|
--- |
|
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: detection |
|
|
|
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) |
|
``` |