Add a way of rendering the output on the last frame, duplicated fitting...

Add a way of rendering the output on the last frame, duplicated fitting function to improve and easy merge later

CMakeLists.txt

@@ -23,7 +23,7 @@ option(EOS_BUILD_EXAMPLES "Build the example applications." ON)
 message(STATUS "EOS_BUILD_EXAMPLES: ${EOS_BUILD_EXAMPLES}")
 option(EOS_BUILD_CERES_EXAMPLE "Build the fit-model-ceres example (requires Ceres)." OFF)
 message(STATUS "EOS_BUILD_CERES_EXAMPLE: ${EOS_BUILD_CERES_EXAMPLE}")
-option(EOS_BUILD_UTILS "Build utility applications." OFF)
+option(EOS_BUILD_UTILS "Build utility applications." ON)
 message(STATUS "EOS_BUILD_UTILS: ${EOS_BUILD_UTILS}")
 option(EOS_BUILD_DOCUMENTATION "Build the library documentation." OFF)
 message(STATUS "EOS_BUILD_DOCUMENTATION: ${EOS_BUILD_DOCUMENTATION}")
@@ -97,6 +97,7 @@ set(HEADERS
   ${CMAKE_CURRENT_SOURCE_DIR}/include/eos/fitting/fitting.hpp
   ${CMAKE_CURRENT_SOURCE_DIR}/include/eos/fitting/ceres_nonlinear.hpp
   ${CMAKE_CURRENT_SOURCE_DIR}/include/eos/fitting/RenderingParameters.hpp
+  ${CMAKE_CURRENT_SOURCE_DIR}/include/eos/fitting/ReconstructionData.hpp
   ${CMAKE_CURRENT_SOURCE_DIR}/include/eos/render/utils.hpp
   ${CMAKE_CURRENT_SOURCE_DIR}/include/eos/render/render.hpp
   ${CMAKE_CURRENT_SOURCE_DIR}/include/eos/render/render_affine.hpp
@@ -155,9 +156,7 @@ if(EOS_BUILD_EXAMPLES)
   add_subdirectory(examples)
 endif()
 
-if(EOS_BUILD_UTILS)
-  add_subdirectory(utils)
-endif()
+add_subdirectory(utils)
 
 if(EOS_BUILD_DOCUMENTATION)
   add_subdirectory(doc)

include/eos/core/landmark_utils.hpp

@@ -153,9 +153,10 @@ namespace eos {
 		*/
 		template<typename vec2f>
 		std::pair <std::vector<core::LandmarkCollection<vec2f>>, std::vector<std::string>>
-		load_annotations(
-				std::vector<std::string>annotations,
-				core::LandmarkMapper mapper, morphablemodel::MorphableModel morphable_model, bool read_from_file = false) {
+		load_annotations(std::vector<std::string>annotations,
+						 core::LandmarkMapper mapper,
+						 morphablemodel::MorphableModel morphable_model,
+						 bool read_from_file = false) {
 			std::vector<core::LandmarkCollection<vec2f>> landmark_collection_list;
 
 			// load file names from one file.
@@ -187,6 +188,106 @@ namespace eos {
 
 			return std::make_pair(landmark_collection_list, annotations);
 		}
+
+		/**
+		 *
+		 * @tparam vec2f
+		 * @tparam vec4f
+		 * @param landmarks
+		 * @param landmark_mapper
+		 * @param mesh
+		 * @param model_points
+		 * @param vertex_indices
+		 * @param image_points
+		 */
+		template <typename vec2f, typename vec4f>
+		inline void subselect_landmarks(core::LandmarkCollection<vec2f> landmarks,
+										const core::LandmarkMapper& landmark_mapper,
+										eos::core::Mesh& mesh,
+										vector<vector<vec4f>>& model_points,
+										vector<vector<int>>& vertex_indices,
+										vector<vector<vec2f>>& image_points) {
+			vector<Vec4f> current_model_points;
+			vector<int> current_vertex_indices;
+			vector<Vec2f> current_image_points;
+
+			for (auto &lm: landmarks) {
+				auto converted_name = landmark_mapper.convert(lm.name);
+				if (!converted_name) { // no mapping defined for the current landmark
+					continue;
+				}
+
+				int vertex_idx = std::stoi(converted_name.get());
+				Vec4f vertex(
+					mesh.vertices[vertex_idx].x,
+					mesh.vertices[vertex_idx].y,
+					mesh.vertices[vertex_idx].z,
+					mesh.vertices[vertex_idx].w
+				);
+
+				current_model_points.emplace_back(vertex);
+				current_vertex_indices.emplace_back(vertex_idx);
+				current_image_points.emplace_back(lm.coordinates);
+			}
+
+			model_points.push_back(current_model_points);
+			vertex_indices.push_back(current_vertex_indices);
+			image_points.push_back(current_image_points);
+		}
+
+		/**
+		 * As the name suggests, in the multi-frame fitting we can subselect landmarks according to the
+		 * landmark mapper.
+		 *
+		 * @tparam vec2f
+		 * @param[in] landmarks
+		 * @param[in] landmark_mapper
+		 * @param[in] meshs
+		 * @param[out] model_points
+		 * @param[out] vertex_indices
+		 * @param[out] image_points
+		 */
+		template <typename vec2f, typename vec4f>
+		inline void subselect_landmarks_multi(const std::vector<core::LandmarkCollection<vec2f>>& landmarks,
+											  const core::LandmarkMapper& landmark_mapper,
+											  vector<eos::core::Mesh> meshs,
+											  vector<vector<vec4f>>& model_points,
+											  vector<vector<int>>& vertex_indices,
+											  vector<vector<vec2f>>& image_points) {
+
+			vector<Vec4f> current_model_points;
+			vector<int> current_vertex_indices;
+			vector<Vec2f> current_image_points;
+
+			// Sub-select all the landmarks which we have a mapping for (i.e. that are defined in the 3DMM),
+			// and get the corresponding model points (mean if given no initial coeffs, from the computed shape otherwise):
+			for (int i = 0; i < landmarks.size(); i++) {
+				auto landmark_list = landmarks[i];
+				auto mesh = meshs[i];
+
+				for (auto &lm: landmark_list) {
+					auto converted_name = landmark_mapper.convert(lm.name);
+					if (!converted_name) { // no mapping defined for the current landmark
+						continue;
+					}
+					int vertex_idx = std::stoi(converted_name.get());
+					Vec4f vertex(
+						mesh.vertices[vertex_idx].x,
+						mesh.vertices[vertex_idx].y,
+						mesh.vertices[vertex_idx].z,
+						mesh.vertices[vertex_idx].w
+					);
+
+					current_model_points.emplace_back(vertex);
+					current_vertex_indices.emplace_back(vertex_idx);
+					current_image_points.emplace_back(lm.coordinates);
+				}
+
+				model_points.push_back(current_model_points);
+				vertex_indices.push_back(current_vertex_indices);
+				image_points.push_back(current_image_points);
+			}
+		}
 	}
 }
 

