dataeval.models.LiteRtImageClassifier¶

class dataeval.models.LiteRtImageClassifier(model_path, metadata_path, *, image_size=None, scores_name='scores')¶

Opinionated image classifier backed by LiteRT (TensorFlow Lite).

Loads an exported .tflite image-classification model via a LiteRT interpreter together with its model-metadata.json contract, then maps a batch of CHW images to per-image class scores. Calling the instance preprocesses each image to the model’s input contract (color layout, size, [0, 1] normalization), runs inference, and returns one (nClasses,) float32 score array per image. Requires dataeval[tflite].

Parameters:¶

model_path : str or Path¶: Path to the exported .tflite model file.
metadata_path : str or Path¶: Path to the model-metadata.json describing the input/output contract. Its declared task must be IMAGE_CLASSIFICATION.
image_size : tuple[int, int] or None, default None¶: Optional (height, width) override for the model’s input size. When set, images are resized to this size instead of the size declared in metadata; required when the metadata declares a variable (-1) dimension.
scores_name : str, default "scores"¶: Name of the model output tensor holding class scores.

Raises:¶

ValueError – If the metadata declares a task other than IMAGE_CLASSIFICATION.
ImportError – If neither tflite-runtime nor tensorflow is installed.
FileNotFoundError – If model_path does not exist.