"""Model 3 — YAMNet binary baby-cry detector via TensorFlow Hub."""

from __future__ import annotations

import time

import numpy as np

from models.base import CryClassifier, CryPrediction, display_label


# "Baby cry, infant cry" class index in the AudioSet ontology used by YAMNet.
_BABY_CRY_CLASS_INDEX = 20


class YAMNetDetector(CryClassifier):
    name = "YAMNet-detector"
    description = "YAMNet (TF Hub) binary cry detector — gates the reason classifiers"

    def __init__(self) -> None:
        super().__init__()
        self._model = None

    def load(self) -> None:
        import tensorflow_hub as hub

        self._model = hub.load("https://tfhub.dev/google/yamnet/1")
        self._loaded = True

    def predict(self, audio_np: np.ndarray, sr: int) -> CryPrediction:
        import tensorflow as tf
        from audio.preprocess import SAMPLE_RATE, resample

        t0 = time.perf_counter()
        try:
            if sr != SAMPLE_RATE:
                audio_np = resample(audio_np, sr, SAMPLE_RATE)

            waveform = tf.cast(audio_np, tf.float32)
            scores, embeddings, spectrogram = self._model(waveform)

            # scores shape: (num_frames, 521)
            scores_np = scores.numpy()
            cry_scores = scores_np[:, _BABY_CRY_CLASS_INDEX]
            avg_cry_score = float(np.mean(cry_scores))

            is_cry = avg_cry_score >= 0.4
            label_raw = "cry" if is_cry else "not_cry"

            latency = (time.perf_counter() - t0) * 1000
            return CryPrediction(
                model_name=self.name,
                label=label_raw,
                display_label=display_label(label_raw),
                confidence=avg_cry_score,
                latency_ms=latency,
            )
        except Exception as exc:
            latency = (time.perf_counter() - t0) * 1000
            return CryPrediction(
                model_name=self.name,
                label="error",
                display_label="⚠️ Error",
                confidence=0.0,
                latency_ms=latency,
                error=str(exc),
            )