Thareah/ThaOCR-textdet

ThaOCR textdet — text-line detector for Khmer + English documents (DB, ONNX)

Stage 2 of 5 of the ThaOCR pipeline. Finds text lines inside a page or region. DB (Differentiable Binarization) with the PaddleOCR PP-OCRv5 mobile backbone, 1.16 M parameters. Dynamic input [1,3,H,W] (H and W multiples of 32); the output is a probability map and boxes are recovered with the original DB unclip post-processing.

Models

id	version	file	size	description
db_ppocrv5_khmer_v1	v1	textdet/db_v1.onnx	4.8 MB	DB PP-OCRv5 mobile, Khmer fine-tuned v1
db_ppocrv5_orig	v0	textdet/db_ppocrv5_orig.onnx	4.8 MB	DB PP-OCRv5 mobile (original)
db_ppocrv5_khmer_v2 (default)	v2	textdet/db_v2.onnx	4.8 MB	DB PP-OCRv5 mobile v2 (docs + exam sheets + handwriting)

db_ppocrv5_orig.onnx is the unmodified PaddleOCR PP-OCRv5 mobile detector (Apache-2.0), included as the baseline and not trained by us. db_v1.onnx is the first Khmer fine-tune on synthetic Khmer pages + real Khmer PDF pages + DocLayNet.

How db_v2.onnx (default) was trained

det/train_textdet.py (in the older Khm-Dataset-Creation repo) converts the original ONNX detector to PyTorch (onnx2torch) and fine-tunes the probability map with DB shrunk kernels (ratio 0.4), then exports back to ONNX with the same input/output contract.

• 20,000 iterations, batch 16, --robust augmentation (scan/photo degradation), initialised from the textdet_robust checkpoint of v1.
• Loss weights per source: synthetic 0.45, Khmer PDF 0.20, DocLayNet 0.35. Evaluation every 2,500 iterations.
• Dataset textdet_v2: synthetic 15,000 train / 750 val docgen pages (v2 documents + exam sheets + handwriting lines, line quads tight to the ink); real DocLayNet 6,895 train / 647 val pages with line boxes from the PDF text layer; real Khmer PDF pages 548 train / 173 val.
• Final F1: synthetic 0.894, DocLayNet 0.880 (0.833 low-res), Khmer PDF 0.697 (0.690 low-res); mean 0.799.

Training data and licences

data	type	licence
docgen v2 / exam synthetic pages and handwriting lines	synthetic	generated
DocLayNet v2	real	CDLA-Permissive 1.0
Real Khmer PDF pages (government / NGO PDF crawl)	real	research use

Base model: PaddleOCR PP-OCRv5 mobile detector (Apache-2.0). Because part of the fine-tuning data is research-use only, the licence field is other: check that your use fits those terms. The owner's private exam photos were never used for training.

Part of ThaOCR

ThaOCR is a five-stage Khmer + English document OCR pipeline (layout, text-line detection, line recognition, font classification, page structure). Every model is plain ONNX (opset 17) and runs with onnxruntime on CPU. There is one repo per stage:

stage	repo
layout	Thareah/ThaOCR-layout
textdet	Thareah/ThaOCR-textdet (this repo)
rec	Thareah/ThaOCR-rec
font	Thareah/ThaOCR-font
structure	Thareah/ThaOCR-structure

The index repo Thareah/ThaOCR-models holds the full models.json manifest for all five stages. models.textdet.json in this repo lists only this stage. The file and vocab paths in both are relative to a folder into which all stage repos are downloaded together, for example hf download Thareah/ThaOCR-textdet --local-dir ThaOCR. The pre/post-processing (letterbox + NMS, DB unclip, width bucketing + CTC, ...) is small numpy/OpenCV code in the ThaOCR backend (backend/app/services/stages/).