Sean/CNNImageProcessor
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Code cleanup

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Sean
2026-03-12 21:17:40 -04:00
parent 013af819cd
commit 56d26795da
1 changed files with 37 additions and 13 deletions
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50
Program.cs
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@@ -63,7 +63,7 @@ namespace CNNImageProcessor
/// </summary> /// </summary>
/// <param name="sourcePath"></param> /// <param name="sourcePath"></param>
/// <param name="destinationPath"></param> /// <param name="destinationPath"></param>
public static bool ProcessImages(String sourcePath, String destinationPath,int resizeTo,String cnnClientUrl="http://10.0.0.73:5000") public static bool ProcessImages(String sourcePath, String destinationPath,int resizeTo,String cnnClientUrl="http://10.0.0.73:5000",bool useGrayScale=false)
{ {
String[] files = Directory.GetFiles(sourcePath,"*.jpg"); String[] files = Directory.GetFiles(sourcePath,"*.jpg");
@@ -78,7 +78,7 @@ namespace CNNImageProcessor
Console.WriteLine($"Processing {file}"); Console.WriteLine($"Processing {file}");
ImageHelper imageHelper=new ImageHelper(); ImageHelper imageHelper=new ImageHelper();
imageHelper.LoadImage(file); imageHelper.LoadImage(file);
// imageHelper.ToGrayScale(); if(useGrayScale)imageHelper.ToGrayScale();
imageHelper.Resize(resizeTo,resizeTo); imageHelper.Resize(resizeTo,resizeTo);
Stream stream = imageHelper.ToStream(); Stream stream = imageHelper.ToStream();
Stream processed = cnnClient.ProcessImage(stream); Stream processed = cnnClient.ProcessImage(stream);
@@ -314,10 +314,41 @@ namespace CNNImageProcessor
outStream.Dispose(); outStream.Dispose();
} }
//public static (List<Holding> avoid, List<Holding> good) GenerateCodeTestCases(List<Holding> universe)
//{
// double validationPercent=0.05;
// double validationPercentUnseen=0.50;
// Console.WriteLine($"Read {universe.Count} holdings");
// List<Holding> avoid = universe.Where(x=>x.GainLoss<-.05).ToList();
// List<Holding> good=universe.Where(x=>x.GainLoss>.05).ToList();
// int validationCount = (int)(validationPercent * universe.Count);
// Random rng = new Random();
// List<Holding> goodValidation = good.OrderBy(x => rng.Next()).Take(validationCount).ToList();
// int goodUnseenCount = (int)(validationPercentUnseen * goodValidation.Count);
// List<Holding> goodValidationUnseen = goodValidation.OrderBy(x => rng.Next()).Take(goodUnseenCount).ToList();
// good.RemoveAll(x => goodValidationUnseen.Contains(x));
// Console.WriteLine($"Validation sample size: {goodValidation.Count}");
// Console.WriteLine($"Unseen validation removed from good: {goodValidationUnseen.Count}");
// Console.WriteLine($"Remaining good count: {good.Count}");
// List<Holding> avoidValidation = avoid.OrderBy(x => rng.Next()).Take(validationCount).ToList();
// int avoidUnseenCount = (int)(validationPercentUnseen * avoidValidation.Count);
// List<Holding> avoidValidationUnseen = avoidValidation.OrderBy(x => rng.Next()).Take(avoidUnseenCount).ToList();
// avoid.RemoveAll(x => avoidValidationUnseen.Contains(x));
// Console.WriteLine($"Validation sample size: {avoidValidation.Count}");
// Console.WriteLine($"Unseen validation removed from avoid: {avoidValidationUnseen.Count}");
// Console.WriteLine($"Remaining avoid count: {avoid.Count}");
// return (avoid, good);
//}
