dlpy.image_captioning.create_embeddings_from_object_detection¶
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dlpy.image_captioning.create_embeddings_from_object_detection(conn, image_table, detection_model, word_embeddings_file, n_threads=None, gpu=None, max_objects=5, word_delimiter='\t')¶ Builds CASTable with objects detected in images as numeric data
- Parameters
- connCAS
Specifies the CAS connection object.
- image_table: imageTable
Specifies name of CASTable that contains images to be used for training
- detection_modelCASTable or string
Specifies CASTable containing model parameters for the object detection model
- word_embeddings_filestring
Specifies full path to file containing pre-trained word vectors to be used for text generation This file should be accessible from the client.
- n_threadsint, optional
Specifies the number of threads to use when scoring the table. All cores available used when nothing is set. Default : None
- gpuGpu, optional
When specified, specifies which gpu to use when scoring the table. GPU=1 uses all available GPU devices and default parameters. Default : None
- max_objectsint, optional
Specifies max number of objects detected if less than five Default : 5
- word_delimiterstring, optional
Specifies delimiter used in word_embeddings file Default : ‘ ‘
- Returns
- ——-
- :class:`CASTable`