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Switched from LibSVM to ThunderSVM for better performance.

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This commit is contained in:
Emiliana 2020-08-28 01:14:48 +02:00
parent ac95537694
commit e854036e56
10 changed files with 708 additions and 61 deletions
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2
Examples/OpenSeeVRMDriver.cs
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@ -273,12 +273,10 @@ public class OpenSeeVRMDriver : MonoBehaviour {
startedSilVisemes = Time.time;
}
wasSilViseme = true;
Debug.Log("Got sil");
} else {
if (wasSilViseme)
startedSilVisemes = Time.time;
wasSilViseme = false;
Debug.Log("Not sil " + current + " " + weight);
if (hybridLipSync && Time.time - startedSilVisemes < silVisemeHybridThreshold)
ApplyMouthShape(true);
}

201
Licenses/ThunderSVM.txt Normal file
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@ -0,0 +1,201 @@
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216
Source/ThunderSVMWrapper.cpp Normal file
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@ -0,0 +1,216 @@
// ThunderSVMWrapper.cpp : Defines the exported functions for the DLL.
//
#include "pch.h"
#include "framework.h"
#include "ThunderSVMWrapper.h"
#include "thundersvm/thundersvm.h"
#include "thundersvm/model/svmmodel.h"
#include "thundersvm/model/svc.h"
#include <cmath>
using namespace std;
extern "C" void __cdecl print_log(const char *str) {
return;
}
struct problem {
int r;
int c;
DataSet::node2d x;
vector<double> y;
DataSet dataset;
};
struct SVMWrapper {
SVC *model;
int cols;
int classes;
double *means;
double *sdevs;
SvmParam param;
struct problem problem;
};
typedef struct svm_node svmnode;
void make_svmnode_array(DataSet::node2d &dataset, float features[], int rows, int cols, double *means, double *sdevs, int rescale) {
double row_factor = 1.0 / (double)rows;
if (rescale) {
for (int c = 0; c < cols; c++) {
means[c] = 0;
sdevs[c] = 0;
}
for (int r = 0; r < rows; r++) {
for (int c = 0; c < cols; c++) {
means[c] += (double)features[r * cols + c];
}
}
for (int c = 0; c < cols; c++) {
means[c] *= row_factor;
}
for (int r = 0; r < rows; r++) {
for (int c = 0; c < cols; c++) {
double sq_diff = ((double)features[r * cols + c] - means[c]);
sq_diff *= sq_diff;
sdevs[c] += sq_diff;
}
}
for (int c = 0; c < cols; c++) {
sdevs[c] *= row_factor;
sdevs[c] = sqrt(sdevs[c]);
sdevs[c] = 1.0 / sdevs[c];
}
}
for (int r = 0; r < rows; r++) {
dataset[r] = vector<DataSet::node>(cols);
int idx = 0;
for (int c = 0; c < cols; c++) {
dataset[r][c].index = c + 1;
dataset[r][c].value = (float)((features[r * cols + c] - means[c]) * sdevs[c]);
}
}
}
void make_problem(struct problem &problem, float features[], float labels[], int rows, int cols, double *means, double *sdevs) {
problem.r = rows;
problem.c = cols;
problem.y = vector<double>(rows);
for (int i = 0; i < rows; i++)
problem.y[i] = (double)labels[i];
problem.x = DataSet::node2d(rows);
make_svmnode_array(problem.x, features, rows, cols, means, sdevs, 1);
problem.dataset = DataSet(problem.x, cols, problem.y);
}
void destroy_problem(struct problem &problem) {
problem.y.clear();
problem.x.clear();
}
extern "C" {
__declspec(dllexport) void *__cdecl trainModel(float features[], float labels[], float weights[], int rows, int cols, int classes, int probability, float C) {
if (!(rows > 0 && cols > 0))
return NULL;
//svm_set_print_string_function(print_log);
struct SVMWrapper *sw = new SVMWrapper();
sw->cols = cols;
sw->classes = classes;
sw->means = new double[cols];
sw->sdevs = new double[cols];
sw->param.svm_type = SvmParam::C_SVC;
sw->param.kernel_type = SvmParam::RBF;
sw->param.degree = 3;
sw->param.gamma = 1.0 / (double)cols;
sw->param.coef0 = 0;
sw->param.nu = 0.5;
sw->param.C = C;
sw->param.epsilon = 0.001;
sw->param.p = 0.1;
sw->param.probability = probability;
sw->param.nr_weight = 0;
sw->param.weight_label = NULL;
sw->param.weight = NULL;
if (weights != NULL) {
sw->param.nr_weight = classes;
sw->param.weight_label = new int[classes];
sw->param.weight = new double[classes];
for (int i = 0; i < classes; i++) {
sw->param.weight_label[i] = i;
sw->param.weight[i] = (double)weights[i];
}
}
