coordinate computation to match PyTorch linspace
skal
34 hours
fix: Add clamp to CNN final layer to match PyTorch training
skal
35 hours
refactor: Optimize CNN grayscale computation
skal
35 hours
update train_cnn.py and shader
skal
36 hours
fix: CNN training normalization pipeline consistency
skal
36 hours
udpate CNN shader code.
skal
37 hours
refactor: Optimize CNN normalization to eliminate redundant conversions
skal
38 hours
fix: Support variable kernel sizes in CNN layer generation
skal
39 hours
feat: CNN RGBD→grayscale with 7-channel augmented input
skal
40 hours
fix: Resolve CNN effect black screen bug (framebuffer capture + uniforms)
skal
43 hours
feat: Add multi-layer CNN support with framebuffer capture and blend control
skal
45 hours
feat: Add coordinate-aware CNN layer 0 for position-dependent stylization
skal
48 hours
feat: Add CNN post-processing effect with modular WGSL architecture
skal