^Nj`ddlmZmZddlmZddlmZddlmZddlm Z GddeeZ y) )IterableAny)DenseModelDescription) NumpyArray)ModelManagement) ImageInputc eZdZ ddededzdedzdefdZ ddeeezded edzded ee f d Z e ded efd Z e d efd Zy)ImageEmbeddingBaseN model_name cache_dirthreadskwargsc j||_||_||_|jdd|_d|_y)Nlocal_files_onlyF)r r r pop_local_files_only_embedding_size)selfr r r rs u/Users/ahmed/devFolder/Ultron/claude-voice/.venv/lib/python3.12/site-packages/fastembed/image/image_embedding_base.py__init__zImageEmbeddingBase.__init__ s5%" !',>!F+/images batch_sizeparallelreturnc t)au Embeds a list of images into a list of embeddings. Args: images: The list of image paths to preprocess and embed. batch_size: Batch size for encoding parallel: If > 1, data-parallel encoding will be used, recommended for offline encoding of large datasets. If 0, use all available cores. If None, don't use data-parallel processing, use default onnxruntime threading instead. **kwargs: Additional keyword argument to pass to the embed method. Yields: Iterable[NdArray]: The embeddings. NotImplementedError)rrrrrs rembedzImageEmbeddingBase.embeds ,"##rctd)z+Returns embedding size of the chosen model.%Subclasses must implement this methodr)clsr s rget_embedding_sizez%ImageEmbeddingBase.get_embedding_size/""IJJrctd)z,Returns embedding size for the current modelr!r)rs rembedding_sizez!ImageEmbeddingBase.embedding_size4r$r)NN)N)__name__ __module__ __qualname__strintrrrrrr classmethodr#propertyr&rrr r s!%" 0 0: 0t 0  0 # $Xj11$$* $  $ *  $0KCKCKKKKKrr N) typingrr"fastembed.common.model_descriptionrfastembed.common.typesr!fastembed.common.model_managementrrr r/rrr4s( D-=-.K)>?.Kr