First CommitHEADmaster

1 files changed, 222 insertions, 0 deletions

diff --git a/sci_gateway1/cpp/opencv_predict.cpp b/sci_gateway1/cpp/opencv_predict.cpp
new file mode 100644
index 0000000..51b9710
--- /dev/null
+++ b/sci_gateway1/cpp/opencv_predict.cpp
@@ -0,0 +1,222 @@
+/***************************************************
+Author : Rohit Suri
+***************************************************/
+#include <iostream>
+#include <opencv2/opencv.hpp>
+#include <opencv2/nonfree/nonfree.hpp>
+#include <opencv2/ml/ml.hpp>
+
+using namespace std;
+using namespace cv;
+
+extern "C"
+{
+    #include "api_scilab.h"
+    #include "Scierror.h"
+    #include "BOOL.h"
+    #include <localization.h>
+    #include "sciprint.h"
+    #include "../common.h"
+    int opencv_predict(char *fname, unsigned long fname_len)
+    {
+        // Error management variables
+        SciErr sciErr;
+
+        //------Local variables------//
+        int upright = 1;
+        Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("FlannBased");
+        Ptr<DescriptorExtractor> extractor = new SurfDescriptorExtractor(1, 4, 2, 1, int(upright));
+        BOWImgDescriptorExtractor bowDE(extractor, matcher);
+        SurfFeatureDetector detector(1, 4, 2, 1, int(upright));
+        char *classifierLocation = NULL;
+        Mat dictionary,features;
+        double response;
+        vector<KeyPoint> keyPoints;
+        CvSVM svm;
+        int dictionarySize;
+        int *piAddr = NULL;
+        int *piChild = NULL;
+        int iRows, iCols;
+        char **pstData = NULL;
+        int *piLen = NULL;
+        char **classifierDescription = NULL;
+        int classifierDescriptionCount;
+        char *bagOfFeaturesLocation = NULL;
+        int descriptionCount;
+        Mat input;
+        //------Check number of parameters------//
+        CheckInputArgument(pvApiCtx, 2, 2);
+        CheckOutputArgument(pvApiCtx, 1, 1);
+
+        //------Get input arguments------//
+        retrieveImage(input,2);
+        sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+        if(!isListType(pvApiCtx, piAddr))
+        {
+            Scierror(999, "Error: The input argument #1 is not of type classifier.\n");
+            return 0;
+        }
+
+        // Extracting object type and checking if type is classifier
+        sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL);
+        if(sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        piLen = (int*)malloc(sizeof(int) * iRows * iCols);
+
+        sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL);
+        if(sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        pstData = (char**)malloc(sizeof(char*) * iRows * iCols);
+
+        for(int iter = 0 ; iter < iRows * iCols ; iter++)
+        {
+            pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination
+        }
+
+        sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData);
+        if(sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        if(!(strcmp(pstData[0],"classifier")==0))
+        {
+            Scierror(999, "Error: The input argument #1 is not of type classifier.\n");
+            return 0;
+        }
+        sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        piLen = (int*) malloc(sizeof(int) * iRows * iCols);
+
+        sciErr = getMatrixOfStringInList(pvApiCtx,  piAddr, 2,  &iRows,  &iCols,  piLen,  NULL);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        pstData = (char**) malloc(sizeof(char*) * iRows * iCols);
+        for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++)
+        {
+            pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1);
+        }
+
+        sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, pstData);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        if(iRows!=1 || iCols!=1)
+        {
+            Scierror(999, "1x1 Matrix expected for classifier argument.");
+            return 0;
+        }
+        classifierLocation = pstData[0];
+        sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, NULL, NULL);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        piLen = (int*) malloc(sizeof(int) * iRows * iCols);
+
+        sciErr = getMatrixOfStringInList(pvApiCtx,  piAddr, 3,  &iRows,  &iCols,  piLen,  NULL);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        pstData = (char**) malloc(sizeof(char*) * iRows * iCols);
+        for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++)
+        {
+            pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1);
+        }
+
+        sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, pstData);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        if(iRows!=1 || iCols!=1)
+        {
+            Scierror(999, "1x1 Matrix expected for bagOfFeatures argument.");
+            return 0;
+        }
+        bagOfFeaturesLocation = pstData[0];
+        sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, NULL, NULL);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        piLen = (int*) malloc(sizeof(int) * iRows * iCols);
+
+        sciErr = getMatrixOfStringInList(pvApiCtx,  piAddr, 4,  &iRows,  &iCols,  piLen,  NULL);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+
+        classifierDescription = (char**) malloc(sizeof(char*) * iRows * iCols);
+        for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++)
+        {
+            classifierDescription[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1);
+        }
+
+        sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, classifierDescription);
+        if (sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+        //------Actual processing------//
+        FileStorage fs(bagOfFeaturesLocation, FileStorage::READ);
+        fs["dictionary"] >> dictionary;
+        fs.release();
+        dictionarySize = dictionary.rows;
+        bowDE.setVocabulary(dictionary);
+        svm.load(classifierLocation);
+        detector.detect(input, keyPoints);
+        bowDE.compute(input, keyPoints, features);
+        response = svm.predict(features);
+        //------Create output arguments------//
+        sciErr = createMatrixOfString(pvApiCtx, nbInputArgument(pvApiCtx)+1, 1, 1, &classifierDescription[(int)response]);
+        if(sciErr.iErr)
+        {
+            printError(&sciErr, 0);
+            return 0;
+        }
+        //------Return Arguments------//
+        AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1;
+        ReturnArguments(pvApiCtx);
+        return 0;
+    }
+    /* ==================================================================== */
+}