pyflink.multimodal.expression.ImageExpressionAccessor.ocr

ImageExpressionAccessor.ocr(*, lang: Optional[Union[List[str], Tuple[str, ...]]] = None, model_sharing: Optional[Literal['process', 'shared']] = None, concurrency: Optional[int] = None, batch_size: Optional[int] = None, num_gpus: Optional[float] = None, gpu_type: Optional[str] = None) → pyflink.table.expression.Expression

Run OCR on image values.

Equivalent to image_ocr(). See that function for full parameter details.

Parameters

• lang – Optional OCR language-code sequence.

• model_sharing – Optional model sharing mode.

• concurrency – Optional execution concurrency for this operation. None uses the framework default.

• batch_size – Optional inference batch size.

• num_gpus – Optional number of GPUs requested for model inference.

• gpu_type – Optional GPU type requested for model inference.

Returns

A DataFrame expression that produces ARRAY<ROW> OCR results with text, confidence, and bbox fields.