Add MocapNET

animation/MocapNET/src/MocapNET4/MocapNET4Test/CMakeLists.txt

@@ -0,0 +1,24 @@
+project( MocapNET4Test ) 
+cmake_minimum_required( VERSION 2.8.7 )   
+#cmake_minimum_required(VERSION 3.5)
+find_package(OpenCV REQUIRED)
+INCLUDE_DIRECTORIES(${OpenCV_INCLUDE_DIRS})
+
+#set_property(GLOBAL PROPERTY USE_FOLDERS ON)
+set(CMAKE_CXX_STANDARD 11)  
+include_directories(${TENSORFLOW_INCLUDE_ROOT})
+include_directories(../MocapNETLib4) #<- includes in test.cpp
+
+
+add_executable(MocapNET4Test test.cpp)
+
+target_link_libraries(MocapNET4Test rt dl m ${OpenCV_LIBRARIES} ${OPENGL_LIBS} JointEstimator2D Tensorflow  TensorflowFramework MocapNETLib4 ${NETWORK_CLIENT_LIBRARIES} ${PNG_Libs} ${JPG_Libs} )
+set_target_properties(MocapNET4Test PROPERTIES DEBUG_POSTFIX "D") 
+
+
+set_target_properties(MocapNET4Test PROPERTIES 
+                       ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_SOURCE_DIR}"
+                       LIBRARY_OUTPUT_DIRECTORY "${CMAKE_SOURCE_DIR}"
+                       RUNTIME_OUTPUT_DIRECTORY "${CMAKE_SOURCE_DIR}"
+                      )
+

animation/MocapNET/src/MocapNET4/MocapNET4Test/test.cpp

@@ -0,0 +1,122 @@
+
+/** @file livedemo.cpp
+ *  @brief This is the main "demo" offered in this repository, it will take a stream from a webcam or video file using OpenCV and run
+*   2D pose estimation + MocapNET giving you a nice 3D visualization as well as an output .bvh file
+ *  @author Ammar Qammaz (AmmarkoV)
+ */
+#include <stdio.h>
+#include <unistd.h>
+//-----------------------------------------------------------------
+
+#include "PCA/PCA.h"
+#include "JSON/readModelConfiguration.h"
+#include "JSON/readListFile.h"
+
+#include "NSxM/NSxM.h"
+
+#define NORMAL   "\033[0m"
+#define BLACK   "\033[30m"      /* Black */
+#define RED     "\033[31m"      /* Red */
+#define GREEN   "\033[32m"      /* Green */
+#define YELLOW  "\033[33m"      /* Yellow */
+
+
+
+void testPCA(struct PCAData * pca)
+{
+    float output[210]={0};
+    int outputSize = 210;
+
+    float input[458]={0};
+    int inputSize = 458;
+    for (int i=0; i<inputSize; i++)
+    {
+        input[i]=1.0;
+    }
+
+    doPCATransform(output,&outputSize,pca,input,inputSize,210);
+
+    for (int i=0; i<outputSize; i++)
+    {
+        fprintf(stderr,"%u = %f \n",i,output[i]);
+    }
+}
+
+
+
+
+int main(int argc, char *argv[])
+{
+    //struct MocapNET2Options options= {0};
+    //struct MocapNET4 mnet={0};
+
+    struct PCAData pcaUpperBody={0};
+    loadPCADataFromJSON(&pcaUpperBody,"dataset/combinedModel/mocapnet4/mode1/1.0/step1_upperbody_all/upperbody_all.pca");
+    // the camera will be deinitialized automatically in VideoCapture destructor
+
+    struct ModelConfigurationData modelConfigurationUpperBody={0};
+    loadModelConfigurationData(&modelConfigurationUpperBody,"dataset/combinedModel/mocapnet4/mode1/1.0/step1_upperbody_all/upperbody_configuration.json");
+    printModelConfigurationData(&modelConfigurationUpperBody);
+
+    printf("Now will load I/O lists..\n");
+
+    struct listFileData neuralNetworkInputsUpperBody  = {0};
+    struct listFileData neuralNetworkOutputsUpperBody = {0};
+    struct listFileData neuralNetworkJointsUpperBody  = {0};
+    //----------------------------------------------------------------------------------------------------------------------------
+    readListFile(&neuralNetworkInputsUpperBody,"dataset/combinedModel/mocapnet4/mode1/1.0/step1_upperbody_all/neuralNetworkInputs.list");
+    printListFile(&neuralNetworkInputsUpperBody,"neuralNetworkInputs");
+    //----------------------------------------------------------------------------------------------------------------------------
+    readListFile(&neuralNetworkOutputsUpperBody,"dataset/combinedModel/mocapnet4/mode1/1.0/step1_upperbody_all/neuralNetworkOutputs.list");
+    printListFile(&neuralNetworkOutputsUpperBody,"neuralNetworkOutputs");
+    //----------------------------------------------------------------------------------------------------------------------------
+    readListFile(&neuralNetworkJointsUpperBody,"dataset/combinedModel/mocapnet4/mode1/1.0/step1_upperbody_all/neuralNetworkJoints.list");
+    printListFile(&neuralNetworkJointsUpperBody,"neuralNetworkJoints");
+    //----------------------------------------------------------------------------------------------------------------------------
+
+
+    unsigned int data2DLength = 25 * 3; //BODY25 * (x,y,vis)
+    float * data2D = (float*) malloc(sizeof(float) * data2DLength);
+    //---------------------------------------------------------------
+    for (int i=0; i<25; i++)
+    {
+        data2D[i*3 + 0 ] = 0.1 * i;
+        data2D[i*3 + 1 ] = 0.1 * i;
+        data2D[i*3 + 2 ] = 1.0;
+    }
+
+    struct inputRouting routeUpperBody={0};
+    //---------------------------------------------------------------
+    generateRouteFromLabels(
+                             &modelConfigurationUpperBody,
+                             &routeUpperBody,
+                             Body25Labels,
+                             25
+                           );
+
+    struct descriptor upperBodyNSRM={0};
+    //---------------------------------------------------------------
+    if (data2D!=0)
+    {
+     createDescriptor(
+                      &upperBodyNSRM,
+                      data2D,
+                      data2DLength,
+                      &routeUpperBody,
+                      &modelConfigurationUpperBody,
+                      &pcaUpperBody,
+                      &neuralNetworkJointsUpperBody,
+                      &neuralNetworkOutputsUpperBody
+                     );
+
+     fprintf(stderr,"\nGenerated UpperBody Descriptor : \n");
+     for (int i=0; i<upperBodyNSRM.numberOfElements; i++)
+     {
+        fprintf(stderr,"%u = %f \n",i,upperBodyNSRM.values[i]);
+     }
+    }
+
+    return 0;
+}
+
+