Use clang++ instead of g++

makefile

@@ -50,7 +50,7 @@ $(SITE_PACKAGES)/cv%:
 src/reconstruction/fit.so: src/reconstruction/fit-model.cpp
 	$(BASE_DOCKER_CMD) /bin/bash -c \
 		'(cd reconstruction; \
-			g++ -fPIC -O3 -shared -std=c++11 \
+			clang++ -fPIC -O3 -shared -std=c++14 \
 				-I/usr/local/include/pybind11/include/ \
 				-I/usr/local/eos/include/ \
 				-I/usr/local/eos/3rdparty/glm/ \
@@ -61,7 +61,7 @@ src/reconstruction/fit.so: src/reconstruction/fit-model.cpp
 				-L/usr/lib/x86_64-linux-gnu/ \
 				-L/usr/local/lib/ \
 				-lboost_program_options \
-				-lfile_system \
+				-lboost_filesystem \
 				-lopencv_world \
 				`python-config --cflags --ldflags` \
 			$(notdir $^) -o $(notdir $@) \

src/reconstruction/fit-model.cpp

@@ -45,8 +45,10 @@ int add(int i, int j) {
 #include <fstream>
 
 using namespace eos;
+
 namespace po = boost::program_options;
 namespace fs = boost::filesystem;
+
 using eos::core::Landmark;
 using eos::core::LandmarkCollection;
 using cv::Mat;
@@ -68,82 +70,82 @@ using std::string;
  * is estimated, and then, using this camera matrix, the shape is fitted
  * to the landmarks.
  */
-int fit(int argc, char *argv[])
-{
-    // Load the image, landmarks, LandmarkMapper and the Morphable Model:
-    Mat image = cv::imread(imagefile.string());
-    LandmarkCollection<cv::Vec2f> landmarks;
-    try {
-        landmarks = read_pts_landmarks(landmarksfile.string());
-    }
-    catch (const std::runtime_error& e) {
-        cout << "Error reading the landmarks: " << e.what() << endl;
-        return EXIT_FAILURE;
-    }
-    morphablemodel::MorphableModel morphable_model;
-    try {
-        morphable_model = morphablemodel::load_model(modelfile.string());
-    }
-    catch (const std::runtime_error& e) {
-        cout << "Error loading the Morphable Model: " << e.what() << endl;
-        return EXIT_FAILURE;
-    }
-    core::LandmarkMapper landmark_mapper = mappingsfile.empty() ? core::LandmarkMapper() : core::LandmarkMapper(mappingsfile);
-
-    // Draw the loaded landmarks:
-    Mat outimg = image.clone();
-    for (auto&& lm : landmarks) {
-        cv::rectangle(outimg, cv::Point2f(lm.coordinates[0] - 2.0f, lm.coordinates[1] - 2.0f), cv::Point2f(lm.coordinates[0] + 2.0f, lm.coordinates[1] + 2.0f), { 255, 0, 0 });
-    }
-
-    // These will be the final 2D and 3D points used for the fitting:
-    vector<Vec4f> model_points; // the points in the 3D shape model
-    vector<int> vertex_indices; // their vertex indices
-    vector<Vec2f> image_points; // the corresponding 2D landmark points
-
-    // Sub-select all the landmarks which we have a mapping for (i.e. that are defined in the 3DMM):
-    for (int i = 0; i < landmarks.size(); ++i) {
-        auto converted_name = landmark_mapper.convert(landmarks[i].name);
-        if (!converted_name) { // no mapping defined for the current landmark
-            continue;
-        }
-        int vertex_idx = std::stoi(converted_name.get());
-        Vec4f vertex = morphable_model.get_shape_model().get_mean_at_point(vertex_idx);
-        model_points.emplace_back(vertex);
-        vertex_indices.emplace_back(vertex_idx);
-        image_points.emplace_back(landmarks[i].coordinates);
-    }
-
-    // Estimate the camera (pose) from the 2D - 3D point correspondences
-    fitting::ScaledOrthoProjectionParameters pose = fitting::estimate_orthographic_projection_linear(image_points, model_points, true, image.rows);
-    fitting::RenderingParameters rendering_params(pose, image.cols, image.rows);
-
-    // The 3D head pose can be recovered as follows:
-    float yaw_angle = glm::degrees(glm::yaw(rendering_params.get_rotation()));
-    // and similarly for pitch and roll.
-
-    // Estimate the shape coefficients by fitting the shape to the landmarks:
-    Mat affine_from_ortho = fitting::get_3x4_affine_camera_matrix(rendering_params, image.cols, image.rows);
-    vector<float> fitted_coeffs = fitting::fit_shape_to_landmarks_linear(morphable_model, affine_from_ortho, image_points, vertex_indices);
-
-    // Obtain the full mesh with the estimated coefficients:
-    render::Mesh mesh = morphable_model.draw_sample(fitted_coeffs, vector<float>());
-
-    // Extract the texture from the image using given mesh and camera parameters:
-    Mat isomap = render::extract_texture(mesh, affine_from_ortho, image);