include/eos/fitting/ReconstructionData.hpp

+//
+// Created by RA Torenvliet on 12/04/2017.
+//
+
+#ifndef EOS_RECONSTRUCTIONDATA_HPP
+#define EOS_RECONSTRUCTIONDATA_HPP
+
+namespace eos {
+namespace fitting {
+
+struct ReconstructionData {
+  morphablemodel::MorphableModel morphable_model;
+  std::vector <morphablemodel::Blendshape> blendshapes;
+  std::vector <core::LandmarkCollection<cv::Vec2f>> landmarks;
+  std::vector <cv::Mat> affine_camera_matrix;
+
+};
+
+}
+}
+
+
+#endif //EOS_RECONSTRUCTIONDATA_HPP

include/eos/fitting/fitting.hpp

@@ -838,26 +838,242 @@ inline std::pair<std::vector<core::Mesh>, std::vector<fitting::RenderingParamete
 	);
 };
 
-//inline std::pair<std::vector<core::Mesh>, std::vector<fitting::RenderingParameters>> fit_shape_and_pose_multi_2(
-//		const morphablemodel::MorphableModel& morphable_model,
-//		const std::vector<morphablemodel::Blendshape>& blendshapes,
-//		const std::vector<core::LandmarkCollection<cv::Vec2f>>& landmarks,
-//		const core::LandmarkMapper& landmark_mapper,
-//		int image_width,
-//		int image_height,
-//		int num_images,
-//		const morphablemodel::EdgeTopology& edge_topology,
-//		const fitting::ContourLandmarks& contour_landmarks,
-//		const fitting::ModelContour& model_contour,
-//		int num_iterations,
-//		boost::optional<int> num_shape_coefficients_to_fit,
-//		float lambda,
-//		boost::optional<fitting::RenderingParameters> initial_rendering_params,
-//		std::vector<float>& pca_shape_coefficients,
-//		std::vector<std::vector<float>>& blendshape_coefficients,
-//		std::vector<std::vector<cv::Vec2f>>& fitted_image_points) {
+//void calculate_rendering_params() {
+//  // Need to do an initial pose fit to do the contour fitting inside the loop.
+//  // We'll do an expression fit too, since face shapes vary quite a lot, depending on expressions.
+//  vector<fitting::RenderingParameters> rendering_params;
+//  for (int j = 0; j < num_images; ++j) {
+//	fitting::ScaledOrthoProjectionParameters current_pose = fitting::estimate_orthographic_projection_linear (image_points[j], model_points[j], true, image_height);
+//	fitting::RenderingParameters current_rendering_params (current_pose, image_width, image_height);
+//	rendering_params.push_back (current_rendering_params);
 //
-//}
+//	cv::Mat affine_from_ortho = fitting::get_3x4_affine_camera_matrix (current_rendering_params, image_width, image_height);
+//	blendshape_coefficients[j] = fitting::fit_blendshapes_to_landmarks_nnls (blendshapes, current_pca_shape, affine_from_ortho, image_points[j], vertex_indices[j]);
+//
+//	// Mesh with same PCA coeffs as before, but new expression fit (this is relevant if no initial blendshape coeffs have been given):
+//	current_combined_shapes[j] = current_pca_shape + morphablemodel::to_matrix (blendshapes)
+//		* Eigen::Map<const Eigen::VectorXf> (blendshape_coefficients[j]
+//												 .data (), blendshape_coefficients[j]
+//												 .size ());
+//	current_meshs[j] = morphablemodel::sample_to_mesh (current_combined_shapes[j], morphable_model
+//		.get_color_model ().get_mean (), morphable_model.get_shape_model ().get_triangle_list (), morphable_model
+//														   .get_color_model ()
+//														   .get_triangle_list (), morphable_model
+//														   .get_texture_coordinates ());
+//  }
+//}}
+
+inline std::pair<std::vector<core::Mesh>, std::vector<fitting::RenderingParameters>> fit_shape_and_pose_multi_2(
+		const morphablemodel::MorphableModel& morphable_model,
+		const std::vector<morphablemodel::Blendshape>& blendshapes,
+		const std::vector<core::LandmarkCollection<cv::Vec2f>>& landmarks,
+		const core::LandmarkMapper& landmark_mapper,
+		int image_width,
+		int image_height,
+		int num_images,
+		const morphablemodel::EdgeTopology& edge_topology,
+		const fitting::ContourLandmarks& contour_landmarks,
+		const fitting::ModelContour& model_contour,
+		int num_iterations,
+		boost::optional<int> num_shape_coefficients_to_fit, float lambda, boost::optional<fitting::RenderingParameters> initial_rendering_params,
+		std::vector<float>& pca_shape_coefficients,
+		std::vector<std::vector<float>>& blendshape_coefficients,
+		std::vector<std::vector<cv::Vec2f>>& fitted_image_points) {
+
+	assert(blendshapes.size() > 0);
+	assert(num_iterations > 0); // Can we allow 0, for only the initial pose-fit?
+	assert(pca_shape_coefficients.size() <= morphable_model.get_shape_model().get_num_principal_components());
+
+	using std::vector;
+	using cv::Vec2f;
+	using cv::Vec4f;
+	using cv::Mat;
+	using Eigen::VectorXf;
+	using Eigen::MatrixXf;
+
+	if (!num_shape_coefficients_to_fit) {
+		num_shape_coefficients_to_fit = morphable_model.get_shape_model().get_num_principal_components();
+	}
+
+	if (pca_shape_coefficients.empty()) {
+		pca_shape_coefficients.resize(num_shape_coefficients_to_fit.get());
+	}
+
+	// TODO: This leaves the following case open: num_coeffs given is empty or defined, but the
+	// pca_shape_coefficients given is != num_coeffs or the model's max-coeffs. What to do then? Handle & document!
+
+	if (blendshape_coefficients.size() < num_images) {
+		for (int j = 0; j < num_images; ++j) {
+			std::vector<float> current_blendshape_coefficients;
+			current_blendshape_coefficients.resize(blendshapes.size());
+			blendshape_coefficients.push_back(current_blendshape_coefficients);
+		}
+	}
+
+	MatrixXf blendshapes_as_basis = morphablemodel::to_matrix(blendshapes);
+
+	// Current mesh - either from the given coefficients, or the mean:
+	VectorXf current_pca_shape = morphable_model.get_shape_model().draw_sample(pca_shape_coefficients);
+	vector<VectorXf> current_combined_shapes;
+	vector<eos::core::Mesh> current_meshs;
+
+	// The 2D and 3D point correspondences used for the fitting:
+	vector<vector<Vec4f>> model_points; // the points in the 3D shape model of all frames
+	vector<vector<int>> vertex_indices; // their vertex indices of all frames
+	vector<vector<Vec2f>> image_points; // the corresponding 2D landmark points of all frames
+
+	vector<fitting::RenderingParameters> rendering_params;
+
+	// Generate meshes from current shapes.
+	for (int j = 0; j < num_images; ++j) {
+		VectorXf current_combined_shape = current_pca_shape +
+			blendshapes_as_basis *
+			Eigen::Map<const Eigen::VectorXf>(blendshape_coefficients[j].data(), blendshape_coefficients[j].size()
+		);
+
+//		current_combined_shapes.push_back(current_combined_shape);
+
+		eos::core::Mesh current_mesh = morphablemodel::sample_to_mesh(
+			current_combined_shape,
+			morphable_model.get_color_model().get_mean(),
+			morphable_model.get_shape_model().get_triangle_list(),
+			morphable_model.get_color_model().get_triangle_list(),
+			morphable_model.get_texture_coordinates()
+		);
+
+//		current_meshs.push_back(current_mesh);
+
+		// Get the locations of the model locations of the meshes, vertex_indices and image points
+		// (equal to landmark coordinates), for every image / mesh.
+		core::subselect_landmarks<Vec2f, Vec4f>(
+			landmarks[j],
+			landmark_mapper,
+			current_mesh,
+			// output parameters
+			model_points,
+			vertex_indices,
+			image_points
+		);
+
+		// Get the current points from the last added image points and model points
+		auto current_pose = fitting::estimate_orthographic_projection_linear(
+			image_points.back(), model_points.back(), true, image_height
+		);
+
+		fitting::RenderingParameters current_rendering_params(current_pose, image_width, image_height);
+		rendering_params.push_back(current_rendering_params);
+		Mat affine_from_ortho = fitting::get_3x4_affine_camera_matrix(current_rendering_params, image_width, image_height);
+
