#include <gtest/gtest.h>

#include "converter/pipeline/Pipeline.h"
#include "converter/pipeline/ImageData.h"
#include "converter/pipeline/Error.h"
#include "converter/preprocess/Preprocessor.h"
#include "converter/negative/NegativeDetector.h"
#include "converter/invert/Inverter.h"
#include "converter/color/ColorCorrector.h"
#include "converter/crop/CropProcessor.h"
#include "config/AppConfig.h"

#include <opencv2/core.hpp>

#include <filesystem>
#include <fstream>

using namespace photoconv;

/**
 * @brief Create a synthetic 16-bit test image.
 *
 * @param width  Image width.
 * @param height Image height.
 * @param value  Fill value for all channels (0-65535).
 * @return CV_16UC3 Mat filled with the given value.
 */
static ImageData make_test_image(int width, int height, uint16_t value) {
    ImageData data;
    data.rgb = cv::Mat(height, width, CV_16UC3, cv::Scalar(value, value, value));
    data.source_path = "test_synthetic.png";
    data.metadata.camera_make  = "Test";
    data.metadata.camera_model = "Synthetic";
    return data;
}

/**
 * @brief Create a synthetic gradient test image.
 *
 * Useful for levels-adjustment and crop tests that need non-uniform content.
 */
static ImageData make_gradient_image(int width, int height) {
    ImageData data;
    data.rgb = cv::Mat(height, width, CV_16UC3);
    data.source_path = "test_gradient.png";
    data.metadata.camera_make = "Test";

    for (int y = 0; y < height; ++y) {
        for (int x = 0; x < width; ++x) {
            const uint16_t v = static_cast<uint16_t>(
                static_cast<double>(x + y) / static_cast<double>(width + height) * 65535.0);
            data.rgb.at<cv::Vec3w>(y, x) = {v, v, v};
        }
    }
    return data;
}

// ──────────────────────────────────────────────
// Pipeline orchestration tests
// ──────────────────────────────────────────────

TEST(PipelineTest, EmptyPipelinePassesThrough) {
    Pipeline pipeline;
    auto data = make_test_image(100, 100, 32768);

    auto result = pipeline.execute(std::move(data));
    ASSERT_TRUE(result.has_value());
    EXPECT_EQ(result->rgb.cols, 100);
    EXPECT_EQ(result->rgb.rows, 100);
}

TEST(PipelineTest, StageCountIsCorrect) {
    Pipeline pipeline;
    EXPECT_EQ(pipeline.stage_count(), 0);

    pipeline.add_stage(std::make_unique<Preprocessor>());
    EXPECT_EQ(pipeline.stage_count(), 1);

    pipeline.add_stage(std::make_unique<NegativeDetector>());
    EXPECT_EQ(pipeline.stage_count(), 2);
}

TEST(PipelineTest, FullPipelineRunsWithoutError) {
    Pipeline pipeline;
    pipeline.add_stage(std::make_unique<Preprocessor>());
    pipeline.add_stage(std::make_unique<NegativeDetector>());
    pipeline.add_stage(std::make_unique<Inverter>());
    pipeline.add_stage(std::make_unique<ColorCorrector>());
    pipeline.add_stage(std::make_unique<CropProcessor>());

    auto data = make_test_image(200, 200, 40000);
    auto result = pipeline.execute(std::move(data));
    ASSERT_TRUE(result.has_value());
}

TEST(PipelineTest, ProgressCallbackIsCalled) {
    Pipeline pipeline;
    pipeline.add_stage(std::make_unique<Preprocessor>());
    pipeline.add_stage(std::make_unique<NegativeDetector>());

    int callback_count = 0;
    auto data = make_test_image(100, 100, 32768);
    auto result = pipeline.execute(std::move(data),
        [&callback_count](const std::string&, float) {
            ++callback_count;
        });

    ASSERT_TRUE(result.has_value());
    // 2 stage callbacks + 1 "done" callback = 3
    EXPECT_EQ(callback_count, 3);
}

// ──────────────────────────────────────────────
// Preprocessor tests
// ──────────────────────────────────────────────

TEST(PreprocessorTest, AcceptsValidImage) {
    Preprocessor stage;
    auto data = make_test_image(100, 100, 32768);

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());
    EXPECT_EQ(result->rgb.type(), CV_16UC3);
}

TEST(PreprocessorTest, RejectsEmptyImage) {
    Preprocessor stage;
    ImageData data;

    auto result = stage.process(std::move(data));
    ASSERT_FALSE(result.has_value());
    EXPECT_EQ(result.error().code, ErrorCode::InvalidBitDepth);
}

TEST(PreprocessorTest, Converts8BitTo16Bit) {
    Preprocessor stage;
    ImageData data;
    data.rgb = cv::Mat(100, 100, CV_8UC3, cv::Scalar(128, 128, 128));
    data.source_path = "test.png";

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());
    EXPECT_EQ(result->rgb.type(), CV_16UC3);
    // 128 * 257 = 32896 ≈ 32768 midpoint
    cv::Scalar mean = cv::mean(result->rgb);
    EXPECT_GT(mean[0], 30000.0);
    EXPECT_LT(mean[0], 36000.0);
}

// ──────────────────────────────────────────────
// NegativeDetector tests
// ──────────────────────────────────────────────

TEST(NegativeDetectorTest, DetectsBrightImageAsNegative) {
    NegativeDetector stage;
    // High values = likely negative (inverted)
    auto data = make_test_image(100, 100, 50000);

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());
    EXPECT_NE(result->film_type, FilmType::Unknown);
}

TEST(NegativeDetectorTest, DetectsDarkImageAsPositive) {
    NegativeDetector stage;
    // Low values = likely positive
    auto data = make_test_image(100, 100, 10000);

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());
    // Should be classified as positive (below midpoint)
    EXPECT_TRUE(result->film_type == FilmType::ColorPositive ||
                result->film_type == FilmType::BWPositive);
}

// ──────────────────────────────────────────────
// Inverter tests
// ──────────────────────────────────────────────

TEST(InverterTest, InvertsNegative) {
    Inverter stage;
    auto data = make_test_image(10, 10, 60000);
    data.film_type = FilmType::BWNegative; // Use B&W to avoid orange mask sampling

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());

    // After inversion, values should be near 65535 - 60000 = 5535
    cv::Scalar mean = cv::mean(result->rgb);
    EXPECT_LT(mean[0], 10000);
}

TEST(InverterTest, SkipsPositive) {
    Inverter stage;
    auto data = make_test_image(10, 10, 30000);
    data.film_type = FilmType::ColorPositive;

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());

    // Should be unchanged
    cv::Scalar mean = cv::mean(result->rgb);
    EXPECT_NEAR(mean[0], 30000.0, 1.0);
}

TEST(InverterTest, ColorNegativeInversionChangesValues) {
    Inverter stage;
    // Create a realistic test image: border with low orange mask, interior with higher values.
    // This allows the mask sampling to find a valid orange pedestal different from image content.
    ImageData data;
    data.rgb = cv::Mat(200, 200, CV_16UC3, cv::Scalar(50000, 50000, 50000));
    data.source_path = "test_c41.png";
    data.metadata.camera_make = "Test";

    // Fill the interior (center 136x136) with brighter content to represent negative
    cv::Mat interior = data.rgb(cv::Rect(32, 32, 136, 136));
    interior.setTo(cv::Scalar(60000, 60000, 60000));

    // Now the border (outer 32px all around) is ~50000 and interior is ~60000
    // The mask sampling will average the borders: ~50000
    // After subtraction and inversion, values should vary and not all be 65535

    data.film_type = FilmType::ColorNegative;

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());

    // After mask removal (subtract ~50000 from all pixels):
    // - Border pixels: 50000 - 50000 = 0
    // - Interior pixels: 60000 - 50000 = 10000
    // After bitwise_not:
    // - Border pixels: 65535 - 0 = 65535 (white)
    // - Interior pixels: 65535 - 10000 = 55535 (medium gray)
    // Overall mean should be around 60000 (weighted average)
    cv::Scalar mean = cv::mean(result->rgb);
    EXPECT_LT(mean[0], 63000.0); // Should not be all white (65535)
    EXPECT_GT(mean[0], 55000.0); // Should not be all black/dark
}

// ──────────────────────────────────────────────
// ColorCorrector tests
// ──────────────────────────────────────────────

TEST(ColorCorrectorTest, AWBPreservesNeutralGrey) {
    ColorCorrector stage;
    // A perfectly neutral grey should be unchanged by AWB
    auto data = make_test_image(100, 100, 32768);
    data.film_type = FilmType::ColorPositive;

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());

    // All channels should remain equal (neutral)
    const std::vector<cv::Mat> channels = [&] {
        std::vector<cv::Mat> ch(3);
        cv::split(result->rgb, ch);
        return ch;
    }();
    const double b_mean = cv::mean(channels[0])[0];
    const double g_mean = cv::mean(channels[1])[0];
    const double r_mean = cv::mean(channels[2])[0];

    EXPECT_NEAR(b_mean, g_mean, 500.0);
    EXPECT_NEAR(g_mean, r_mean, 500.0);
}

TEST(ColorCorrectorTest, SkipsGreyscaleFilm) {
    ColorCorrector stage;
    auto data = make_test_image(100, 100, 32768);
    data.film_type = FilmType::BWNegative;

    // Must succeed without error
    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());
}

// ──────────────────────────────────────────────
// CropProcessor tests
// ──────────────────────────────────────────────

TEST(CropProcessorTest, LevelsAdjustmentRunsWithoutError) {
    CropProcessor stage;
    auto data = make_gradient_image(256, 256);

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());
    EXPECT_FALSE(result->rgb.empty());
}

TEST(CropProcessorTest, SharpeningDoesNotClip) {
    CropProcessor stage;
    // Mid-grey: sharpening should not saturate to 0 or 65535
    auto data = make_test_image(100, 100, 32768);

    auto result = stage.process(std::move(data));
    ASSERT_TRUE(result.has_value());

    cv::Scalar mean = cv::mean(result->rgb);
    EXPECT_GT(mean[0], 100.0);
    EXPECT_LT(mean[0], 65000.0);
}

TEST(CropProcessorTest, RejectsEmptyImage) {
    CropProcessor stage;
    ImageData data; // empty rgb

    auto result = stage.process(std::move(data));
    ASSERT_FALSE(result.has_value());
    EXPECT_EQ(result.error().code, ErrorCode::CropFailed);
}

// ──────────────────────────────────────────────
// AppConfig tests
// ──────────────────────────────────────────────

TEST(AppConfigTest, LoadsValidIniFile) {
    // Write a minimal config to a temp file
    const auto temp = std::filesystem::temp_directory_path() / "test_config.ini";
    {
        std::ofstream f{temp};
        f << "[batch]\n"
          << "input_dir   = /tmp/in\n"
          << "output_dir  = /tmp/out\n"
          << "recursive   = true\n"
          << "file_extensions = arw,cr2\n"
          << "\n"
          << "[conversion]\n"
          << "film_type       = c41\n"
          << "output_format   = png8\n"
          << "output_bit_depth = 8\n"
          << "auto_crop       = false\n"
          << "sharpen         = false\n"
          << "invert          = true\n"
          << "\n"
          << "[quality]\n"
          << "jpeg_quality     = 80\n"
          << "sharpen_strength = 0.3\n";
    }

    auto result = AppConfig::load(temp);
    ASSERT_TRUE(result.has_value()) << result.error().message;

    const AppConfig& cfg = result.value();
    EXPECT_EQ(cfg.batch.input_dir,  "/tmp/in");
    EXPECT_EQ(cfg.batch.output_dir, "/tmp/out");
    EXPECT_TRUE(cfg.batch.recursive);
    EXPECT_EQ(cfg.batch.file_extensions, "arw,cr2");

    EXPECT_EQ(cfg.conversion.film_type,       "c41");
    EXPECT_EQ(cfg.conversion.output_format,   "png8");
    EXPECT_EQ(cfg.conversion.output_bit_depth, 8);
    EXPECT_FALSE(cfg.conversion.auto_crop);
    EXPECT_FALSE(cfg.conversion.sharpen);
    EXPECT_TRUE(cfg.conversion.invert);

    EXPECT_EQ(cfg.quality.jpeg_quality, 80);
    EXPECT_NEAR(cfg.quality.sharpen_strength, 0.3, 0.001);

    std::filesystem::remove(temp);
}

TEST(AppConfigTest, RejectsMissingFile) {
    auto result = AppConfig::load("/nonexistent/config.ini");
    ASSERT_FALSE(result.has_value());
    EXPECT_EQ(result.error().code, ErrorCode::FileNotFound);
}

TEST(AppConfigTest, ParsedExtensionsHaveDots) {
    AppConfig cfg;
    cfg.batch.file_extensions = "arw, CR2, NEF";
    const auto exts = cfg.parsed_extensions();

    ASSERT_EQ(exts.size(), 3u);
    EXPECT_EQ(exts[0], ".arw");
    EXPECT_EQ(exts[1], ".cr2");
    EXPECT_EQ(exts[2], ".nef");
}

TEST(AppConfigTest, OutputFormatMapping) {
    AppConfig cfg;
    cfg.conversion.output_format = "png8";
    EXPECT_EQ(cfg.output_format(), OutputFormat::PNG_8bit);

    cfg.conversion.output_format = "tiff16";
    EXPECT_EQ(cfg.output_format(), OutputFormat::TIFF_16bit);

    cfg.conversion.output_format = "jpg";
    EXPECT_EQ(cfg.output_format(), OutputFormat::JPEG);

    cfg.conversion.output_format = "png16";
    EXPECT_EQ(cfg.output_format(), OutputFormat::PNG_16bit);

    cfg.conversion.output_format = "unknown";
    EXPECT_EQ(cfg.output_format(), OutputFormat::PNG_16bit); // fallback
}

TEST(AppConfigTest, WriteDefaultCreatesFile) {
    const auto temp = std::filesystem::temp_directory_path() / "default_config.ini";
    std::filesystem::remove(temp); // Ensure it does not exist

    auto result = AppConfig::write_default(temp);
    ASSERT_TRUE(result.has_value()) << result.error().message;
    EXPECT_TRUE(std::filesystem::exists(temp));
    EXPECT_GT(std::filesystem::file_size(temp), 0u);

    // Verify the written file can be loaded back.
    auto reload = AppConfig::load(temp);
    ASSERT_TRUE(reload.has_value()) << reload.error().message;

    std::filesystem::remove(temp);
}

// ──────────────────────────────────────────────
// Error type tests
// ──────────────────────────────────────────────

TEST(ErrorTest, FormatIncludesAllInfo) {
    auto err = make_error(ErrorCode::FileNotFound, "test.arw not found");
    auto formatted = err.format();

    EXPECT_NE(formatted.find("test.arw not found"), std::string::npos);
    EXPECT_NE(formatted.find("test_pipeline.cpp"), std::string::npos);
}