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path: root/training/train_cnn.py
AgeCommit message (Expand)Author
23 hoursrefactor: Use linspace(-1,1) directly for coordsskal
23 hoursfix: Compute gray from [0,1] RGB in CNN shader generatorskal
29 hoursadd --save-intermediates to train.py and cnn_testskal
29 hoursfix: Move sigmoid activation to call site in CNN layer shaderskal
29 hoursfix: Replace clamp with sigmoid in CNN final layerskal
30 hoursfeat: Add early stopping to CNN trainingskal
30 hoursfix: CNN training/inference to match WGSL sliding windowskal
30 hoursformat .wgsl layer code (cosmetics)skal
39 hoursfix: Use patch-based inference to match CNN training distributionskal
39 hoursopt: Move invariant in1 calculation outside CNN convolution loopsskal
40 hoursopt: Vec4-optimize CNN convolution shaders for SIMDskal
41 hoursfeat: Add salient-point patch extraction for CNN trainingskal
42 hoursfix: Correct UV coordinate computation to match PyTorch linspaceskal
42 hoursfix: Add clamp to CNN final layer to match PyTorch trainingskal
42 hoursrefactor: Optimize CNN grayscale computationskal
42 hoursupdate train_cnn.py and shaderskal
43 hoursfeat: Add inference mode to train_cnn.py for ground truth generationskal
44 hoursfix: CNN training normalization pipeline consistencyskal
45 hoursrefactor: Optimize CNN normalization to eliminate redundant conversionsskal
46 hoursfix: Support variable kernel sizes in CNN layer generationskal
47 hoursfeat: CNN RGBD→grayscale with 7-channel augmented inputskal
2 daysfeat: Add multi-layer CNN support with framebuffer capture and blend controlskal
2 daysfeat: Add checkpointing support to CNN training scriptskal
2 daysfix: Auto-expand single kernel size to all layers in training scriptskal
2 daysfeat: Add coordinate-aware CNN layer 0 for position-dependent stylizationskal