import base64

import pytest

from app.detector import MockDetector, abnormal_probability, detection_status

# 1x1 透明 PNG
TINY_PNG = base64.b64decode(
    "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8BQDwAEhQGAhKmMIQAAAABJRU5ErkJggg=="
)


def test_mock_detector_returns_canned_detection():
    det = MockDetector(class_name="sick", confidence=0.92)
    result = det.detect(TINY_PNG)
    assert len(result) == 1
    assert result[0]["class_name"] == "sick"
    assert result[0]["confidence"] == 0.92
    assert result[0]["bbox"]["w"] > 0


def test_mock_detector_rejects_invalid_image():
    det = MockDetector()
    with pytest.raises(ValueError):
        det.detect(b"not an image")


def test_abnormal_probability_ignores_healthy_and_unknown():
    detections = [
        {"class_name": "healthy", "confidence": 0.95},
        {"class_name": "unknown", "confidence": 0.8},
        {"class_name": "sick", "confidence": 0.72},
    ]
    assert abnormal_probability(detections, ("healthy", "sick")) == 0.72


def test_detection_status_returns_unknown_for_empty_or_unknown():
    assert detection_status([], ("healthy", "sick")) == "unknown"
    assert detection_status([{"class_name": "unknown", "confidence": 0.8}], ("healthy", "sick")) == "unknown"
    assert detection_status([{"class_name": "healthy", "confidence": 0.95}], ("healthy", "sick")) == "healthy"
    assert detection_status(
        [{"class_name": "white_muscardine", "confidence": 0.7}],
        ("healthy", "white_muscardine", "nuclear_polyhedrosis"),
    ) == "abnormal"