public static (List<Holding> avoid, List<Holding> good) GenerateCodeTestCases(List<Holding> universe) public static (List<Holding> avoid, List<Holding> good) GenerateCodeTestCases(List<Holding> universe)
{ {
double validationPercent=0.05; double validationPercent=0.05;
double validationPercentUnseen=0.50;
Console.WriteLine($"Read {universe.Count} holdings"); Console.WriteLine($"Read {universe.Count} holdings");
List<Holding> avoid = universe.Where(x=>x.GainLoss<-.05).ToList(); List<Holding> avoid = universe.Where(x=>x.GainLoss<-.05).ToList();
@@ -327,25 +358,18 @@ namespace CNNImageProcessor
Random rng = new Random(); Random rng = new Random();
List<Holding> goodValidation = good.OrderBy(x => rng.Next()).Take(validationCount).ToList(); List<Holding> goodValidation = good.OrderBy(x => rng.Next()).Take(validationCount).ToList();
int goodUnseenCount = (int)(validationPercentUnseen * goodValidation.Count);
List<Holding> goodValidationUnseen = goodValidation.OrderBy(x => rng.Next()).Take(goodUnseenCount).ToList();
good.RemoveAll(x => goodValidationUnseen.Contains(x));
Console.WriteLine($"Validation sample size: {goodValidation.Count}"); Console.WriteLine($"Validation sample size: {goodValidation.Count}");
Console.WriteLine($"Unseen validation removed from good: {goodValidationUnseen.Count}");
Console.WriteLine($"Remaining good count: {good.Count}"); Console.WriteLine($"Remaining good count: {good.Count}");
List<Holding> avoidValidation = avoid.OrderBy(x => rng.Next()).Take(validationCount).ToList(); List<Holding> avoidValidation = avoid.OrderBy(x => rng.Next()).Take(validationCount).ToList();
int avoidUnseenCount = (int)(validationPercentUnseen * avoidValidation.Count);
List<Holding> avoidValidationUnseen = avoidValidation.OrderBy(x => rng.Next()).Take(avoidUnseenCount).ToList();
avoid.RemoveAll(x => avoidValidationUnseen.Contains(x));
Console.WriteLine($"Validation sample size: {avoidValidation.Count}"); Console.WriteLine($"Validation sample size: {avoidValidation.Count}");
Console.WriteLine($"Unseen validation removed from avoid: {avoidValidationUnseen.Count}");
Console.WriteLine($"Remaining avoid count: {avoid.Count}"); Console.WriteLine($"Remaining avoid count: {avoid.Count}");
return (avoid, good); return (avoid, good);
} }
public static void GenerateTrainingImages(List<Holding> avoid, List<Holding> good) public static void GenerateTrainingImages(List<Holding> avoid, List<Holding> good)
{ {
String cnnClientUrl="http://127.0.0.1:5000"; String cnnClientUrl="http://127.0.0.1:5000";
@@ -361,8 +385,8 @@ namespace CNNImageProcessor
Console.WriteLine($"CNN Server @ {cnnClientUrl} is not responding."); Console.WriteLine($"CNN Server @ {cnnClientUrl} is not responding.");
return; return;
} }
ProcessImages(@"C:\boneyard\DeepLearning\ModelInputData\0",@"C:\boneyard\DeepLearning\Data\0",imageSize,cnnClientUrl); // Process through PIL and put in C:\boneyard\DeepLearning\Data\0 ProcessImages(@"C:\boneyard\DeepLearning\ModelInputData\0",@"C:\boneyard\DeepLearning\Data\0",imageSize,cnnClientUrl,false); // Process through PIL and put in C:\boneyard\DeepLearning\Data\0
ProcessImages(@"C:\boneyard\DeepLearning\ModelInputData\1",@"C:\boneyard\DeepLearning\Data\1",imageSize,cnnClientUrl); // Process through PIL and put in C:\boneyard\DeepLearning\Data\1 ProcessImages(@"C:\boneyard\DeepLearning\ModelInputData\1",@"C:\boneyard\DeepLearning\Data\1",imageSize,cnnClientUrl,false); // Process through PIL and put in C:\boneyard\DeepLearning\Data\1
Console.WriteLine("Done."); Console.WriteLine("Done.");
} }