from typing import Mapping, List

import numpy as np

from image_prediction.estimator.adapter.adapter import EstimatorAdapter
from image_prediction.utils import get_logger

logger = get_logger()


class Classifier:
    def __init__(self, estimator_adapter: EstimatorAdapter, classes: Mapping[int, str]):
        """Abstraction layer over different estimator backends (e.g. keras or scikit-learn). For each backend to be used
        an EstimatorAdapter must be implemented.

        Args:
            estimator_adapter: adapter for a given estimator backend; expected to be a classifier that returns numeric
                labels as predictions
            classes: mapping from a numerical label to a human-readable label for classes
        """
        self.__estimator_adapter = estimator_adapter
        self.__classes = classes

    def predict(self, batch: np.array) -> List[str]:

        if batch.shape[0] == 0:
            return []

        return [self.__classes[numeric_label] for numeric_label in self.__estimator_adapter.predict(batch)]

    def __call__(self, batch: np.array) -> List[str]:
        return self.predict(batch)