index
:
demo.git
main
Vide-coded 64k demo system
summary
refs
log
tree
commit
diff
log msg
author
committer
range
path:
root
/
training
/
train_cnn.py
Age
Commit message (
Expand
)
Author
24 hours
fix: CNN training/inference to match WGSL sliding window
skal
24 hours
format .wgsl layer code (cosmetics)
skal
33 hours
fix: Use patch-based inference to match CNN training distribution
skal
33 hours
opt: Move invariant in1 calculation outside CNN convolution loops
skal
34 hours
opt: Vec4-optimize CNN convolution shaders for SIMD
skal
35 hours
feat: Add salient-point patch extraction for CNN training
skal
36 hours
fix: Correct UV coordinate computation to match PyTorch linspace
skal
36 hours
fix: Add clamp to CNN final layer to match PyTorch training
skal
36 hours
refactor: Optimize CNN grayscale computation
skal
37 hours
update train_cnn.py and shader
skal
38 hours
feat: Add inference mode to train_cnn.py for ground truth generation
skal
38 hours
fix: CNN training normalization pipeline consistency
skal
39 hours
refactor: Optimize CNN normalization to eliminate redundant conversions
skal
40 hours
fix: Support variable kernel sizes in CNN layer generation
skal
41 hours
feat: CNN RGBD→grayscale with 7-channel augmented input
skal
45 hours
feat: Add multi-layer CNN support with framebuffer capture and blend control
skal
47 hours
feat: Add checkpointing support to CNN training script
skal
47 hours
fix: Auto-expand single kernel size to all layers in training script
skal
47 hours
feat: Add coordinate-aware CNN layer 0 for position-dependent stylization
skal