Working example.

davidstutz · Jul 17, 2014 · e08018c · e08018c
1 parent 867c25a
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diff --git a/CMakeLists.txt b/CMakeLists.txt
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+cmake_minimum_required(VERSION 2.8)
+
+project(vlfeat_slic_example)
+
+set(EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/bin)
+
+add_library(vlfeat_slic lib_vlfeat/vl/host.c
+lib_vlfeat/vl/random.c
+lib_vlfeat/vl/generic.c
+lib_vlfeat/vl/slic.c)
+add_subdirectory(vlfeat_slic_cli)
diff --git a/vlfeat_slic_cli/CMakeLists.txt b/vlfeat_slic_cli/CMakeLists.txt
@@ -0,0 +1,6 @@
+include_directories(../lib_vlfeat/)
+
+find_package(OpenCV REQUIRED)
+
+add_executable(vlfeat_slic_example main.cpp)
+target_link_libraries(vlfeat_slic_example ${OpenCV_LIBS} vlfeat_slic)
diff --git a/vlfeat_slic_cli/main.cpp b/vlfeat_slic_cli/main.cpp
@@ -0,0 +1,93 @@
+// OpenCV can be used to read images.
+#include <opencv2/opencv.hpp>
+
+// The VLFeat header files need to be declared external.
+extern "C" {
+    #include "vl/generic.h"
+    #include "vl/slic.h"
+}
+
+int main() {
+    // Read the Lenna image. The matrix 'mat' will have 3 8 bit channels
+    // corresponding to BGR color space.
+    cv::Mat mat = cv::imread("Lenna.png", CV_LOAD_IMAGE_COLOR);
+
+    // Convert image to one-dimensional array.
+    float* image = new float[mat.rows*mat.cols*mat.channels()];
+    for (int i = 0; i < mat.rows; ++i) {
+        for (int j = 0; j < mat.cols; ++j) {
+            // Assuming three channels ...
+            image[j + mat.cols*i + mat.cols*mat.rows*0] = mat.at<cv::Vec3b>(i, j)[0];
+            image[j + mat.cols*i + mat.cols*mat.rows*1] = mat.at<cv::Vec3b>(i, j)[1];
+            image[j + mat.cols*i + mat.cols*mat.rows*2] = mat.at<cv::Vec3b>(i, j)[2];
+        }
+    }
+
+    // The algorithm will store the final segmentation in a one-dimensional array.
+    vl_uint32* segmentation = new vl_uint32[mat.rows*mat.cols];
+    vl_size height = mat.rows;
+    vl_size width = mat.cols;
+    vl_size channels = mat.channels();
+
+    // The region size defines the number of superpixels obtained.
+    // Regularization describes a trade-off between the color term and the
+    // spatial term.
+    vl_size region = 30;        
+    float regularization = 1000.;
+    vl_size minRegion = 10;
+
+    vl_slic_segment(segmentation, image, width, height, channels, region, regularization, minRegion);
+
+    // Convert segmentation.
+    int** labels = new int*[mat.rows];
+    for (int i = 0; i < mat.rows; ++i) {
+        labels[i] = new int[mat.cols];
+
+        for (int j = 0; j < mat.cols; ++j) {
+            labels[i][j] = (int) segmentation[j + mat.cols*i];
+        }
+    }
+
+    int label = 0;
+    int labelTop = -1;
+    int labelBottom = -1;
+    int labelLeft = -1;
+    int labelRight = -1;
+
+    for (int i = 0; i < mat.rows; i++) {
+        for (int j = 0; j < mat.cols; j++) {
+
+            label = labels[i][j];
+
+            labelTop = label;
+            if (i > 0) {
+                labelTop = labels[i - 1][j];
+            }
+
+            labelBottom = label;
+            if (i < mat.rows - 1) {
+                labelBottom = labels[i + 1][j];
+            }
+
+            labelLeft = label;
+            if (j > 0) {
+                labelLeft = labels[i][j - 1];
+            }
+
+            labelRight = label;
+            if (j < mat.cols - 1) {
+                labelRight = labels[i][j + 1];
+            }
+
+            if (label != labelTop || label != labelBottom || label!= labelLeft || label != labelRight) {
+                mat.at<cv::Vec3b>(i, j)[0] = 0;
+                mat.at<cv::Vec3b>(i, j)[1] = 0;
+                mat.at<cv::Vec3b>(i, j)[2] = 255;
+            }
+        }
+    }
+
+    cv::imwrite("Lenna_contours.png", mat);
+
+    return 0;
+}