make_problem(sw->problem, features, labels, rows, cols, sw->means, sw->sdevs);
sw->model = new SVC();//svm_train(sw->problem, &sw->param);
sw->model->train(sw->problem.dataset, sw->param);
if (weights != NULL) {
delete sw->param.weight_label;
delete sw->param.weight;
}
return sw;
}
__declspec(dllexport) void __cdecl predict(void *ptr, float features[], float predictions[], double probabilities[], int rows) {
struct SVMWrapper *sw = (struct SVMWrapper *)ptr;
int cols = sw->cols;
DataSet::node2d instances = DataSet::node2d(rows);
make_svmnode_array(instances, features, rows, sw->cols, sw->means, sw->sdevs, 0);
vector<double> predicted = sw->model->predict(instances, -1);
instances.clear();
for (int r = 0; r < rows; r++)
predictions[r] = (float)predicted[r];
predicted.clear();
return;
}
__declspec(dllexport) void *__cdecl loadModel(char *filename, int cols, int classes, double means[], double sdevs[]) {
struct SVMWrapper *sw = new SVMWrapper();
sw->cols = cols;
sw->model = new SVC();
sw->model->load_from_file(filename);
sw->classes = classes;
sw->means = new double[cols];
sw->sdevs = new double[cols];
for (int c = 0; c < cols; c++) {
sw->means[c] = means[c];
sw->sdevs[c] = sdevs[c];
}
return sw;
}
__declspec(dllexport) void *__cdecl loadModelString(char *modelString, int cols, int classes, double means[], double sdevs[]) {
struct SVMWrapper *sw = new SVMWrapper();
sw->cols = cols;
sw->model = new SVC();
sw->model->load_from_string(modelString);
sw->classes = classes;
sw->means = new double[cols];
sw->sdevs = new double[cols];
for (int c = 0; c < cols; c++) {
sw->means[c] = means[c];
sw->sdevs[c] = sdevs[c];
}
return sw;
}
__declspec(dllexport) void __cdecl getScales(void *ptr, double means[], double sdevs[]) {
struct SVMWrapper *sw = (struct SVMWrapper *)ptr;
int cols = sw->cols;
for (int c = 0; c < cols; c++) {
means[c] = sw->means[c];
sdevs[c] = sw->sdevs[c];
}
}
__declspec(dllexport) const char *__cdecl saveModelString(void *ptr) {
struct SVMWrapper *sw = (struct SVMWrapper *)ptr;
string model = sw->model->save_to_string();
return _strdup(model.c_str());
}
__declspec(dllexport) int __cdecl saveModel(void *ptr, char *filename) {
struct SVMWrapper *sw = (struct SVMWrapper *)ptr;
sw->model->save_to_file(string(filename));
return 1;
}
__declspec(dllexport) void __cdecl destroyModel(void *ptr) {
struct SVMWrapper *sw = (struct SVMWrapper *)ptr;
delete sw->means;
delete sw->sdevs;
delete sw->model;
destroy_problem(sw->problem);
delete sw;
}
}

12
Unity/OpenSeeExpression.cs
View file

@ -152,6 +152,7 @@ public class OpenSeeExpression : MonoBehaviour
private string[] classLabels = null;
private int[] indices = null;
private PointSelection pointSelection;
private bool thunderSVM = false;
//private bool newModel = false;
static public void LoadSerialized(byte[] modelBytes, out Dictionary<string, List<float[]>> expressions, out SVMModel model, out string[] classLabels, out int[] indices, ref PointSelection pointSelection) {
@ -163,7 +164,10 @@ public class OpenSeeExpression : MonoBehaviour
oser = formatter.Deserialize(gzipStream) as OpenSeeExpressionRepresentation;
}
expressions = oser.expressions;
model = new SVMModel(oser.modelBytes);
if (oser.thunderSVM)
model = new ThunderSVMModel(oser.modelBytes);
else
model = new SVMModel(oser.modelBytes);
classLabels = oser.classLabels;
indices = oser.indices;
//pointSelection = oser.pointSelection;
@ -185,6 +189,7 @@ public class OpenSeeExpression : MonoBehaviour
oser.classLabels = classLabels;
oser.indices = indices;
oser.pointSelection = pointSelection;
oser.thunderSVM = true;
//oser.newModel = true;
IFormatter formatter = new BinaryFormatter();
@ -357,7 +362,7 @@ public class OpenSeeExpression : MonoBehaviour
}
ResetInfo();
expressions = new Dictionary<string, List<float[]>>();
model = new SVMModel();
model = new ThunderSVMModel();
rnd = new System.Random();
}
@ -411,7 +416,8 @@ public class OpenSeeExpression : MonoBehaviour
return false;
}
modelReady = false;
//model = new SVMModel();
if (model is SVMModel)
model = new ThunderSVMModel();
SelectPoints();
List<string> keys = new List<string>();
List<string> accuracyWarnings = new List<string>();

141
Unity/Plugins/SVMModel.cs
View file

