Downloads · 30 days
39
100% of all-time downloads
doctr-fast-base-detection-v1
Filiphw/doctr-fast-base-detection-v1
doctr-fast-base-detection-v1 is a machine learning model from Filiphw. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for doctr.
<p align="center" <img src="https://doctr-static.mindee.com/models?id=v0.3.1/Logodoctr.gif&src=0" width="60%" </p
All-time downloads
39
Public
Repo size
65.8 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin65.8 MB · 100%
At a glance
- Library
- doctr
- Access
- Public
- Created
- Sep 9, 2026
- Updated
- Sep 9, 2026
- SHA
- 5689cc9a
Model card
From the Hugging Face model README
<p align="center">
<img src="https://doctr-static.mindee.com/models?id=v0.3.1/Logo_doctr.gif&src=0" width="60%">
</p>
Optical Character Recognition made seamless & accessible to anyone, powered by PyTorch
Task: detection
https://github.com/mindee/doctr
Example usage:
>>> from doctr.io import DocumentFile
>>> from doctr.models import ocr_predictor, from_hub
>>> img = DocumentFile.from_images(['<image_path>'])
>>> # Load your model from the hub
>>> model = from_hub('mindee/my-model')
>>> # Pass it to the predictor
>>> # If your model is a recognition model:
>>> predictor = ocr_predictor(det_arch='db_mobilenet_v3_large',
>>> reco_arch=model,
>>> pretrained=True)
>>> # If your model is a detection model:
>>> predictor = ocr_predictor(det_arch=model,
>>> reco_arch='crnn_mobilenet_v3_small',
>>> pretrained=True)
>>> # Get your predictions
>>> res = predictor(img)
- Library
- doctr
- Languages
- en
- Created
- Sep 9, 2026
- Updated
- Sep 9, 2026