"""Provider tests for ImageQualityProvider."""

from __future__ import annotations

import cv2
import numpy as np
import pytest

from config.settings import Settings
from pipeline.feature_extraction import PipelineOutput
from providers.image_analysis.image_quality import ImageQualityProvider


@pytest.fixture
def quality_provider():
    return ImageQualityProvider(settings=Settings(environment="test", db_path=":memory:"))


@pytest.fixture
def pipeline_output(sample_image_bytes):
    img = cv2.imdecode(np.frombuffer(sample_image_bytes, np.uint8), cv2.IMREAD_COLOR)
    return PipelineOutput(
        image=img, image_hash="h", width=img.shape[1], height=img.shape[0], source="bytes",
        original_bytes=sample_image_bytes, original_format=".jpg",
    )


class TestImageQualityProvider:
    def test_name(self, quality_provider):
        assert quality_provider.name == "image_quality"

    def test_capability(self, quality_provider):
        from models.providers import ProviderCapability
        assert quality_provider.capability == ProviderCapability.IMAGE_ANALYSIS

    def test_is_available(self, quality_provider):
        assert quality_provider.is_available() is True

    def test_execute_returns_metrics(self, quality_provider, pipeline_output):
        result = quality_provider.execute(pipeline_output)
        assert result.success is True
        n = result.normalized
        assert "brightness" in n
        assert "contrast" in n
        assert "sharpness" in n
        assert "noise_level" in n
        assert "quality_score" in n
        assert isinstance(n["brightness"], float)
        assert isinstance(n["quality_score"], float)

    def test_quality_score_in_range(self, quality_provider, pipeline_output):
        result = quality_provider.execute(pipeline_output)
        q = result.normalized["quality_score"]
        assert 0.0 <= q <= 1.0

    def test_black_image_low_brightness(self, quality_provider):
        img = np.zeros((200, 200, 3), dtype=np.uint8)
        po = PipelineOutput(image=img, image_hash="h", width=200, height=200, source="bytes")
        result = quality_provider.execute(po)
        assert result.normalized["brightness"] < 10.0  # near-black

    def test_white_image_high_brightness(self, quality_provider):
        img = np.full((200, 200, 3), 255, dtype=np.uint8)
        po = PipelineOutput(image=img, image_hash="h", width=200, height=200, source="bytes")
        result = quality_provider.execute(po)
        assert result.normalized["brightness"] > 240.0