ImageEmbedding

Represents custom features derived from image embeddings for visual content analysis. ImageEmbedding extends VectorFeature to handle image-based embeddings, providing clustering analysis specifically designed for visual content. This feature type is used to monitor image models and detect visual drift in high-dimensional embedding spaces. The feature type is automatically set to CustomFeatureType.FROM_IMAGE_EMBEDDING and applies clustering to image embeddings for visual pattern analysis.

Examples

Creating an image embedding feature for product photos:

image_feature = ImageEmbedding(
    name="product_image_clusters",
    column="product_embedding",
    source_column="product_image_url",
    n_clusters=15
)

Creating a feature for medical image analysis:

medical_feature = ImageEmbedding(
    name="xray_pattern_clusters",
    column="xray_embedding",
    source_column="xray_image_path",
    n_clusters=10
)

type

source_column

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

EventIdDataSource

ModelSchema

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Examples

type

source_column

model_config

​Examples

​type

​source_column

​model_config

Examples

type

source_column

model_config