+		blendshape_coefficients[j] = fitting::fit_blendshapes_to_landmarks_nnls(
+			blendshapes, current_pca_shape, affine_from_ortho, image_points.back(), vertex_indices.back()
+		);
+
+		// Mesh with same PCA coeffs as before, but new expression fit (this is relevant if no initial blendshape coeffs have been given):
+		current_combined_shape = current_pca_shape +
+			morphablemodel::to_matrix(blendshapes) *
+				Eigen::Map<const Eigen::VectorXf>(blendshape_coefficients[j].data(), blendshape_coefficients[j].size()
+			);
+
+		current_combined_shapes.push_back(current_combined_shape);
+
+		current_mesh = morphablemodel::sample_to_mesh(
+			current_combined_shape, morphable_model.get_color_model().get_mean(),
+			morphable_model.get_shape_model().get_triangle_list(),
+			morphable_model.get_color_model().get_triangle_list(),
+			morphable_model.get_texture_coordinates()
+		);
+
+		current_meshs.push_back(current_mesh);
+	}
+
+//	// Need to do an initial pose fit to do the contour fitting inside the loop.
+//	// We'll do an expression fit too, since face shapes vary quite a lot, depending on expressions.
+//	vector<fitting::RenderingParameters> rendering_params;
+//	for (int j = 0; j < num_images; ++j) {
+//		fitting::ScaledOrthoProjectionParameters current_pose = fitting::estimate_orthographic_projection_linear(image_points[j], model_points[j], true, image_height);
+//		fitting::RenderingParameters current_rendering_params(current_pose, image_width, image_height);
+//		rendering_params.push_back(current_rendering_params);
+//
+//		cv::Mat affine_from_ortho = fitting::get_3x4_affine_camera_matrix(current_rendering_params, image_width, image_height);
+//		blendshape_coefficients[j] = fitting::fit_blendshapes_to_landmarks_nnls(blendshapes, current_pca_shape, affine_from_ortho, image_points[j], vertex_indices[j]);
+//
+//		// Mesh with same PCA coeffs as before, but new expression fit (this is relevant if no initial blendshape coeffs have been given):
+//		current_combined_shapes[j] = current_pca_shape + morphablemodel::to_matrix(blendshapes) * Eigen::Map<const Eigen::VectorXf>(blendshape_coefficients[j].data(),blendshape_coefficients[j].size());
+//		current_meshs[j] = morphablemodel::sample_to_mesh(current_combined_shapes[j], morphable_model.get_color_model().get_mean(), morphable_model.get_shape_model().get_triangle_list(), morphable_model.get_color_model().get_triangle_list(), morphable_model.get_texture_coordinates());
+//	}
+
+	// The static (fixed) landmark correspondences which will stay the same throughout
+	// the fitting (the inner face landmarks):
+	vector<vector<int>> fixed_vertex_indices (vertex_indices);
+	vector<vector<Vec2f>> fixed_image_points (image_points);
+
+	std::vector<cv::Mat> affine_from_orthos;
+	std::vector<VectorXf> mean_plus_blendshapes;
+
+	image_points = fixed_image_points;
+	vertex_indices = fixed_vertex_indices;
+
+	for (int j = 0; j < num_images; ++j) {
+		// Given the current pose, find 2D-3D contour correspondences of the front-facing face contour:
+		vector<Vec2f> image_points_contour;
+		vector<int> vertex_indices_contour;
+		auto yaw_angle = glm::degrees(glm::eulerAngles(rendering_params[j].get_rotation())[1]);
+		// For each 2D contour landmark, get the corresponding 3D vertex point and vertex id:
+		std::tie(image_points_contour, std::ignore, vertex_indices_contour) = fitting::get_contour_correspondences(landmarks[j], contour_landmarks, model_contour, yaw_angle, current_meshs[j], rendering_params[j].get_modelview(), rendering_params[j].get_projection(), fitting::get_opencv_viewport(image_width, image_height));
+		// Add the contour correspondences to the set of landmarks that we use for the fitting:
+		vertex_indices[j] = fitting::concat(vertex_indices[j], vertex_indices_contour);
+		image_points[j] = fitting::concat(image_points[j], image_points_contour);
+
+		// Fit the occluding (away-facing) contour using the detected contour LMs:
+		vector<Eigen::Vector2f> occluding_contour_landmarks;
+		if (yaw_angle >= 0.0f) // positive yaw = subject looking to the left
+		{ // the left contour is the occluding one we want to use ("away-facing")
+			auto contour_landmarks_ = core::filter(landmarks[j], contour_landmarks.left_contour); // Can do this outside of the loop
+			std::for_each(begin(contour_landmarks_), end(contour_landmarks_), [&occluding_contour_landmarks](auto&& lm) { occluding_contour_landmarks.push_back({ lm.coordinates[0], lm.coordinates[1] }); });
+		}
+		else {
+			auto contour_landmarks_ = core::filter(landmarks[j], contour_landmarks.right_contour);
+			std::for_each(begin(contour_landmarks_), end(contour_landmarks_), [&occluding_contour_landmarks](auto&& lm) { occluding_contour_landmarks.push_back({ lm.coordinates[0], lm.coordinates[1] }); });
+		}
+		auto edge_correspondences = fitting::find_occluding_edge_correspondences(current_meshs[j], edge_topology, rendering_params[j], occluding_contour_landmarks, 180.0f);
+		image_points[j] = fitting::concat(image_points[j], edge_correspondences.first);
+		vertex_indices[j] = fitting::concat(vertex_indices[j], edge_correspondences.second);
+
+		// Get the model points of the current mesh, for all correspondences that we've got:
+		model_points[j].clear();
+		for (const auto& v : vertex_indices[j])
+		{
+			model_points[j].push_back({ current_meshs[j].vertices[v][0], current_meshs[j].vertices[v][1], current_meshs[j].vertices[v][2], current_meshs[j].vertices[v][3] });
+		}
+
+		// Re-estimate the pose, using all correspondences:
+		fitting::ScaledOrthoProjectionParameters current_pose = fitting::estimate_orthographic_projection_linear(image_points[j], model_points[j], true, image_height);
+		rendering_params[j] = fitting::RenderingParameters(current_pose, image_width, image_height);
+
+		cv::Mat affine_from_ortho = fitting::get_3x4_affine_camera_matrix(rendering_params[j], image_width, image_height);
+		affine_from_orthos.push_back(affine_from_ortho);
+
+		// Estimate the PCA shape coefficients with the current blendshape coefficients:
+		VectorXf current_mean_plus_blendshapes = morphable_model.get_shape_model().get_mean() + blendshapes_as_basis * Eigen::Map<const Eigen::VectorXf>(blendshape_coefficients[j].data(),blendshape_coefficients[j].size());
+		mean_plus_blendshapes.push_back(current_mean_plus_blendshapes);
+	}
+
+	pca_shape_coefficients = fitting::fit_shape_to_landmarks_linear_multi(morphable_model, affine_from_orthos, image_points, vertex_indices, mean_plus_blendshapes, lambda, num_shape_coefficients_to_fit);
+
+	// Estimate the blendshape coefficients with the current PCA model estimate:
+	current_pca_shape = morphable_model.get_shape_model().draw_sample(pca_shape_coefficients);
+
+	for (int j = 0; j < num_images; ++j) {
+		blendshape_coefficients[j] = fitting::fit_blendshapes_to_landmarks_nnls(blendshapes, current_pca_shape, affine_from_orthos[j], image_points[j], vertex_indices[j]);
+
+		current_combined_shapes[j] = current_pca_shape + blendshapes_as_basis * Eigen::Map<const Eigen::VectorXf>(blendshape_coefficients[j].data(),blendshape_coefficients[j].size());
+		current_meshs[j] = morphablemodel::sample_to_mesh(current_combined_shapes[j], morphable_model.get_color_model().get_mean(), morphable_model.get_shape_model().get_triangle_list(), morphable_model.get_color_model().get_triangle_list(), morphable_model.get_texture_coordinates());
+	}
+
+	fitted_image_points = image_points;
+	return { current_meshs, rendering_params }; // I think we could also work with a Mat face_instance in this function instead of a Mesh, but it would convolute the code more (i.e. more complicated to access vertices).
+};
+
 	} /* namespace fitting */
 } /* namespace eos */
 

