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Vide-coded 64k demo system
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29 hours
fix: Add clamp to CNN final layer to match PyTorch training
skal
30 hours
refactor: Optimize CNN grayscale computation
skal
30 hours
update train_cnn.py and shader
skal
31 hours
feat: Add inference mode to train_cnn.py for ground truth generation
skal
31 hours
fix: CNN training normalization pipeline consistency
skal
32 hours
refactor: Optimize CNN normalization to eliminate redundant conversions
skal
33 hours
fix: Support variable kernel sizes in CNN layer generation
skal
34 hours
feat: CNN RGBD→grayscale with 7-channel augmented input
skal
35 hours
udpate
skal
38 hours
feat: Add multi-layer CNN support with framebuffer capture and blend control
skal
40 hours
docs: Update and streamline CNN training documentation
skal
40 hours
feat: Add checkpointing support to CNN training script
skal
40 hours
fix: Auto-expand single kernel size to all layers in training script
skal
40 hours
update target images
skal
40 hours
feat: Add coordinate-aware CNN layer 0 for position-dependent stylization
skal