PARSEq Text Recognition model for Arabic language
Use with the DocTr.
Example usage:
>>> from doctr.io import DocumentFile
>>> from doctr.models import ocr_predictor, from_hub
>>> img = DocumentFile.from_images(['<image_path>'])
>>> # Load your models from the hub
>>> reco_model = from_hub("madskills/parseq_arabic_v1")
>>> # Load custom detection model for best performance
>>> det_model = from_hub("madskills/fast_base_arabic_v1")
>>> # Pass it to the predictor
>>> # If your model is a recognition model:
>>> predictor = ocr_predictor(det_arch=det_model,
>>> reco_arch=reco_model,
>>> pretrained=True
>>> )
>>> # optional if your documents are not well oriented
>>> # custom crop and page orientation predictors
>>> page_orientation_model = from_hub("madskills/mobilenet_v3_small_page_orientation_arabic")
>>> crop_orientation_model = from_hub("madskills/mobilenet_v3_small_crop_orientation_arabic")
# set the custom orientation predictors
>>> predictor.crop_orientation_predictor = crop_orientation_predictor(
>>> pretrained=False, arch=crop_orientation_model
>>> )
>>> predictor.page_orientation_predictor = page_orientation_predictor(
>>> pretrained=False, arch=page_orientation_model
>>> )
>>> # Get your predictions
>>> res = predictor(img)
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