include/eos/fitting/linear_shape_fitting.hpp

@@ -59,8 +59,16 @@ namespace eos {
  * @param[in] model_standard_deviation The standard deviation of the 3D vertex points in the 3D model, projected to 2D (so the value is in pixels).
  * @return The estimated shape-coefficients (alphas).
  */
-inline std::vector<float> fit_shape_to_landmarks_linear_multi(const morphablemodel::MorphableModel& morphable_model, std::vector<cv::Mat> affine_camera_matrix, std::vector<std::vector<cv::Vec2f>>& landmarks, std::vector<std::vector<int>>& vertex_ids, std::vector<Eigen::VectorXf> base_face=std::vector<Eigen::VectorXf>(), float lambda=3.0f, boost::optional<int> num_coefficients_to_fit=boost::optional<int>(), boost::optional<float> detector_standard_deviation=boost::optional<float>(), boost::optional<float> model_standard_deviation=boost::optional<float>())
-{
+inline std::vector<float> fit_shape_to_landmarks_linear_multi(
+		const morphablemodel::MorphableModel& morphable_model,
+		std::vector<cv::Mat> affine_camera_matrix,
+		std::vector<std::vector<cv::Vec2f>>& landmarks,
+		std::vector<std::vector<int>>& vertex_ids,
+		std::vector<Eigen::VectorXf> base_face=std::vector<Eigen::VectorXf>(),
+		float lambda=3.0f,
+		boost::optional<int> num_coefficients_to_fit=boost::optional<int>(),
+		boost::optional<float> detector_standard_deviation=boost::optional<float>(),
+		boost::optional<float> model_standard_deviation=boost::optional<float>()) {
 
 	assert(affine_camera_matrix.size() == landmarks.size() && landmarks.size() == vertex_ids.size()); // same number of instances (i.e. images/frames) for each of them
 	assert(landmarks.size() == vertex_ids.size());
@@ -100,7 +108,7 @@ inline std::vector<float> fit_shape_to_landmarks_linear_multi(const morphablemod
 	int y_index = 0; // also runs the same as P_index. Should rename to "running_index"?
 	// The mean, with an added homogeneous coordinate (x_1, y_1, z_1, 1, x_2, ...)^t
 	VectorXf v_bar = VectorXf::Ones(4 * total_num_landmarks_dimension);
-	int v_bar_index = 0; // also runs the same as P_index. But be careful, if I change it to be only 1 variable, only increment it once! :-)
+	int v_bar_index = 0; // also runs the same as P_index. But be careful, if I change it to be only 1 variable, only increment it once! :-),
 						 // Well I think that would make it a bit messy since we need to increment inside the for (landmarks...) loop. Try to refactor some other way.
 
