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The post-processing (DBNet contour → bbox, CTC greedy decode) stays in
TypeScript — both are trivial and runtime-portable. This C++ library runs only
the forward pass; the JS caller orchestrates det → crop → rec → decode.
Status
Phase 1 (current): FFI surface scaffolded; weight conversion script
authored; build glue authored. GGUF weight files are not yet built. The TS
binding throws a clear error until vision/doctr-det.gguf and
vision/doctr-rec.gguf are present on disk.
The detection variant writes a single tensor graph + mean/std metadata.
The recognition variant additionally writes the character vocabulary as a
doctr.charset KV entry inside the GGUF file.
ABI
See include/doctr.h. The ABI is intentionally minimal: