Commit Graph

2 Commits

Author SHA1 Message Date
Devin AI
d0e1835cc1 Phase 2: document detection + perspective correction + shadow removal
Adds OpenCV-based phone-photo handling that runs before the standard
preprocessing pipeline for IMAGE source kinds (PDF renders are flat by
construction and skip this stage).

Pipeline additions in src/ocr_sprint/pipeline/document_detect.py:
- _find_document_quad: Canny + dilate + contour search, picks the
  largest convex 4-point polygon above a configurable area threshold;
  fails gracefully and returns None when no usable quad is found.
- _four_point_warp: orders corners (TL/TR/BR/BL via sum/diff trick)
  and runs cv2.getPerspectiveTransform + warpPerspective.
- _remove_shadow: per-channel background-division (dilate + median
  blur + 255 - absdiff + normalize) for uneven phone-shot lighting.
- detect_and_correct: top-level entrypoint with graceful fallback
  to the original image when detection fails.

Wired into the synchronous orchestrator: only enabled for IMAGE
sources, skipped for PDF. New settings:
- preprocess_detect_document (default: true)
- preprocess_remove_shadow (default: true)
- preprocess_min_quad_area_fraction (default: 0.20)

Tests: 9 new unit tests covering corner ordering, quad detection on
synthetic skewed documents, perspective warp output sanity, shadow
removal shape preservation, full-pipeline behavior, and graceful
fallback when detection fails. 70 tests total, all green.

ML-based dewarping (DewarpNet) and DocTR detector are deferred to a
future phase per the roadmap; the existing API is structured so they
can be added as alternative backends behind DocumentDetectConfig.

Co-authored-by: adrian kuman firmansah <adriancuman@gmail.com>
2026-04-25 15:06:58 +00:00
Devin AI
ca0c0a0428 Phase 1 MVP: synchronous OCR + regex header extraction
Implements the foundation of the OCR Sprint service:
- FastAPI app with /api/v1/health and /api/v1/documents (sync upload)
- Pydantic v2 schemas for documents, extraction result, personnel
- Pipeline: PDF/image ingest (PyMuPDF), preprocessing (resize, deskew,
  denoise, optional adaptive threshold), PaddleOCR wrapper, regex-based
  header extraction (nomor sprint, tanggal, satuan, perihal, dasar),
  signatory NRP, master-pangkat validation, confidence scoring + routing.
- Tests: 61 unit tests covering regex rules, validators, preprocess,
  ingest, confidence, and API contract (PaddleOCR mocked).
- Tooling: pyproject (setuptools), ruff, mypy strict, pytest, pre-commit,
  Dockerfile, docker-compose, Makefile.
- Docs: README + docs/architecture.md (full hybrid stack rationale and
  6-phase roadmap).

Co-authored-by: adrian kuman firmansah <adriancuman@gmail.com>
2026-04-25 14:58:50 +00:00