quaterion.dataset.similarity_samples module

class SimilarityGroupSample(obj: Any, group: int)[source]

Bases: object

Represent groups of similar objects all of which should match with one-another within the group.

Examples:

Faces dataset.
All pictures of a single person should have single unique group
id. In this case NN will learn to match all pictures within
the group closer to each-other, but pictures from different
groups - further.

             file_name  group_id
0      elon_musk_1.jpg       555
1      elon_musk_2.jpg       555
2      elon_musk_3.jpg       555
3  leonard_nimoy_1.jpg       209
4  leonard_nimoy_2.jpg       209

group: int

obj: Any

class SimilarityPairSample(obj_a: Any, obj_b: Any, score: float = 1.0, subgroup: int = 0)[source]

Bases: object

Represents a pair of objects, their similarity and relationship with other pairs.

Examples:

data = [
    # First query group (subgroup)
    SimilarityPairSample(
        obj_a="cheesecake",
        obj_b="muffins",
        score=0.9,
        subgroup=10
    ),
    SimilarityPairSample(
        obj_a="cheesecake",
        obj_b="macaroons",
        score=0.8,
        subgroup=10
    ),
    SimilarityPairSample(
        obj_a="cheesecake",
        obj_b="candies",
        score=0.7,
        subgroup=10
    ),

    # Second query group (subgroup)
    SimilarityPairSample(
        obj_a="lemon",
        obj_b="lime",
        score=0.9,
        subgroup=11
    ),
    SimilarityPairSample(
        obj_a="lemon",
        obj_b="orange",
        score=0.7,
        subgroup=11
    ),
]

obj_a: Any

obj_b: Any

score: float = 1.0

Similarity score between Object A and B. It is assumed, that score = 1.0 - means objects are similar, score = 0.0 objects are completely different.

subgroup: int = 0

Consider all examples outside this group as negative samples. By default, all samples belong to group 0 - therefore other samples could not be used as negative examples.