| --- |
| language: |
| - ko |
| library_name: doctr |
| --- |
| |
| <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 TensorFlow 2 & PyTorch** |
|
|
| ## Task: recognition |
|
|
| https://github.com/mindee/doctr |
|
|
| ### Example usage: |
|
|
| ```python |
| >>> 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) |
| ``` |