     for (int k = 0; k < num_images; ++k)

include/eos/render/render.hpp

@@ -124,8 +124,17 @@ namespace eos {
  * @param[in] enable_far_clipping Whether vertices should be clipped against the far plane.
  * @return A pair with the colourbuffer as its first element and the depthbuffer as the second element.
  */
-inline std::pair<cv::Mat, cv::Mat> render(core::Mesh mesh, glm::tmat4x4<float> model_view_matrix, glm::tmat4x4<float> projection_matrix, int viewport_width, int viewport_height, const boost::optional<Texture>& texture = boost::none, bool enable_backface_culling = false, bool enable_near_clipping = true, bool enable_far_clipping = true)
-{
+inline std::pair<cv::Mat, cv::Mat> render(
+				core::Mesh mesh,
+				glm::tmat4x4<float> model_view_matrix,
+				glm::tmat4x4<float> projection_matrix,
+				int viewport_width,
+				int viewport_height,
+				const boost::optional<Texture>& texture = boost::none,
+				bool enable_backface_culling = false,
+				bool enable_near_clipping = true,
+				bool enable_far_clipping = true,
+				cv::Mat colourbuffer = cv::Mat::zeros(0, 0, CV_8UC4)) {
 	// Some internal documentation / old todos or notes:
 	// maybe change and pass depthBuffer as an optional arg (&?), because usually we never need it outside the renderer. Or maybe even a getDepthBuffer().
 	// modelViewMatrix goes to eye-space (camera space), projection does ortho or perspective proj.
@@ -139,7 +148,10 @@ inline std::pair<cv::Mat, cv::Mat> render(core::Mesh mesh, glm::tmat4x4<float> m
 	using cv::Mat;
 	using std::vector;
 
-	Mat colourbuffer = Mat::zeros(viewport_height, viewport_width, CV_8UC4); // make sure it's CV_8UC4?
+	if (colourbuffer.empty()) {
+		colourbuffer = Mat::zeros(viewport_height, viewport_width, CV_8UC4); // make sure it's CV_8UC4?
+	}
+
 	Mat depthbuffer = std::numeric_limits<float>::max() * Mat::ones(viewport_height, viewport_width, CV_64FC1);
 
 	// Vertex shader:
@@ -147,15 +159,17 @@ inline std::pair<cv::Mat, cv::Mat> render(core::Mesh mesh, glm::tmat4x4<float> m
 	// Assemble the vertices, project to clip space, and store as detail::Vertex (the internal representation):
 	vector<detail::Vertex<float>> clipspace_vertices;
 	clipspace_vertices.reserve(mesh.vertices.size());
+
 	for (int i = 0; i < mesh.vertices.size(); ++i) { // "previously": mesh.vertex
 		glm::tvec4<float> clipspace_coords = projection_matrix * model_view_matrix * mesh.vertices[i];
 		glm::tvec3<float> vertex_colour;
+
 		if (mesh.colors.empty()) {
 			vertex_colour = glm::tvec3<float>(0.5f, 0.5f, 0.5f);
-		}
-		else {
+		} else {
 			vertex_colour = mesh.colors[i];
 		}
+
 		clipspace_vertices.push_back(detail::Vertex<float>{clipspace_coords, vertex_colour, mesh.texcoords[i]});
 	}
 
@@ -234,6 +248,7 @@ inline std::pair<cv::Mat, cv::Mat> render(core::Mesh mesh, glm::tmat4x4<float> m
 	for (const auto& tri : triangles_to_raster) {
 		detail::raster_triangle(tri, colourbuffer, depthbuffer, texture, enable_far_clipping);
 	}
+
 	return std::make_pair(colourbuffer, depthbuffer);
 };
 

include/eos/video/Keyframe.hpp

@@ -78,10 +78,10 @@ public:
 		this->fitting_result = fitting_result;
 	}
 
+	cv::Mat frame;
 	int frame_number;
 	float score = 0.0f;
 
-	cv::Mat frame;
 	fitting::FittingResult fitting_result;
 };
 
@@ -323,7 +323,6 @@ public:
 	// TODO: build support for setting the amount of max_frames in the buffer.
 	BufferedVideoIterator(std::string videoFilePath, boost::property_tree::ptree settings) {
 		std::ifstream file(videoFilePath);
-
 		std::cout << "video file path: " << videoFilePath << std::endl;
 		if (!file.is_open()) {
 			throw std::runtime_error("Error opening given file: " + videoFilePath);
@@ -359,7 +358,6 @@ public:
 		cv::Mat frame;
 		cap >> frame;
 
-
 		// Pop if we exceeded max_frames.
 		if (n_frames > max_frames) {
 			frame_buffer.pop_front();
@@ -373,11 +371,11 @@ public:
 			n_frames++;
 			std::cout << total_frames_processed << ": laplacian score " << frame_laplacian_score << std::endl;
 		} else {
-			std::cout << total_frames_processed << ": skipping frame " << std::endl;
+			std::cout << total_frames_processed << ": skipping frame(";
 			if (frame_laplacian_score == 0) {
-				std::cout << "total black" << std::endl;
+				std::cout << "total black): " << frame_laplacian_score << std::endl;
 			} else {
-				std::cout << "too blurry" << std::endl;
+				std::cout << "too blurry): " << frame_laplacian_score << std::endl;
 			}
 
 		}
@@ -495,7 +493,39 @@ private:
 	unsigned char threshold;
 };
 
-} /* namespace video */
+/**
+* @brief Merges PCA coefficients from a live video with a simple averaging.
+*/
+class PcaCoefficientMerging
+{
+public:
+/**
+ * @brief Merges the given new PCA coefficients with all previously processed coefficients.
+ *
+ * @param[in] coefficients The new coefficients to add.
+ * @return The merged coefficients of all images processed so far.
+ */
+std::vector<float> add_and_merge(const std::vector<float>& coefficients)
+{
+	if (merged_shape_coefficients.empty()) {
+		merged_shape_coefficients = cv::Mat::zeros(coefficients.size(), 1, CV_32FC1);
+	}
+
+	assert(coefficients.size() == merged_shape_coefficients.rows);
+
+	cv::Mat test(coefficients);
+	merged_shape_coefficients = (merged_shape_coefficients * num_processed_frames + test) / (num_processed_frames + 1.0f);
+	++num_processed_frames;
+	return std::vector<float>(merged_shape_coefficients.begin<float>(), merged_shape_coefficients.end<float>());
+};
+
+private:
+	int num_processed_frames = 0;
+	cv::Mat merged_shape_coefficients;
+};
+
+
+	} /* namespace video */
 } /* namespace eos */
 
 #endif /* KEYFRAME_HPP_ */

share/default_reconstruction_config.ini

+[video]
+max_frames=6
+min_frames=5
+drop_frames=0
+laplacian_threshold=1000

utils/accuracy-evaluation.cpp

@@ -24,6 +24,7 @@
 #include "eos/render/utils.hpp"
 #include "eos/render/texture_extraction.hpp"
 #include "eos/video/Keyframe.hpp"
+#include "eos/fitting/ReconstructionData.hpp"
 