@ -6,34 +6,61 @@ using System.Runtime.InteropServices;
using System.Runtime.Serialization;
using System.Runtime.Serialization.Formatters.Binary;
using System.Text;
using UnityEngine;
namespace OpenSee {
public class SVMModel {
#region DllImport
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl)]
private static extern System.IntPtr trainModel(float[] features, float[] labels, float[] weights, int rows, int cols, int classes, int probability, float C);
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, EntryPoint = "trainModel")]
private static extern System.IntPtr trainModelDll(float[] features, float[] labels, float[] weights, int rows, int cols, int classes, int probability, float C);
protected virtual System.IntPtr trainModel(float[] features, float[] labels, float[] weights, int rows, int cols, int classes, int probability, float C) {
Debug.Log("Training LibSVM");
return trainModelDll(features, labels, weights, rows, cols, classes, probability, C);
}
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl)]
private static extern void predict(System.IntPtr model, float[] features, [Out] float[] predictions, [Out] double[] probabilities, int rows);
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, EntryPoint = "predict")]
private static extern void predictDll(System.IntPtr model, float[] features, [Out] float[] predictions, [Out] double[] probabilities, int rows);
protected virtual void predict(System.IntPtr model, float[] features, [Out] float[] predictions, [Out] double[] probabilities, int rows) {
predictDll(model, features, predictions, probabilities, rows);
}
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
private static extern System.IntPtr loadModel([MarshalAs(UnmanagedType.LPStr)]string filename, int cols, int classes, double[] means, double[] sdevs);
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi, EntryPoint = "loadModel")]
private static extern System.IntPtr loadModelDll([MarshalAs(UnmanagedType.LPStr)]string filename, int cols, int classes, double[] means, double[] sdevs);
protected virtual System.IntPtr loadModel([MarshalAs(UnmanagedType.LPStr)]string filename, int cols, int classes, double[] means, double[] sdevs) {
return loadModelDll(filename, cols, classes, means, sdevs);
}
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
private static extern System.IntPtr loadModelString([MarshalAs(UnmanagedType.LPStr)]string modelString, int cols, int classes, double[] means, double[] sdevs);
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi, EntryPoint = "loadModelString")]
private static extern System.IntPtr loadModelStringDll([MarshalAs(UnmanagedType.LPStr)]string modelString, int cols, int classes, double[] means, double[] sdevs);
protected virtual System.IntPtr loadModelString([MarshalAs(UnmanagedType.LPStr)]string modelString, int cols, int classes, double[] means, double[] sdevs) {
Debug.Log("Loading LibSVM");
return loadModelStringDll(modelString, cols, classes, means, sdevs);
}
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl)]
private static extern void getScales(System.IntPtr model, [Out] double[] means, [Out] double[] sdevs);
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, EntryPoint = "getScales")]
private static extern void getScalesDll(System.IntPtr model, [Out] double[] means, [Out] double[] sdevs);
protected virtual void getScales(System.IntPtr model, [Out] double[] means, [Out] double[] sdevs) {
getScalesDll(model, means, sdevs);
}
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
private static extern int saveModel(System.IntPtr model, [MarshalAs(UnmanagedType.LPStr)]string filename);
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi, EntryPoint = "saveModel")]
private static extern int saveModelDll(System.IntPtr model, [MarshalAs(UnmanagedType.LPStr)]string filename);
protected virtual int saveModel(System.IntPtr model, [MarshalAs(UnmanagedType.LPStr)]string filename) {
return saveModelDll(model, filename);
}
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
private static extern string saveModelString(System.IntPtr model);
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi, EntryPoint = "saveModelString")]
private static extern string saveModelStringDll(System.IntPtr model);
