public bool Decide()
{
// Get list of files in folders
String[] files = Testing.GetFilesFromDirectory(decidePath).ToArray();
string csvPath = userPath + "\\Decide.txt";
string resultPath = userPath + "\\Result.txt";
for (int i = 0; i < files.Length; i++)
{
System.IO.StreamWriter file = new System.IO.StreamWriter(@csvPath, false);
ImageVector vec = new ImageVector(files[i], null);
file.WriteLine(vec.getAllParameters(false));
file.Close();
MLApp.MLApp matlab = new MLApp.MLApp();
string cd = "cd C:\\Users\\anoach\\Desktop\\papa_matlab";
//string exe = "albumSvm('" + userPath + "');";
string exe = "albumKnn('" + userPath + "', " + 1 + ");"; //K = 1
matlab.Execute(cd);
matlab.Execute(exe);
string[] readText = File.ReadAllLines(resultPath);
if (readText[0] == "1")
{
Console.WriteLine("Good Image");
}
else
{
Console.WriteLine("Bad Image. Delete it");
File.Delete(files[i]);
}
}
return true;
}
/// <summary>
/// predicts for all images in folder if true or false
/// </summary>
/// <param name="folder">path to folder with images to predict</param>
/// <param name="res">keeps for each image if true or falde</param>
/// <returns>true if decision was successful. else false.</returns>
public bool Decide(string folder, out double [] res)
{
res = null;
// Get list of files in folders
String[] files;
try
{
files = Testing.GetFilesFromDirectory(folder).ToArray();//Directory.GetFiles(folder);
}
catch (Exception exc)
{
MessageBox.Show(exc.Message);
return false;
}
DecisionListcount = 0;
String[] cVectors= new string[files.Length];
List<ImageVector> vectors = new List<ImageVector>();
for(int i = 0; i < files.Length; i++)
{
string path = "C:\\Users\\anoach\\Desktop\\PAPA\\csv"+i+".txt";
System.IO.StreamWriter file = new System.IO.StreamWriter(@path, true);
//get imageVectors
ImageVector vec = new ImageVector(files[i], ParameterList);
vectors.Add(new ImageVector(vec));
//Convert to clasiffied vector
DecisionListcount++;
file.WriteLine(vec.getAllParameters(false));
file.Close();
}
double[] results;
//load algorithm data and predict
//if (!_algorithm.LoadData())
//{
// return false;
//}
if (!Algorithm.Predict(vectors, out results))
return false;
res = results;
return true;
}
public bool Learn(string folderAll, string folderTrue)
{
// Get list of files in folders
string[] filesAll = Testing.GetFilesFromDirectory(folderAll).ToArray();//Directory.GetFiles(folderAll);
string[] filesTrue = Testing.GetFilesFromDirectory(folderTrue).ToArray(); //Directory.GetFiles(folderTrue);
if (filesAll.Length <= 0)
return false;
// Make False vector list
int index=0;
string[] filesFalse = new string[filesAll.Length - filesTrue.Length];
bool exist;
string fn_all, fn_true;
for (int i = 0; i < filesAll.Length; i++)
{
fn_all = filesAll[i].Substring(filesAll[i].LastIndexOf("\\")+1);
exist = false;
for (int j = 0; j < filesTrue.Length; j++)
{
fn_true = filesTrue[j].Substring(filesTrue[j].LastIndexOf("\\") + 1);
if (fn_true.Equals(fn_all))
{
exist = true;
break;
}
}
if (exist)
continue;
filesFalse[index++] = filesAll[i];
}
// Convert to vector List
List<ImageVector> vectorsTrue = new List<ImageVector>();
List<ImageVector> vectorsFalse = new List<ImageVector>();
List<ImageVector> newTrue = new List<ImageVector>();
List<ImageVector> newFalse = new List<ImageVector>();
Listcount = 0;
_repository.loadList();
System.IO.StreamWriter file = new System.IO.StreamWriter(@"C:\Users\anoach\Desktop\PAPA\csv.txt", true);
foreach (string path in filesTrue)
{
ImageVector existing = _repository.getVectorByPath(path);
if (existing != null)
{
vectorsTrue.Add(new ImageVector(existing));
file.WriteLine(existing.getAllParameters(true));
}
else
{
ImageVector vec = new ImageVector(path, _parameterList);
