Instructions to use openmasq/doctr-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- docTR
How to use openmasq/doctr-onnx with docTR:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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Download README.md from openmasq/doctr-onnx: direct link, hf CLI and curl.
- Browser
- Download file 1.07 kB
-
https://huggingface.co/openmasq/doctr-onnx/resolve/main/README.md
- Command line
-
hf download hf://openmasq/doctr-onnx/README.md
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curl -L -o README.md https://huggingface.co/openmasq/doctr-onnx/resolve/main/README.md
1.07 kB
metadata
license: apache-2.0
library_name: onnx
tags:
- ocr
- doctr
- text-detection
- text-recognition
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.