protected virtual string saveModelString(System.IntPtr model) {
return saveModelStringDll(model);
}
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl)]
private static extern void destroyModel(System.IntPtr model);
[DllImport("SVMModel", CallingConvention = CallingConvention.Cdecl, EntryPoint = "destroyModel")]
private static extern void destroyModelDll(System.IntPtr model);
protected virtual void destroyModel(System.IntPtr model) {
destroyModelDll(model);
}
#endregion
private bool haveModel = false;
@ -43,51 +70,51 @@ public class SVMModel {
[Serializable]
private class SVMModelRepresentation {
private string modelString;
private int cols;
private int maxClasses;
private double[] means;
private double[] sdevs;
public string modelString;
public int cols;
public int maxClasses;
public double[] means;
public double[] sdevs;
}
static public System.IntPtr LoadSerialized(byte[] modelBytes, out int cols, out int maxClasses, bool compress) {
IFormatter formatter = new BinaryFormatter();
MemoryStream memoryStream = new MemoryStream(modelBytes);
memoryStream.Position = 0;
SVMModelRepresentation smr;
if (compress) {
using (GZipStream gzipStream = new GZipStream(memoryStream, CompressionMode.Decompress)) {
smr = formatter.Deserialize(gzipStream) as SVMModelRepresentation;
}
} else {
smr = formatter.Deserialize(memoryStream) as SVMModelRepresentation;
public System.IntPtr LoadSerialized(byte[] modelBytes, out int cols, out int maxClasses, bool compress) {
IFormatter formatter = new BinaryFormatter();
MemoryStream memoryStream = new MemoryStream(modelBytes);
memoryStream.Position = 0;
SVMModelRepresentation smr;
if (compress) {
using (GZipStream gzipStream = new GZipStream(memoryStream, CompressionMode.Decompress)) {
smr = formatter.Deserialize(gzipStream) as SVMModelRepresentation;
}
cols = smr.cols;
maxClasses = smr.maxClasses;
System.IntPtr model = loadModelString(smr.modelString, smr.cols, smr.maxClasses, smr.means, smr.sdevs);
return model;
} else {
smr = formatter.Deserialize(memoryStream) as SVMModelRepresentation;
}
cols = smr.cols;
maxClasses = smr.maxClasses;
System.IntPtr model = loadModelString(smr.modelString, smr.cols, smr.maxClasses, smr.means, smr.sdevs);
return model;
}
static public byte[] ToSerialized(System.IntPtr model, int cols, int maxClasses, bool compress) {
SVMModelRepresentation smr = new SVMModelRepresentation();
smr.cols = cols;
smr.maxClasses = maxClasses;
smr.means = new double[cols];
smr.sdevs = new double[cols];
getScales(model, smr.means, smr.sdevs);
smr.modelString = saveModelString(model);
public byte[] ToSerialized(System.IntPtr model, int cols, int maxClasses, bool compress) {
SVMModelRepresentation smr = new SVMModelRepresentation();
smr.cols = cols;
smr.maxClasses = maxClasses;
smr.means = new double[cols];
smr.sdevs = new double[cols];
getScales(model, smr.means, smr.sdevs);
smr.modelString = saveModelString(model);
IFormatter formatter = new BinaryFormatter();
MemoryStream memoryStream = new MemoryStream();
if (compress) {
using (GZipStream gzipStream = new GZipStream(memoryStream, CompressionMode.Compress)) {
formatter.Serialize(gzipStream, smr);
gzipStream.Flush();
}
} else {
formatter.Serialize(memoryStream, smr);
IFormatter formatter = new BinaryFormatter();
MemoryStream memoryStream = new MemoryStream();
if (compress) {
using (GZipStream gzipStream = new GZipStream(memoryStream, CompressionMode.Compress)) {
formatter.Serialize(gzipStream, smr);
gzipStream.Flush();
}
return memoryStream.ToArray();
} else {
formatter.Serialize(memoryStream, smr);
}
return memoryStream.ToArray();
}
public void DestroyModel() {
@ -99,7 +126,7 @@ public class SVMModel {
private void LoadModel(byte[] modelBytes, bool compress) {
DestroyModel();
model = SVMModelRepresentation.LoadSerialized(modelBytes, out cols, out maxClasses, compress);
model = LoadSerialized(modelBytes, out cols, out maxClasses, compress);
haveModel = true;
}
@ -110,7 +137,7 @@ public class SVMModel {
private byte[] SaveModel(bool compress) {
if (!haveModel)
return null;
return SVMModelRepresentation.ToSerialized(model, cols, maxClasses, compress);
return ToSerialized(model, cols, maxClasses, compress);
}
