static async Task MainAsync(string[] args)
{
/* you need at least 2 tags and 5 images for each tag to start*/
//generate random name for the project
var projectName = Guid.NewGuid().ToString();
Console.WriteLine($"\tCreating a project in customvision.ai - project name: {projectName}");
var project = CreateProject(projectName);
var basepath = Directory.GetCurrentDirectory();
//read tags
var tsgfilepath = $"{basepath}\\tags.csv";
Console.WriteLine($"\tReading Tags from {tsgfilepath}");
var tags = ReadTags(tsgfilepath);
//download images -
var trainingSetPath = $"{basepath}\\{projectName}\\data\\TrainingSet";
var testSetPath = $"{basepath}\\{projectName}\\data\\TestSet";
Console.WriteLine($"\tBing search & downloading images - split them in TrainingSet & TestSet for each tag");
Console.WriteLine($"\tTrainingSetPath: {trainingSetPath}");
Console.WriteLine($"\tTestSetPath: {testSetPath}");
System.IO.Directory.CreateDirectory(trainingSetPath);
System.IO.Directory.CreateDirectory(testSetPath);
int minTrainingPhotosCount = 5;
int minTestPhotosCount = 3;
foreach (var tag in tags)
{
{
using (var bingImageSearchService = new BingImageSearchService())
{
Console.WriteLine($"\tStarting the Process for : {tag}");
var bingresult = await bingImageSearchService.ImageSearch(tag, 20);
if (bingresult.value == null)
{
return;
}
//training
Console.WriteLine($"\tDownloading the training set");
var trainingphotos = DownloadImages($"{trainingSetPath}\\{tag}", bingresult.value.ToList(), minTrainingPhotosCount);
//test
Console.WriteLine($"\tDownloading the test set");
var testphotos = DownloadImages($"{testSetPath}\\{tag}", bingresult.value.Skip(trainingphotos).ToList(), minTestPhotosCount);
if (trainingphotos < minTrainingPhotosCount || testphotos < minTestPhotosCount)
{
throw new Exception($"Bing couldn't find required images.you need at least 2 tags and 5 images for each tag to start");
}
}
}
}
CreateTheModel(trainingSetPath, project);
// Now there are images with tags start training the project
TrainTheModel(project);
Console.WriteLine($"\tTesting the Model");
TestingTheModel(testSetPath, project);
}
static async Task MainAsync(string[] args)
{
/* you need at least 2 tags and 5 images for each tag to start*/
var basepath = Directory.GetCurrentDirectory();
//read tags
var tsgfilepath = $"{basepath}\\tags.csv";
Console.WriteLine($"\tReading Tags from {tsgfilepath}");
var tags = ReadTags(tsgfilepath);
//generate random name for the project
var projectName = tags.Count == 2 ? $"{tags[0]} {tags[1]} classifier {DateTime.Now:yyyyMMddHHmm}" : DateTime.Now.ToString("yyyyMMddHHmm");
Console.WriteLine($"\tCreating a project in customvision.ai - project name: {projectName}");
var project = CreateProject(projectName);
//download images -
var imagesresouce = $"{basepath}\\{projectName}\\data\\";
var trainingSetPath = $"{imagesresouce}TrainingSet";
var testSetPath = $"{imagesresouce}TestSet";
Console.WriteLine($"\tBing search & downloading images - split them in TrainingSet & TestSet for each tag");
Console.WriteLine($"\tTrainingSetPath: {trainingSetPath}");
Console.WriteLine($"\tTestSetPath: {testSetPath}");
System.IO.Directory.CreateDirectory(trainingSetPath);
System.IO.Directory.CreateDirectory(testSetPath);
var minTrainingPhotosCount = int.Parse(ConfigurationManager.AppSettings["TrainingImagesCount"]);
var minTestPhotosCount = int.Parse(ConfigurationManager.AppSettings["TestImagesCount"]);
var sizeOfImageSet = (minTrainingPhotosCount + minTestPhotosCount) * 3;
var augmentTrainingImages = bool.Parse(ConfigurationManager.AppSettings["AugmentTrainingImages"]);
foreach (var tag in tags)
{
{
using (var bingImageSearchService = new BingImageSearchService())
{
Console.WriteLine($"\tStarting the Process for : {tag}");
var bingresult = await bingImageSearchService.ImageSearch(tag, sizeOfImageSet);
if (bingresult.value == null)
{
return;
}
//
using (var writer = new StreamWriter($"{imagesresouce}\\{tag}_resource.csv"))
{
using (var csvWriter = new CsvWriter(writer))
{
csvWriter.WriteRecords(bingresult.value);
