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>

.env.example

@@ -21,6 +21,11 @@ PREPROCESS_DENOISE=true
 PREPROCESS_DESKEW=true
 PREPROCESS_ADAPTIVE_THRESHOLD=false  # turn on for low-quality phone photos
 
+# ==== Document detection (Phase 2, IMAGE sources only) ====
+PREPROCESS_DETECT_DOCUMENT=true
+PREPROCESS_REMOVE_SHADOW=true
+PREPROCESS_MIN_QUAD_AREA_FRACTION=0.20
+
 # ==== Confidence / routing (Phase 5) ====
 CONFIDENCE_AUTO_APPROVE=0.95
 CONFIDENCE_NEEDS_REVIEW=0.85