train_classifier.py's split_dataset() previously shuffled and split
individual image files, letting an augmented copy (photo_aug_2.jpeg) land
in validation while its near-duplicate source stayed in training -
inflating val accuracy with memorization rather than measuring real
generalization. Now groups by source photo (stripping _aug_N) before
shuffling and splitting 80/20.
Also records the in-progress effort to retrain the product classifier
against the full 81-class/2,493-photo foto-kemasan-v2 dataset (up from the
16 classes/118 photos the deployed model was actually trained on) - see
plans/next-enhancements.md task 2.5 and the accompanying iteration-log
entry for the real, currently-observed numbers (DINOv2 index rebuilt:
2493/2493 images; classifier training: in progress, ~32s/epoch observed).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Xsxk4ZkDQVVaLUcixDcqb5
Fixes reported from APK field testing: DO/Product scan mode was inconsistent
between the camera drawer and documents screen (now one shared provider,
with an orange/green color cue); unconfirmed scans leaked into history with
placeholder data before the user tapped confirm (backend now gates
GET /documents on a new `confirmed` column, flipped only by PUT); and
Product Scan ran the GPU classifier twice, once at upload and again on
review (now a single pass at upload, persisted and read directly by the
editor). Also removes the unused "Hubungkan ke PO" field and fabricated
PO/SO/DO placeholder values from the Product Scan flow, closes out the
per-document-polling and save-recovery tasks (6.1/6.3), and splits several
touched files to stay under the repo's 256-line guideline.
Full detail in docs/iteration-log.md and backend/docs/iteration-log.md.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Rafhan Mazaya FathurrahmanandClaude Sonnet 5