pyflink.multimodal.expression.ImageExpressionAccessor.text_similarity#

ImageExpressionAccessor.text_similarity(*, text_column: Optional[pyflink.table.expression.Expression] = None, text: Optional[str] = None, model: str = 'ViT-B/32', pretrained: str = 'openai', 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[source]#

Compute similarity between image values and text.

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

Exactly one of text_column or text must be provided.

Parameters

  • text_column – Text expression compared with this image expression.

  • text – Constant text compared with this image expression.

  • model – CLIP-style model name.

  • pretrained – Pretrained weights identifier.

  • 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 a DOUBLE similarity score.