Thanks. A few diagrams on the spatial layout and information flow between stages would indeed go a long way. I'll take that up in the upcoming commits.
11 karma · joined July 11, 2026
For a breakdown of the algo's stages on an image, the -d flag on inference generates detailed views like cell density, orientations, etc.
I've developed an edge detection algorithm inspired by functions of the visual cortex such as divisive normalization and spatial pooling. This goal here is to sit in the class of compact methods like Canny, while having a small set of trainable parameters that adjust to data.