dlpy.image_embedding.ImageEmbeddingTable.load_files¶
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classmethod
ImageEmbeddingTable.load_files(conn, path, casout=None, columns=None, caslib=None, embedding_model_type='Siamese', n_samples=512, label_level=-2, resize_width=None, resize_height=None)¶ Create ImageEmbeddingTable from files in path
Parameters: - conn : CAS
The CAS connection object
- path : string
The path to the image directory on the server. Path may be absolute, or relative to caslib root if specified.
- casout : dict, optional
The output table specifications
- columns : list of str, optional
Specifies the extra columns in the image table.
- caslib : string, optional
The name of the caslib containing the images.
- embedding_model_type : string, optional
Specifies the embedding model type that the created table will be applied for training.
Valid Values: Siamese, Triplet, and Quartet.
Default: Siamese- n_samples : int, optional
Number of samples to generate.
Default: 512- label_level : int, optional
Specifies which path level should be used to generate the class labels for each image. This class label determines whether a given image pair belongs to the same class. For instance, label_level = 1 means the first directory and label_level = -2 means the last directory. This internally use the SAS scan function (check https://www.sascrunch.com/scan-function.html for more details).
Default: -2- resize_width : int, optional
Specifies the image width that needs be resized to. When resize_width is not given, it will be reset to the specified resize_height.
- resize_height : int, optional
Specifies the image height that needs be resized to. When resize_height is not given, it will be reset to the specified resize_width.
Returns: