CliRunner: - --batch / --config <file> flags trigger batch mode with directory scanning - collect_files() with recursive support and case-insensitive extension matching - build_pipeline() respects AppConfig conversion flags (invert toggle) - Progress output to stderr: "[1/42] Processing DSC09246.ARW..." Tests (test_pipeline.cpp): - AppConfig: load/save roundtrip, missing file error, extension parsing, format mapping, write_default - CropProcessor: levels adjustment, sharpening no-clip, empty image error - ColorCorrector: AWB preserves neutral grey, skips B&W film - Inverter: color negative changes values, B&W inversion, positive passthrough - Preprocessor: 8-bit→16-bit conversion test_rawloader.cpp: added missing <fstream> include Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
404 lines
14 KiB
C++
404 lines
14 KiB
C++
#include <gtest/gtest.h>
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#include "converter/pipeline/Pipeline.h"
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#include "converter/pipeline/ImageData.h"
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#include "converter/pipeline/Error.h"
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#include "converter/preprocess/Preprocessor.h"
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#include "converter/negative/NegativeDetector.h"
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#include "converter/invert/Inverter.h"
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#include "converter/color/ColorCorrector.h"
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#include "converter/crop/CropProcessor.h"
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#include "config/AppConfig.h"
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#include <opencv2/core.hpp>
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#include <filesystem>
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#include <fstream>
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using namespace photoconv;
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/**
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* @brief Create a synthetic 16-bit test image.
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*
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* @param width Image width.
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* @param height Image height.
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* @param value Fill value for all channels (0-65535).
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* @return CV_16UC3 Mat filled with the given value.
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*/
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static ImageData make_test_image(int width, int height, uint16_t value) {
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ImageData data;
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data.rgb = cv::Mat(height, width, CV_16UC3, cv::Scalar(value, value, value));
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data.source_path = "test_synthetic.png";
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data.metadata.camera_make = "Test";
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data.metadata.camera_model = "Synthetic";
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return data;
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}
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/**
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* @brief Create a synthetic gradient test image.
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*
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* Useful for levels-adjustment and crop tests that need non-uniform content.
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*/
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static ImageData make_gradient_image(int width, int height) {
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ImageData data;
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data.rgb = cv::Mat(height, width, CV_16UC3);
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data.source_path = "test_gradient.png";
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data.metadata.camera_make = "Test";
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for (int y = 0; y < height; ++y) {
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for (int x = 0; x < width; ++x) {
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const uint16_t v = static_cast<uint16_t>(
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static_cast<double>(x + y) / static_cast<double>(width + height) * 65535.0);
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data.rgb.at<cv::Vec3w>(y, x) = {v, v, v};
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}
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}
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return data;
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}
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// ──────────────────────────────────────────────
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// Pipeline orchestration tests
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// ──────────────────────────────────────────────
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TEST(PipelineTest, EmptyPipelinePassesThrough) {
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Pipeline pipeline;
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auto data = make_test_image(100, 100, 32768);
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auto result = pipeline.execute(std::move(data));
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ASSERT_TRUE(result.has_value());
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EXPECT_EQ(result->rgb.cols, 100);
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EXPECT_EQ(result->rgb.rows, 100);
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}
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TEST(PipelineTest, StageCountIsCorrect) {
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Pipeline pipeline;
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EXPECT_EQ(pipeline.stage_count(), 0);
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pipeline.add_stage(std::make_unique<Preprocessor>());
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EXPECT_EQ(pipeline.stage_count(), 1);
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pipeline.add_stage(std::make_unique<NegativeDetector>());
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EXPECT_EQ(pipeline.stage_count(), 2);
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}
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TEST(PipelineTest, FullPipelineRunsWithoutError) {
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Pipeline pipeline;
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pipeline.add_stage(std::make_unique<Preprocessor>());
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pipeline.add_stage(std::make_unique<NegativeDetector>());
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pipeline.add_stage(std::make_unique<Inverter>());
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pipeline.add_stage(std::make_unique<ColorCorrector>());
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pipeline.add_stage(std::make_unique<CropProcessor>());
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auto data = make_test_image(200, 200, 40000);
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auto result = pipeline.execute(std::move(data));
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ASSERT_TRUE(result.has_value());
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}
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TEST(PipelineTest, ProgressCallbackIsCalled) {
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Pipeline pipeline;
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pipeline.add_stage(std::make_unique<Preprocessor>());
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pipeline.add_stage(std::make_unique<NegativeDetector>());
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int callback_count = 0;
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auto data = make_test_image(100, 100, 32768);
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auto result = pipeline.execute(std::move(data),
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[&callback_count](const std::string&, float) {
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++callback_count;
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});
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ASSERT_TRUE(result.has_value());
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// 2 stage callbacks + 1 "done" callback = 3
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EXPECT_EQ(callback_count, 3);
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}
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// ──────────────────────────────────────────────
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// Preprocessor tests
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// ──────────────────────────────────────────────
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TEST(PreprocessorTest, AcceptsValidImage) {
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Preprocessor stage;
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auto data = make_test_image(100, 100, 32768);
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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EXPECT_EQ(result->rgb.type(), CV_16UC3);
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}
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TEST(PreprocessorTest, RejectsEmptyImage) {
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Preprocessor stage;
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ImageData data;
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auto result = stage.process(std::move(data));
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ASSERT_FALSE(result.has_value());
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EXPECT_EQ(result.error().code, ErrorCode::InvalidBitDepth);
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}
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TEST(PreprocessorTest, Converts8BitTo16Bit) {
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Preprocessor stage;
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ImageData data;
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data.rgb = cv::Mat(100, 100, CV_8UC3, cv::Scalar(128, 128, 128));
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data.source_path = "test.png";
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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EXPECT_EQ(result->rgb.type(), CV_16UC3);
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// 128 * 257 = 32896 ≈ 32768 midpoint
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cv::Scalar mean = cv::mean(result->rgb);
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EXPECT_GT(mean[0], 30000.0);
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EXPECT_LT(mean[0], 36000.0);
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}
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// ──────────────────────────────────────────────
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// NegativeDetector tests
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// ──────────────────────────────────────────────
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TEST(NegativeDetectorTest, DetectsBrightImageAsNegative) {
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NegativeDetector stage;
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// High values = likely negative (inverted)
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auto data = make_test_image(100, 100, 50000);
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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EXPECT_NE(result->film_type, FilmType::Unknown);
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}
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TEST(NegativeDetectorTest, DetectsDarkImageAsPositive) {
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NegativeDetector stage;
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// Low values = likely positive
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auto data = make_test_image(100, 100, 10000);
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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// Should be classified as positive (below midpoint)
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EXPECT_TRUE(result->film_type == FilmType::ColorPositive ||
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result->film_type == FilmType::BWPositive);
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}
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// ──────────────────────────────────────────────
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// Inverter tests
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// ──────────────────────────────────────────────
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TEST(InverterTest, InvertsNegative) {
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Inverter stage;
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auto data = make_test_image(10, 10, 60000);
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data.film_type = FilmType::BWNegative; // Use B&W to avoid orange mask sampling
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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// After inversion, values should be near 65535 - 60000 = 5535
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cv::Scalar mean = cv::mean(result->rgb);
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EXPECT_LT(mean[0], 10000);
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}
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TEST(InverterTest, SkipsPositive) {
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Inverter stage;
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auto data = make_test_image(10, 10, 30000);
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data.film_type = FilmType::ColorPositive;
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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// Should be unchanged
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cv::Scalar mean = cv::mean(result->rgb);
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EXPECT_NEAR(mean[0], 30000.0, 1.0);
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}
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TEST(InverterTest, ColorNegativeInversionChangesValues) {
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Inverter stage;
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// Create an image large enough for border sampling
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auto data = make_test_image(200, 200, 55000);
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data.film_type = FilmType::ColorNegative;
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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// After orange mask removal and inversion, values should have changed
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cv::Scalar mean = cv::mean(result->rgb);
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EXPECT_LT(mean[0], 65000.0); // Not all white
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}
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// ──────────────────────────────────────────────
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// ColorCorrector tests
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// ──────────────────────────────────────────────
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TEST(ColorCorrectorTest, AWBPreservesNeutralGrey) {
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ColorCorrector stage;
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// A perfectly neutral grey should be unchanged by AWB
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auto data = make_test_image(100, 100, 32768);
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data.film_type = FilmType::ColorPositive;
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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// All channels should remain equal (neutral)
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const std::vector<cv::Mat> channels = [&] {
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std::vector<cv::Mat> ch(3);
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cv::split(result->rgb, ch);
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return ch;
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}();
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const double b_mean = cv::mean(channels[0])[0];
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const double g_mean = cv::mean(channels[1])[0];
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const double r_mean = cv::mean(channels[2])[0];
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EXPECT_NEAR(b_mean, g_mean, 500.0);
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EXPECT_NEAR(g_mean, r_mean, 500.0);
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}
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TEST(ColorCorrectorTest, SkipsGreyscaleFilm) {
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ColorCorrector stage;
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auto data = make_test_image(100, 100, 32768);
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data.film_type = FilmType::BWNegative;
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// Must succeed without error
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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}
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// ──────────────────────────────────────────────
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// CropProcessor tests
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// ──────────────────────────────────────────────
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TEST(CropProcessorTest, LevelsAdjustmentRunsWithoutError) {
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CropProcessor stage;
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auto data = make_gradient_image(256, 256);
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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EXPECT_FALSE(result->rgb.empty());
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}
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TEST(CropProcessorTest, SharpeningDoesNotClip) {
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CropProcessor stage;
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// Mid-grey: sharpening should not saturate to 0 or 65535
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auto data = make_test_image(100, 100, 32768);
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auto result = stage.process(std::move(data));
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ASSERT_TRUE(result.has_value());
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cv::Scalar mean = cv::mean(result->rgb);
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EXPECT_GT(mean[0], 100.0);
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EXPECT_LT(mean[0], 65000.0);
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}
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TEST(CropProcessorTest, RejectsEmptyImage) {
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CropProcessor stage;
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ImageData data; // empty rgb
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auto result = stage.process(std::move(data));
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ASSERT_FALSE(result.has_value());
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EXPECT_EQ(result.error().code, ErrorCode::CropFailed);
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}
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// ──────────────────────────────────────────────
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// AppConfig tests
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// ──────────────────────────────────────────────
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TEST(AppConfigTest, LoadsValidIniFile) {
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// Write a minimal config to a temp file
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const auto temp = std::filesystem::temp_directory_path() / "test_config.ini";
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{
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std::ofstream f{temp};
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f << "[batch]\n"
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<< "input_dir = /tmp/in\n"
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<< "output_dir = /tmp/out\n"
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<< "recursive = true\n"
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<< "file_extensions = arw,cr2\n"
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<< "\n"
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<< "[conversion]\n"
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<< "film_type = c41\n"
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<< "output_format = png8\n"
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<< "output_bit_depth = 8\n"
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<< "auto_crop = false\n"
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<< "sharpen = false\n"
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<< "invert = true\n"
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<< "\n"
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<< "[quality]\n"
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<< "jpeg_quality = 80\n"
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<< "sharpen_strength = 0.3\n";
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}
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auto result = AppConfig::load(temp);
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ASSERT_TRUE(result.has_value()) << result.error().message;
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const AppConfig& cfg = result.value();
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EXPECT_EQ(cfg.batch.input_dir, "/tmp/in");
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EXPECT_EQ(cfg.batch.output_dir, "/tmp/out");
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EXPECT_TRUE(cfg.batch.recursive);
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EXPECT_EQ(cfg.batch.file_extensions, "arw,cr2");
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EXPECT_EQ(cfg.conversion.film_type, "c41");
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EXPECT_EQ(cfg.conversion.output_format, "png8");
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EXPECT_EQ(cfg.conversion.output_bit_depth, 8);
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EXPECT_FALSE(cfg.conversion.auto_crop);
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EXPECT_FALSE(cfg.conversion.sharpen);
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EXPECT_TRUE(cfg.conversion.invert);
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EXPECT_EQ(cfg.quality.jpeg_quality, 80);
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EXPECT_NEAR(cfg.quality.sharpen_strength, 0.3, 0.001);
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std::filesystem::remove(temp);
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}
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TEST(AppConfigTest, RejectsMissingFile) {
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auto result = AppConfig::load("/nonexistent/config.ini");
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ASSERT_FALSE(result.has_value());
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EXPECT_EQ(result.error().code, ErrorCode::FileNotFound);
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}
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TEST(AppConfigTest, ParsedExtensionsHaveDots) {
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AppConfig cfg;
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cfg.batch.file_extensions = "arw, CR2, NEF";
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const auto exts = cfg.parsed_extensions();
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ASSERT_EQ(exts.size(), 3u);
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EXPECT_EQ(exts[0], ".arw");
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EXPECT_EQ(exts[1], ".cr2");
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EXPECT_EQ(exts[2], ".nef");
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}
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TEST(AppConfigTest, OutputFormatMapping) {
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AppConfig cfg;
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cfg.conversion.output_format = "png8";
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EXPECT_EQ(cfg.output_format(), OutputFormat::PNG_8bit);
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cfg.conversion.output_format = "tiff16";
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EXPECT_EQ(cfg.output_format(), OutputFormat::TIFF_16bit);
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cfg.conversion.output_format = "jpg";
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EXPECT_EQ(cfg.output_format(), OutputFormat::JPEG);
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cfg.conversion.output_format = "png16";
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EXPECT_EQ(cfg.output_format(), OutputFormat::PNG_16bit);
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cfg.conversion.output_format = "unknown";
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EXPECT_EQ(cfg.output_format(), OutputFormat::PNG_16bit); // fallback
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}
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TEST(AppConfigTest, WriteDefaultCreatesFile) {
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const auto temp = std::filesystem::temp_directory_path() / "default_config.ini";
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std::filesystem::remove(temp); // Ensure it does not exist
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auto result = AppConfig::write_default(temp);
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ASSERT_TRUE(result.has_value()) << result.error().message;
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EXPECT_TRUE(std::filesystem::exists(temp));
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EXPECT_GT(std::filesystem::file_size(temp), 0u);
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// Verify the written file can be loaded back.
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auto reload = AppConfig::load(temp);
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ASSERT_TRUE(reload.has_value()) << reload.error().message;
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std::filesystem::remove(temp);
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}
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// ──────────────────────────────────────────────
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// Error type tests
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// ──────────────────────────────────────────────
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TEST(ErrorTest, FormatIncludesAllInfo) {
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auto err = make_error(ErrorCode::FileNotFound, "test.arw not found");
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auto formatted = err.format();
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EXPECT_NE(formatted.find("test.arw not found"), std::string::npos);
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EXPECT_NE(formatted.find("test_pipeline.cpp"), std::string::npos);
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}
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