Descriptors

Descriptors

Descriptors(client: Connector = None, response: dict = None, type: str = None, spec: Query = None)

Bases: Entities

Python wrapper for ApertureDB Descriptors API.

find_similar

find_similar(set: str, vector, k_neighbors: int, constraints=None, distances: bool = False, blobs: bool = False, results={'all_properties': True})

Find similar descriptors to the input descriptor.

Parameters:

Name	Type	Description	Default
set	str	Descriptor set name.	required
vector	list	Input descriptor vector.	required
k_neighbors	int	Number of neighbors to return.	required
constraints	Constraints	Constraints for the search. Defaults to None.	None
distances	bool	Return similarity metric values. Defaults to False.	False
blobs	bool	Return vectors of the neighbors. Defaults to False.	False
results	dict	Dictionary with the results format. Defaults to {"all_properties": True}.	{'all_properties': True}

Returns:

Name	Type	Description
None		Populates self.response with the parsed JSON response from the database.

find_similar_mmr

find_similar_mmr(set: str, vector, k_neighbors: int, fetch_k: int, lambda_mult: float = 0.5, **kwargs)

As find_similar, but using the MMR algorithm to diversify the results.

Args:

set (str): Descriptor set name.
vector (list): Input descriptor vector.
k_neighbors (int): Number of results to return.
fetch_k (int): Number of neighbors to fetch from the database.
lambda_mult (float): Lambda multiplier for the MMR algorithm.
    Defaults to 0.5.  1.0 means no diversity.