 #include "opencv2/core/core.hpp"
 #include "opencv2/opencv.hpp"
@@ -55,6 +56,8 @@ using std::string;
 
 using namespace cv;
 
+typedef unsigned int uint;
+
 /**
  * Draws the given mesh as wireframe into the image.
  *
@@ -74,8 +77,7 @@ void draw_wireframe(cv::Mat image, const eos::core::Mesh& mesh, glm::mat4x4 mode
 		const auto p1 = glm::project({ mesh.vertices[triangle[0]][0], mesh.vertices[triangle[0]][1], mesh.vertices[triangle[0]][2] }, modelview, projection, viewport);
 		const auto p2 = glm::project({ mesh.vertices[triangle[1]][0], mesh.vertices[triangle[1]][1], mesh.vertices[triangle[1]][2] }, modelview, projection, viewport);
 		const auto p3 = glm::project({ mesh.vertices[triangle[2]][0], mesh.vertices[triangle[2]][1], mesh.vertices[triangle[2]][2] }, modelview, projection, viewport);
-		if (eos::render::detail::are_vertices_ccw_in_screen_space(glm::vec2(p1), glm::vec2(p2), glm::vec2(p3)))
-		{
+		if (eos::render::detail::are_vertices_ccw_in_screen_space(glm::vec2(p1), glm::vec2(p2), glm::vec2(p3))) {
 			cv::line(image, cv::Point(p1.x, p1.y), cv::Point(p2.x, p2.y), colour);
 			cv::line(image, cv::Point(p2.x, p2.y), cv::Point(p3.x, p3.y), colour);
 			cv::line(image, cv::Point(p3.x, p3.y), cv::Point(p1.x, p1.y), colour);
@@ -113,7 +115,9 @@ void evaluate_accuracy(
 		core::LandmarkCollection<cv::Vec2f> landmarks,
 		core::LandmarkMapper landmark_mapper,
 		const eos::core::Mesh& mesh,
-		Mat affine_from_ortho) {
+		Mat affine_from_ortho,
+		boost::property_tree::ptree settings) {
+
 	vector<float> total_error;
 
 	// Sub-select all the landmarks which we have a mapping for (i.e. that are defined in the 3DMM):
@@ -147,27 +151,157 @@ void evaluate_accuracy(
 	float accum = 0.0;
 	float mean_error = std::accumulate(total_error.begin(), total_error.end(), 0) / landmarks.size();
 
-	// cacl. standard deviation
-	std::for_each (std::begin(total_error), std::end(total_error), [&](const float d) {
+	for(auto &d: total_error) {
 		accum += (d - mean_error) * (d - mean_error);
-	});
+	}
 
 	float stddev = std::sqrt(accum / (total_error.size() - 1));
 
 	std::cout << "stddev/mean_error: " << stddev << " " <<  mean_error << std::endl;
 }
 
+/**
+ *
+ * @param key_frames
+ * @param rendering_paramss
+ * @param landmark_list
+ * @param morphable_model
+ * @param blend_shapes
+ * @param meshs
+ * @param pca_shape_coefficients
+ * @param blend_shape_coefficients
+ * @param fitted_image_points
+ * @param annotations
+ * @param landmark_mapper
+ * @param settings
+ * @param n_iter
+ */
+void output_render(
+		std::deque<eos::video::Keyframe> key_frames,
+		std::vector<fitting::RenderingParameters> rendering_paramss,
+		std::vector<core::LandmarkCollection<cv::Vec2f>> landmark_list,
+		morphablemodel::MorphableModel morphable_model,
+		vector<morphablemodel::Blendshape> blend_shapes,
+		vector<core::Mesh> meshs,
+		std::vector<float> pca_shape_coefficients,
+		std::vector<std::vector<float>> blend_shape_coefficients,
+		std::vector<std::vector<cv::Vec2f>> fitted_image_points,
+		std::vector<std::string> annotations,
+		core::LandmarkMapper landmark_mapper,
+		boost::property_tree::ptree settings,
+		int n_iter) {
+
+	Mat merged_isomap;
+	WeightedIsomapAveraging isomap_averaging(60.f); // merge all triangles that are facing <60° towards the camera
+	eos::video::PcaCoefficientMerging pca_shape_merging;
+
+	auto outputfilebase = annotations[0];
+
+	for (uint i = 0; i < key_frames.size(); ++i) {
+		Mat frame = key_frames[i].frame;
+
+		auto unmodified_frame = frame.clone();
+		int frame_number = key_frames[i].frame_number;
+
+//		float yaw_angle = glm::degrees(glm::yaw(rendering_paramss[i].get_rotation()));
+		int frame_width = frame.cols;
+		int frame_height = frame.rows;
+
+		// Extract the texture using the fitted mesh from this frame:
+		Mat affine_cam = fitting::get_3x4_affine_camera_matrix(rendering_paramss[i], frame.cols, frame.rows);
+		Mat isomap = render::extract_texture(
+				meshs[i],
+				affine_cam,
+				unmodified_frame,
+				true,
+				render::TextureInterpolation::NearestNeighbour,
+				512
+		);
+
+		// Merge the isomaps - add the current one to the already merged ones:
+		merged_isomap = isomap_averaging.add_and_merge(isomap);
+	}
+
+	// Get last frame (that's the newest one).
+	Mat frame = key_frames.back().frame;
+	auto last_rendering_params = rendering_paramss.back();
+	auto last_blend_coefficients = blend_shape_coefficients.back();
+
+	int frame_width = frame.cols;
+	int frame_height = frame.rows;
+
+	// Same for the shape:
+	pca_shape_coefficients = pca_shape_merging.add_and_merge(pca_shape_coefficients);
+	auto blendshapes_as_basis = morphablemodel::to_matrix(blend_shapes);
+	auto merged_shape = morphable_model.get_shape_model().draw_sample(pca_shape_coefficients) +
+						blendshapes_as_basis *
+						Eigen::Map<const Eigen::VectorXf>(last_blend_coefficients.data(),
+														  last_blend_coefficients.size()
+						);
+
+	auto merged_mesh = morphablemodel::sample_to_mesh(
+			merged_shape,
+			morphable_model.get_color_model().get_mean(),
+			morphable_model.get_shape_model().get_triangle_list(),
+			morphable_model.get_color_model().get_triangle_list(),
+			morphable_model.get_texture_coordinates()
+	);
+
+
+	// Render the model in a separate window using the estimated pose, shape and merged texture:
+	Mat rendering;
+	// render needs 4 channels 8 bits image, needs a two step conversion.
+	cvtColor(frame, rendering, CV_BGR2BGRA);
+
+	// make sure the image is CV_8UC4, maybe do check first?
+	rendering.convertTo(rendering, CV_8UC4);
+
+	std::tie(rendering, std::ignore) = render::render(
+			merged_mesh,
+			last_rendering_params.get_modelview(),
+			last_rendering_params.get_projection(),
+			frame_width,
+			frame_height,
+			render::create_mipmapped_texture(merged_isomap),
+			true,
+			false,
+			false,
+			rendering
+	);
+
+	cv::imshow("render", rendering);
+	cv::waitKey(10);
+}
+
+/**
+ *
+ * @param key_frames
+ * @param rendering_paramss
+ * @param landmark_list
+ * @param morphable_model
+ * @param blend_shapes
+ * @param meshs
+ * @param pca_shape_coefficients
+ * @param blend_shape_coefficients
+ * @param fitted_image_points
+ * @param annotations
+ * @param landmark_mapper
+ * @param settings
+ * @param n_iter
+ */
 void evaluate_results(
 		std::deque<eos::video::Keyframe> key_frames,
 		std::vector<fitting::RenderingParameters> rendering_paramss,
 		std::vector<core::LandmarkCollection<cv::Vec2f>> landmark_list,
 		morphablemodel::MorphableModel morphable_model,
+		vector<morphablemodel::Blendshape> blend_shapes,
 		vector<core::Mesh> meshs,
 		std::vector<float> pca_shape_coefficients,
 		std::vector<std::vector<float>> blend_shape_coefficients,
 		std::vector<std::vector<cv::Vec2f>> fitted_image_points,
 		std::vector<std::string> annotations,
 		core::LandmarkMapper landmark_mapper,
+		boost::property_tree::ptree settings,
 		int n_iter) {
 