}
}
var randomize = bool.Parse(ConfigurationManager.AppSettings["Randomize"]);
var imageList = bingresult.value.ToList();
if (randomize)
{
imageList.Shuffle();
}
//training
Console.WriteLine($"\tDownloading the training set");
var trainingphotos = await DownloadImagesAsync($"{trainingSetPath}\\{tag}", imageList, minTrainingPhotosCount, augmentTrainingImages);
//test
Console.WriteLine($"\tDownloading the test set");
var testphotos = await DownloadImagesAsync($"{testSetPath}\\{tag}", imageList.Skip(trainingphotos).ToList(), minTestPhotosCount);
if (trainingphotos < minTrainingPhotosCount || testphotos < minTestPhotosCount)
{
throw new Exception($"Bing couldn't find required images.you need at least 2 tags and 5 images for each tag to start");
}
}
}
}
CreateTheModel(trainingSetPath, project);
// Now there are images with tags start training the project
TrainTheModel(project);
Console.WriteLine($"\tTesting the Model");
TestingTheModel(testSetPath, project);
}
static async Task MainAsync(string[] args)
{
/* you need at least 2 tags and 5 images for each tag to start*/
var basepath = Directory.GetCurrentDirectory();
//read tags
var tsgfilepath = $"{basepath}\\tags.csv";
Console.WriteLine($"\tReading Tags from {tsgfilepath}");
var tags = ReadTags(tsgfilepath);
//generate random name for the project if projectname isn't passed in
string projectName = string.Empty;
try
{
projectName = ConfigurationManager.AppSettings["ProjectName"];
}
catch { }
if (projectName == string.Empty)
{
projectName = tags.Count == 2 ? $"{tags[0]} {tags[1]} classifier {DateTime.Now:yyyyMMddHHmm}" : DateTime.Now.ToString("yyyyMMddHHmm");
}
Console.WriteLine($"\tCreating or returning project in customvision.ai - project name: {projectName}");
var project = CreateProject(projectName);
//download images -
var imagesresouce = $"{basepath}\\{projectName}\\data\\";
var trainingSetPath = $"{imagesresouce}TrainingSet";
var testSetPath = $"{imagesresouce}TestSet";
Console.WriteLine($"\tBing search & downloading images - split them in TrainingSet & TestSet for each tag");
Console.WriteLine($"\tTrainingSetPath: {trainingSetPath}");
Console.WriteLine($"\tTestSetPath: {testSetPath}");
try {
// create the directory if it doesn't already exist
System.IO.Directory.CreateDirectory(trainingSetPath);
}
catch { }
try
{
// create the directory if it doesn't already exist
System.IO.Directory.CreateDirectory(testSetPath);
}
catch { }
int sizeOfImageSet = 10;
try
{
sizeOfImageSet = Convert.ToInt16(ConfigurationManager.AppSettings["SizeOfImageSet"]); //recommend 100
}
catch { }
bool PerformImageDownload = true;
try
{
PerformImageDownload = Convert.ToBoolean(ConfigurationManager.AppSettings["PerformImageDownload"]);
}
catch { }
if (PerformImageDownload)
{
foreach (var tag in tags)
{
{
using (var bingImageSearchService = new BingImageSearchService())
{
Console.WriteLine($"\tStarting the Process for : {tag}");
string tagResource = $"{imagesresouce}\\{tag}_resource.csv";
try
{
// if it exists from a previous run delete it
System.IO.File.Delete(tagResource);
}
catch { }
var bingresult = await bingImageSearchService.ImageSearch(tag, sizeOfImageSet);
if (bingresult.value == null)
{
return;
}
//
using (var writer = new StreamWriter(tagResource))
{
using (var csvWriter = new CsvWriter(writer))
{
csvWriter.WriteRecords(bingresult.value);
}
}
Console.WriteLine($"\tDownloading the training and test set");
var trainingphotos = DownloadImages(projectName, tag, bingresult.value.ToList(), sizeOfImageSet);
}
}
}
}
bool TrainModel = true;
try
{
TrainModel = Convert.ToBoolean(ConfigurationManager.AppSettings["TrainModel"]);
}
catch { }
if (TrainModel)
{
Console.WriteLine($"\tCreating the Model");
CreateTheModel(trainingSetPath, project);
// Now there are images with tags start training the project
TrainTheModel(project);
}
bool TestModel = true;
try
{
TestModel = Convert.ToBoolean(ConfigurationManager.AppSettings["TestModel"]);
}
catch { }
if (TestModel)
{
Console.WriteLine($"\tTesting the Model");
TestingTheModel(testSetPath, project);
}
}