vectorsTrue.Add(new ImageVector(vec));
newTrue.Add(vec);
file.WriteLine(vec.getAllParameters(true));
}
Listcount++;
}
foreach (string path in filesFalse)
{
ImageVector existing = _repository.getVectorByPath(path);
if (existing != null)
{
vectorsFalse.Add(new ImageVector(existing));
file.WriteLine(existing.getAllParameters(false));
}
else
{
ImageVector vec = new ImageVector(path, _parameterList);
vectorsFalse.Add(new ImageVector(vec));
newFalse.Add(vec);
file.WriteLine(vec.getAllParameters(false));
}
Listcount++;
}
file.Close();
// Push new vectors to repository (Only vectors that was not on the repository)
_repository.AddToList(newTrue, newFalse);
// Push vectors to algorithm (Learn by given pictures only)
bool success = _algorithm.Train(vectorsTrue, vectorsFalse);
return success;
}
private bool Internal_DecideImage(MLApp.MLApp matlab, ImageVector image, int algo)
{
string csvPathDecide = userPath + "\\Decide.txt";
string resultPath = userPath + "\\Result.txt";
System.IO.StreamWriter file = new System.IO.StreamWriter(@csvPathDecide, false);
file.WriteLine(image.getAllParameters(false));
file.Close();
string command = Internal_GetCommand(algo);
matlab.Execute(command);
string[] readText = File.ReadAllLines(resultPath);
if (readText[0] == "0")
return false;
return true;
}
public bool Learn()
{
// Get list of files in folders
string[] filesAll = Testing.GetFilesFromDirectory(allPath).ToArray();
string[] filesTrue = Testing.GetFilesFromDirectory(truePath).ToArray();
if (filesAll.Length <= 0 || filesTrue.Length <= 0)
return false;
// Make False vector list - All the files in all that are not in true.
int index = 0;
string[] filesFalse = new string[filesAll.Length - filesTrue.Length];
bool exist;
string fn_all, fn_true;
for (int i = 0; i < filesAll.Length; i++)
{
fn_all = filesAll[i].Substring(filesAll[i].LastIndexOf("\\") + 1);
exist = false;
for (int j = 0; j < filesTrue.Length; j++)
{
fn_true = filesTrue[j].Substring(filesTrue[j].LastIndexOf("\\") + 1);
if (fn_true.Equals(fn_all))
{
exist = true;
break;
}
}
if (exist)
continue;
filesFalse[index++] = filesAll[i];
}
string csvPath = userPath + "\\Learn.txt";
System.IO.StreamWriter file = new System.IO.StreamWriter(@csvPath, true);
// Convert to vector List
foreach (string path in filesTrue)
{
ImageVector vec = new ImageVector(path, null);
file.WriteLine(vec.getAllParameters(true));
}
foreach (string path in filesFalse)
{
ImageVector vec = new ImageVector(path, null);
file.WriteLine(vec.getAllParameters(false));
}
file.Close();
MLApp.MLApp matlab = new MLApp.MLApp();
string cd = "cd C:\\Users\\anoach\\Desktop\\papa_matlab";
string exe = "albumLearn('" + userPath + "');";
matlab.Execute(cd);
matlab.Execute(exe);
return true;
}
private bool Internal_DecideImage(MLApp.MLApp matlab, ImageVector image, int algo)
{
string csvPathDecide = userPath + "\\Decide.txt";
int result = 0;
System.IO.StreamWriter file = new System.IO.StreamWriter(@csvPathDecide, false);
file.WriteLine(image.getAllParameters(false));
file.Close();
string commandBestKnn = Internal_GetCommand(2);
string commandBestSvm = Internal_GetCommand(10);
if (algo != 1)
{
matlab.Execute(commandBestKnn);
result += Internal_GetResult();
}
if (algo != 0)
{
matlab.Execute(commandBestSvm);
result += Internal_GetResult();
}
if (result == 2)
return true;
if ((algo != 2) && (result == 1))
return true;
return false;
}
/*
* copy imageVector into a file
*/
public static void convertImageVectorToFile(string path, ImageVector image)
{
string algoPath = path;
string csvPathDecide = algoPath + "\\Decide.txt";
System.IO.StreamWriter file = new System.IO.StreamWriter(@csvPathDecide, false);
file.WriteLine(image.getAllParameters(false));
file.Close();
}
