docTR ONNX models for OpenMasq

ONNX exports of two pretrained docTR models by Mindee, used by the OpenMasq desktop app for on-device OCR of Latin-script documents:

file	docTR architecture	sha256
`db_mobilenet_v3_large.onnx`	text detection, `db_mobilenet_v3_large`	`5a82788a1907dccec9978c756f56d386fd2242597ba2630322da063af44cf4d3`
`crnn_mobilenet_v3_small.onnx`	text recognition, `crnn_mobilenet_v3_small`	`d89bbd3e732261c341c4cd50e3ad879233c852062866fd55b32c7d431dce301d`

Provenance. Exported from Mindee's official pretrained weights with docTR's own export_model_to_onnx; no retraining, no third-party re-upload.

Integrity. The app pins these sha256 values: the build verifies each file before bundling it, and the app verifies it again before onnxruntime loads it. A different byte content is refused.

License. Apache-2.0, as docTR and its pretrained weights.

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