public byte[] SaveModel() {
@ -143,7 +170,9 @@ public class SVMModel {
maxClasses = max + 1;
this.cols = cols;
float start = Time.realtimeSinceStartup;
model = trainModel(features, labels, weights, rows, cols, maxClasses, probability, C);
Debug.Log("Training took: " + (Time.realtimeSinceStartup - start).ToString());
haveModel = true;
return true;

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@ -0,0 +1,71 @@
using System;
using System.Collections.Generic;
using System.IO;
using System.IO.Compression;
using System.Runtime.InteropServices;
using System.Runtime.Serialization;
using System.Runtime.Serialization.Formatters.Binary;
using System.Text;
using OpenSee;
using UnityEngine;
public class ThunderSVMModel : SVMModel {
#region DllImport
[DllImport("ThunderSVMWrapper", CallingConvention = CallingConvention.Cdecl, EntryPoint = "trainModel")]
private static extern System.IntPtr trainModelDll(float[] features, float[] labels, float[] weights, int rows, int cols, int classes, int probability, float C);
protected override System.IntPtr trainModel(float[] features, float[] labels, float[] weights, int rows, int cols, int classes, int probability, float C) {
Debug.Log("Training ThunderSVM");
return trainModelDll(features, labels, weights, rows, cols, classes, probability, C);
}
[DllImport("ThunderSVMWrapper", CallingConvention = CallingConvention.Cdecl, EntryPoint = "predict")]
private static extern void predictDll(System.IntPtr model, float[] features, [Out] float[] predictions, [Out] double[] probabilities, int rows);
protected override void predict(System.IntPtr model, float[] features, [Out] float[] predictions, [Out] double[] probabilities, int rows) {
predictDll(model, features, predictions, probabilities, rows);
}
[DllImport("ThunderSVMWrapper", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi, EntryPoint = "loadModel")]
private static extern System.IntPtr loadModelDll([MarshalAs(UnmanagedType.LPStr)]string filename, int cols, int classes, double[] means, double[] sdevs);
protected override System.IntPtr loadModel([MarshalAs(UnmanagedType.LPStr)]string filename, int cols, int classes, double[] means, double[] sdevs) {
return loadModelDll(filename, cols, classes, means, sdevs);
}
[DllImport("ThunderSVMWrapper", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi, EntryPoint = "loadModelString")]
private static extern System.IntPtr loadModelStringDll([MarshalAs(UnmanagedType.LPStr)]string modelString, int cols, int classes, double[] means, double[] sdevs);
protected override System.IntPtr loadModelString([MarshalAs(UnmanagedType.LPStr)]string modelString, int cols, int classes, double[] means, double[] sdevs) {
Debug.Log("Loading ThunderSVM");
return loadModelStringDll(modelString, cols, classes, means, sdevs);
}
[DllImport("ThunderSVMWrapper", CallingConvention = CallingConvention.Cdecl, EntryPoint = "getScales")]
private static extern void getScalesDll(System.IntPtr model, [Out] double[] means, [Out] double[] sdevs);
protected override void getScales(System.IntPtr model, [Out] double[] means, [Out] double[] sdevs) {
getScalesDll(model, means, sdevs);
}
[DllImport("ThunderSVMWrapper", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi, EntryPoint = "saveModel")]
private static extern int saveModelDll(System.IntPtr model, [MarshalAs(UnmanagedType.LPStr)]string filename);
protected override int saveModel(System.IntPtr model, [MarshalAs(UnmanagedType.LPStr)]string filename) {
return saveModelDll(model, filename);
}
[DllImport("ThunderSVMWrapper", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi, EntryPoint = "saveModelString")]
private static extern string saveModelStringDll(System.IntPtr model);
protected override string saveModelString(System.IntPtr model) {
return saveModelStringDll(model);
}
[DllImport("ThunderSVMWrapper", CallingConvention = CallingConvention.Cdecl, EntryPoint = "destroyModel")]
private static extern void destroyModelDll(System.IntPtr model);
protected override void destroyModel(System.IntPtr model) {
destroyModelDll(model);
}
#endregion
public ThunderSVMModel() {
}
public ThunderSVMModel(byte[] modelBytes) {
LoadModel(modelBytes);
}
}

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