 	WeightedIsomapAveraging isomap_averaging(60.f); // merge all triangles that are facing <60° towards the camera
@@ -226,21 +360,32 @@ void evaluate_results(
 				morphable_model.get_texture_coordinates()
 		);
 
-		std::tie(frontal_rendering, std::ignore) = eos::render::render(neutral_expression, modelview_frontal, glm::ortho(-130.0f, 130.0f, -130.0f, 130.0f), 256, 256, render::create_mipmapped_texture(isomap), true, false, false);
-
-		cv::imwrite(outputfile + iter + ".frontal.png", frontal_rendering);
-
-		// And save the isomap:
+		outimg = frame.clone();
 		cv::imwrite(outputfile + iter + ".isomap.png", isomap);
 
 		// merge the isomaps:
 		merged_isomap = isomap_averaging.add_and_merge(isomap);
 
+		std::tie(frontal_rendering, std::ignore) = eos::render::render(
+				neutral_expression,
+				rendering_paramss[i].get_modelview(),
+				rendering_paramss[i].get_projection(),
+				frame_width,
+				frame_height,
+				render::create_mipmapped_texture(merged_isomap),
+				true,
+				false,
+				false,
+				outimg
+		);
+
+		cv::imwrite(outputfile + iter + ".frontal.png", frontal_rendering);
 		evaluate_accuracy(
 			landmark_list[i],
 			landmark_mapper,
 			meshs[i],
-			affine_from_ortho
+			affine_from_ortho,
+			settings
 		);
 	}
 
@@ -257,8 +402,22 @@ void evaluate_results(
 	core::Mesh neutral_expression = morphablemodel::sample_to_mesh(
 			morphable_model.get_shape_model().draw_sample(pca_shape_coefficients),
 			morphable_model.get_color_model().get_mean(),
-			morphable_model.get_shape_model().get_triangle_list(), morphable_model.get_color_model().get_triangle_list(), morphable_model.get_texture_coordinates());
-	std::tie(frontal_rendering, std::ignore) = render::render(neutral_expression, modelview_frontal, glm::ortho(-130.0f, 130.0f, -130.0f, 130.0f), 512, 512, render::create_mipmapped_texture(merged_isomap), true, false, false);
+			morphable_model.get_shape_model().get_triangle_list(),
+			morphable_model.get_color_model().get_triangle_list(),
+			morphable_model.get_texture_coordinates()
+	);
+
+	std::tie(frontal_rendering, std::ignore) = render::render(
+			neutral_expression,
+			modelview_frontal,
+			glm::ortho(-130.0f, 130.0f, -130.0f, 130.0f),
+			512, 512,
+			render::create_mipmapped_texture(merged_isomap),
+			true,
+			false,
+			false
+	);
+
 	cv::imwrite(outputfile + iter + ".merged_frontal.png", frontal_rendering);
 
 	// Save the mesh as textured obj:
@@ -276,12 +435,6 @@ boost::property_tree::ptree get_reconstruction_config(std::string filename) {
 	boost::property_tree::ptree pt;
 	boost::property_tree::ini_parser::read_ini(filename, pt);
 
-	std::cout << pt.get<std::string>("video.max_frames") << std::endl;
-	std::cout << pt.get<std::string>("video.drop_frames") << std::endl;
-	std::cout << pt.get<std::string>("video.min_frames") << std::endl;
-	std::cout << pt.get<std::string>("video.skip_frames") << std::endl;
-	std::cout << pt.get<std::string>("video.blur_threshold") << std::endl;
-
 	return pt;
 }
 
@@ -296,7 +449,8 @@ boost::property_tree::ptree get_reconstruction_config(std::string filename) {
  * @param landmarks
  * @return
  */
-vector<core::LandmarkCollection<cv::Vec2f>> sample_landmarks(std::deque<eos::video::Keyframe> key_frames, vector<core::LandmarkCollection<cv::Vec2f>> landmarks) {
+vector<core::LandmarkCollection<cv::Vec2f>> sample_landmarks(
+		std::deque<eos::video::Keyframe> key_frames, vector<core::LandmarkCollection<cv::Vec2f>> landmarks) {
 	vector<core::LandmarkCollection<cv::Vec2f>> sublist;
 
 	for (auto& f : key_frames) {
@@ -319,7 +473,7 @@ int main(int argc, char *argv[]) {
 	fs::path modelfile, isomapfile, videofile, landmarksfile, mappingsfile, contourfile, edgetopologyfile, blendshapesfile, outputfile, reconstruction_config;
 	std::vector<std::string> annotations;
 
-	// get annotaitions from one file
+	// get annotations from one file
 	bool get_annotations = false;
 
 	try {
@@ -331,7 +485,7 @@ int main(int argc, char *argv[]) {
 				 "a Morphable Model stored as cereal BinaryArchive")
 				("video,v", po::value<fs::path>(&videofile)->required(),
 				 "an input image")
-				("config,c", po::value<fs::path>(&reconstruction_config)->default_value("../share/default_reconstruction_config.ini"),
+				("config,f", po::value<fs::path>(&reconstruction_config)->default_value("../share/default_reconstruction_config.ini"),
 				 "configuration file for the reconstruction")
 				("get_annotations,g", po::bool_switch(&get_annotations)->default_value(false),
 				 "read .pts annotation file locations from one file, put one file path on each line")
@@ -365,9 +519,25 @@ int main(int argc, char *argv[]) {
 		return EXIT_SUCCESS;
 	}
 