-
-    // Save the mesh as textured obj:
-    outputfile += fs::path(".obj");
-    render::write_textured_obj(mesh, outputfile.string());
-
-    // And save the isomap:
-    outputfile.replace_extension(".isomap.png");
-    cv::imwrite(outputfile.string(), isomap);
-
-    cout << "Finished fitting and wrote result mesh and isomap to files with basename " << outputfile.stem().stem() << "." << endl;
-
-    return EXIT_SUCCESS;
-}
+//int fit(int argc, char *argv[])
+//{
+//    // Load the image, landmarks, LandmarkMapper and the Morphable Model:
+//    Mat image = cv::imread(imagefile.string());
+//    LandmarkCollection<cv::Vec2f> landmarks;
+//    try {
+//        landmarks = read_pts_landmarks(landmarksfile.string());
+//    }
+//    catch (const std::runtime_error& e) {
+//        cout << "Error reading the landmarks: " << e.what() << endl;
+//        return EXIT_FAILURE;
+//    }
+//    morphablemodel::MorphableModel morphable_model;
+//    try {
+//        morphable_model = morphablemodel::load_model(modelfile.string());
+//    }
+//    catch (const std::runtime_error& e) {
+//        cout << "Error loading the Morphable Model: " << e.what() << endl;
+//        return EXIT_FAILURE;
+//    }
+//    core::LandmarkMapper landmark_mapper = mappingsfile.empty() ? core::LandmarkMapper() : core::LandmarkMapper(mappingsfile);
+//
+//    // Draw the loaded landmarks:
+//    Mat outimg = image.clone();
+//    for (auto&& lm : landmarks) {
+//        cv::rectangle(outimg, cv::Point2f(lm.coordinates[0] - 2.0f, lm.coordinates[1] - 2.0f), cv::Point2f(lm.coordinates[0] + 2.0f, lm.coordinates[1] + 2.0f), { 255, 0, 0 });
+//    }
+//
+//    // These will be the final 2D and 3D points used for the fitting:
+//    vector<Vec4f> model_points; // the points in the 3D shape model
+//    vector<int> vertex_indices; // their vertex indices
+//    vector<Vec2f> image_points; // the corresponding 2D landmark points
+//
+//    // Sub-select all the landmarks which we have a mapping for (i.e. that are defined in the 3DMM):
+//    for (int i = 0; i < landmarks.size(); ++i) {
+//        auto converted_name = landmark_mapper.convert(landmarks[i].name);
+//        if (!converted_name) { // no mapping defined for the current landmark
+//            continue;
+//        }
+//        int vertex_idx = std::stoi(converted_name.get());
+//        Vec4f vertex = morphable_model.get_shape_model().get_mean_at_point(vertex_idx);
+//        model_points.emplace_back(vertex);
+//        vertex_indices.emplace_back(vertex_idx);
+//        image_points.emplace_back(landmarks[i].coordinates);
+//    }
+//
+//    // Estimate the camera (pose) from the 2D - 3D point correspondences
+//    fitting::ScaledOrthoProjectionParameters pose = fitting::estimate_orthographic_projection_linear(image_points, model_points, true, image.rows);
+//    fitting::RenderingParameters rendering_params(pose, image.cols, image.rows);
+//
+//    // The 3D head pose can be recovered as follows:
+//    float yaw_angle = glm::degrees(glm::yaw(rendering_params.get_rotation()));
+//    // and similarly for pitch and roll.
+//
+//    // Estimate the shape coefficients by fitting the shape to the landmarks:
+//    Mat affine_from_ortho = fitting::get_3x4_affine_camera_matrix(rendering_params, image.cols, image.rows);
+//    vector<float> fitted_coeffs = fitting::fit_shape_to_landmarks_linear(morphable_model, affine_from_ortho, image_points, vertex_indices);
+//
+//    // Obtain the full mesh with the estimated coefficients:
+//    render::Mesh mesh = morphable_model.draw_sample(fitted_coeffs, vector<float>());
+//
+//    // Extract the texture from the image using given mesh and camera parameters:
+//    Mat isomap = render::extract_texture(mesh, affine_from_ortho, image);
+//
+//    // Save the mesh as textured obj:
+//    outputfile += fs::path(".obj");
+//    render::write_textured_obj(mesh, outputfile.string());
+//
+//    // And save the isomap:
+//    outputfile.replace_extension(".isomap.png");
+//    cv::imwrite(outputfile.string(), isomap);
+//
+//    cout << "Finished fitting and wrote result mesh and isomap to files with basename " << outputfile.stem().stem() << "." << endl;
+//
+//    return EXIT_SUCCESS;
+//}
 
 PYBIND11_PLUGIN(fit) {
     py::module m("fit", "fit example");