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language: |
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- en |
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- da |
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- fr |
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- it |
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- es |
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- de |
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- pt |
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- cs |
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- pl |
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- nl |
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- 'no' |
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- fi |
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license: apache-2.0 |
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--- |
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<p align="center"> |
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<img src="https://doctr-static.mindee.com/models?id=v0.3.1/Logo_doctr.gif&src=0" width="60%"> |
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</p> |
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**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch** |
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## Task: recognition |
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https://github.com/mindee/doctr |
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### Example usage: |
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```python |
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>>> from doctr.io import DocumentFile |
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>>> from doctr.models import ocr_predictor, from_hub |
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>>> img = DocumentFile.from_images(['<image_path>']) |
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>>> # Load your model from the hub |
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>>> model = from_hub('mindee/my-model') |
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>>> # Pass it to the predictor |
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>>> # If your model is a recognition model: |
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>>> predictor = ocr_predictor(det_arch='db_mobilenet_v3_large', |
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>>> reco_arch=model, |
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>>> pretrained=True) |
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>>> # If your model is a detection model: |
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>>> predictor = ocr_predictor(det_arch=model, |
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>>> reco_arch='crnn_mobilenet_v3_small', |
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>>> pretrained=True) |
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>>> # Get your predictions |
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>>> res = predictor(img) |
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``` |