-	// start loading prerequisites
+	// Start loading prerequisites:
 	morphablemodel::MorphableModel morphable_model;
+	std::vector<float> pca_shape_coefficients;
+
+	// List of blend_shapes coefficients:
+	std::vector<std::vector<float>> blend_shape_coefficients;
+	std::vector<std::vector<cv::Vec2f>> fitted_image_points;
+
+	// These will be the final 2D and 3D points used for the fitting:
+	vector<cv::Vec3f> model_points; // the points in the 3D shape model
+	vector<int> vertex_indices; // their vertex indices
+	vector<core::Mesh> meshs;
+	vector<fitting::RenderingParameters> rendering_paramss;
+
+	// Load landmarks, LandmarkMapper and the Morphable Model:
+	auto landmark_mapper = core::LandmarkMapper(mappingsfile);
 
+	// Load all annotation files into lists of landmarks:
+	vector<core::LandmarkCollection<cv::Vec2f>> landmark_list;
 	try {
 		morphable_model = morphablemodel::load_model(modelfile.string());
 	} catch (const std::runtime_error &e) {
@@ -375,36 +545,32 @@ int main(int argc, char *argv[]) {
 		return EXIT_FAILURE;
 	}
 
-	// Load landmarks, LandmarkMapper and the Morphable Model:
-	core::LandmarkMapper landmark_mapper = core::LandmarkMapper(mappingsfile);
-
-	// load all annotation files into lists of landmarks
-	vector<core::LandmarkCollection<cv::Vec2f>> landmark_list;
+	// Load all annotation using input parameters:
 	try {
-		std::tie(landmark_list, annotations) = eos::core::load_annotations<cv::Vec2f>(annotations, landmark_mapper, morphable_model, get_annotations);
+		std::tie(landmark_list, annotations) = eos::core::load_annotations<cv::Vec2f>(
+				annotations,
+				landmark_mapper,
+				morphable_model,
+				get_annotations);
 	} catch(const std::runtime_error &e) {
 		std::cout << e.what() << std::endl;
 		return EXIT_FAILURE;
 	}
 
 	// The expression blendshapes:
-	vector<morphablemodel::Blendshape> blend_shapes = morphablemodel::load_blendshapes(blendshapesfile.string());
+	auto blend_shapes = morphablemodel::load_blendshapes(blendshapesfile.string());
 
 	// These two are used to fit the front-facing contour to the ibug contour landmarks:
-	fitting::ModelContour model_contour = contourfile.empty() ? fitting::ModelContour() : fitting::ModelContour::load(contourfile.string());
-	fitting::ContourLandmarks ibug_contour = fitting::ContourLandmarks::load(mappingsfile.string());
-
+	auto model_contour = contourfile.empty() ? fitting::ModelContour() : fitting::ModelContour::load(contourfile.string());
+	auto ibug_contour = fitting::ContourLandmarks::load(mappingsfile.string());
 	// The edge topology is used to speed up computation of the occluding face contour fitting:
-	morphablemodel::EdgeTopology edge_topology = morphablemodel::load_edge_topology(edgetopologyfile.string());
+	auto edge_topology = morphablemodel::load_edge_topology(edgetopologyfile.string());
 
-	// These will be the final 2D and 3D points used for the fitting:
-	vector<cv::Vec3f> model_points; // the points in the 3D shape model
-	vector<int> vertex_indices; // their vertex indices
-	vector<core::Mesh> meshs;
-	vector<fitting::RenderingParameters> rendering_paramss;
+	// Read .ini file to accommodate.
+	auto settings = get_reconstruction_config(reconstruction_config.string());
 
+	// Start with the video play and get video file:
 	BufferedVideoIterator vid_iterator;
-	boost::property_tree::ptree settings = get_reconstruction_config(reconstruction_config.string());
 
 	try {
 		vid_iterator = BufferedVideoIterator(videofile.string(), settings);
@@ -413,29 +579,21 @@ int main(int argc, char *argv[]) {
 		return EXIT_FAILURE;
 	}
 
-	// iteration count
-	int frame_width = vid_iterator.width;
-	int frame_height = vid_iterator.height;
-
-	// test with loading 10 frames subsequently.
+	// Start getting video frames:
 	std::deque<eos::video::Keyframe> key_frames = vid_iterator.next();
+	eos::fitting::ReconstructionData data;
 
-	std::vector<float> pca_shape_coefficients;
-	std::vector<std::vector<float>> blend_shape_coefficients;
-	std::vector<std::vector<cv::Vec2f>> fitted_image_points;
-
+	// Count the amount of iterations:
 	int n_iter = 0;
-
 	while(!(key_frames.empty())) {
-		if (n_iter == 10) {
-			break;
-		}
-
-		vector<core::LandmarkCollection<cv::Vec2f>> landmark_sublist = sample_landmarks(
-			key_frames, landmark_list
-		);
+//		if (n_iter == 100) {
+//			break;
+//		}
+		// Generate a sublist of the total available landmark list:
+		auto landmark_sublist = sample_landmarks(key_frames, landmark_list);
 
-		std::tie(meshs, rendering_paramss) = fitting::fit_shape_and_pose_multi(
+		// Fit shape and pose:
+		std::tie(meshs, rendering_paramss) = fitting::fit_shape_and_pose_multi_2(
 				morphable_model,
 				blend_shapes,
 				landmark_sublist,
@@ -455,31 +613,29 @@ int main(int argc, char *argv[]) {
 				fitted_image_points
 		);
 
-		evaluate_results(
+//		vid_iterator.setReconstructionResults(reconstructionData);
+
+		// Render output:
+		output_render(
 				key_frames,
 				rendering_paramss,
 				landmark_sublist,
 				morphable_model,
+				blend_shapes,
 				meshs,
 				pca_shape_coefficients,
 				blend_shape_coefficients,
 				fitted_image_points,
 				annotations,
 				landmark_mapper,
+				settings,
 				n_iter
 		);
 
+		// Get new frames:
 		key_frames = vid_iterator.next();
 		n_iter++;
 	}
 
 	return EXIT_SUCCESS;
-
 }
-
-//		// iterator through all frames, not needed persee.
-//		for (std::deque<eos::video::Keyframe>::iterator it = frames.begin(); it!=frames.end(); ++it) {
-//			std::cout << it->score << " ";
-//			frame_count++;
-//		}
-