public GetClassifiersPerClassifierVerbose GetClassifier(string classifierId)
{
if (string.IsNullOrEmpty(classifierId))
{
throw new ArgumentNullException(nameof(classifierId));
}
GetClassifiersPerClassifierVerbose result = null;
try
{
result = this.Client.GetAsync($"{this.Endpoint}{string.Format(PATH_CLASSIFIER, classifierId)}")
.WithArgument("api_key", ApiKey)
.WithArgument("version", VERSION_DATE_2016_05_20)
.WithFormatter(new MediaTypeHeaderValue("application/octet-stream"))
.As <GetClassifiersPerClassifierVerbose>()
.Result;
}
catch (AggregateException ae)
{
throw ae.Flatten();
}
return(result);
}
private void OnTrainClassifier(GetClassifiersPerClassifierVerbose classifier, string data)
{
Log.Debug("ExampleVisualRecognition", "VisualRecognition - TrainClassifier Response: {0}", data);
#if DELETE_TRAINED_CLASSIFIER
_classifierToDelete = classifier.classifier_id;
#endif
_trainClassifierTested = true;
}
public GetClassifiersPerClassifierVerbose CreateClassifier(string classifierName, Dictionary <string, byte[]> positiveExamplesData, byte[] negativeExamplesData = null)
{
GetClassifiersPerClassifierVerbose result = null;
if (string.IsNullOrEmpty(classifierName))
{
throw new ArgumentNullException(nameof(classifierName));
}
if (positiveExamplesData == null)
{
throw new ArgumentNullException(nameof(positiveExamplesData));
}
if (positiveExamplesData.Count < 2 && negativeExamplesData == null)
{
throw new ArgumentNullException("Training a Visual Recognition classifier requires at least two positive example files or one positive example and negative example file.");
}
try
{
var formData = new MultipartFormDataContent();
foreach (var kvp in positiveExamplesData)
{
var positiveExampleDataContent = new ByteArrayContent(kvp.Value);
positiveExampleDataContent.Headers.ContentType = MediaTypeHeaderValue.Parse("application/zip");
formData.Add(positiveExampleDataContent, string.Format("{0}_positive_examples", kvp.Key), string.Format("{0}_positive_examples.zip", kvp.Key));
}
if (negativeExamplesData != null)
{
var negativeExamplesDataContent = new ByteArrayContent(negativeExamplesData);
negativeExamplesDataContent.Headers.ContentType = MediaTypeHeaderValue.Parse("application/zip");
formData.Add(negativeExamplesDataContent, "negative_examples", "negative_examples.zip");
}
var nameDataContent = new StringContent(classifierName, Encoding.UTF8, HttpMediaType.TEXT_PLAIN);
nameDataContent.Headers.ContentType = MediaTypeHeaderValue.Parse("application/json");
formData.Add(nameDataContent, "name");
result = this.Client.PostAsync($"{ this.Endpoint}{PATH_CLASSIFIERS}")
.WithArgument("version", VERSION_DATE_2016_05_20)
.WithArgument("api_key", ApiKey)
.WithBodyContent(formData)
.WithFormatter(new MediaTypeHeaderValue("application/octet-stream"))
.As <GetClassifiersPerClassifierVerbose>()
.Result;
}
catch (AggregateException ae)
{
throw ae.Flatten();
}
return(result);
}
private void OnTrainClassifier(GetClassifiersPerClassifierVerbose classifier, Dictionary <string, object> customData)
{
Log.Debug("ExampleVisualRecognition.OnTrainClassifier()", "{0}", customData["json"].ToString());
#if DELETE_TRAINED_CLASSIFIER
_classifierToDelete = classifier.classifier_id;
#endif
_classifierID = classifier.classifier_id;
_trainClassifierTested = true;
}
private void OnGetClassifier(GetClassifiersPerClassifierVerbose classifier)
{
Test(classifier != null);
if (classifier != null)
{
Log.Debug("TestVisualRecognition", "Classifier {0} found! Classifier name: {1}", classifier.classifier_id, classifier.name);
}
m_GetClassifierTested = true;
}
private void OnTrainClassifier(GetClassifiersPerClassifierVerbose classifier, string data)
{
if (classifier != null)
{
Log.Debug("ExampleVisualRecognition", "Classifier is training! " + classifier);
}
else
{
Log.Debug("ExampleVisualRecognition", "Failed to train classifier!");
}
}
private void OnGetClassifier(GetClassifiersPerClassifierVerbose classifier, string data)
{
if (classifier != null)
{
Log.Debug("ExampleVisualRecognition", "Classifier " + m_classifierID + " found! Classifier name: " + classifier.name);
}
else
{
Log.Debug("ExampleVisualRecognition", "Failed to find classifier by ID!");
}
}
private void OnFindClassifier(GetClassifiersPerClassifierVerbose classifier, string data)
{
if (classifier != null)
{
Log.Debug("ExampleVisualRecognition", "Classifier " + m_classifierName + " found! ClassifierID: " + classifier.classifier_id);
}
else
{
Log.Debug("ExampleVisualRecognition", "Failed to find classifier by name!");
}
}
private void OnDeleteClassifierFinal(GetClassifiersPerClassifierVerbose classifier)
{
if (classifier == null)
{
Log.Debug("TestVisualRecognition", "Classifier not found! Delete sucessful!");
}
else
{
Log.Debug("TestVisualRecognition", "Classifier {0} found! Delete failed!", classifier.name);
}
}
private void OnTrainClassifier(GetClassifiersPerClassifierVerbose classifier, string customData)
{
Test(classifier != null);
if (classifier != null)
{
Log.Status("TestVisualRecognition", "Classifier ID: {0}, Classifier name: {1}, Status: {2}", classifier.classifier_id, classifier.name, classifier.status);
// store classifier id
m_ClassifierId = classifier.classifier_id;
}
m_TrainClasifierTested = true;
}
private bool ContainsClass(GetClassifiersPerClassifierVerbose result, string classname)
{
bool containsClass = false;
foreach (ModelClass _class in result.Classes)
{
if (_class._Class == classname)
containsClass = true;
}
return containsClass;
}
private void OnCheckUpdatedClassifierStatus(GetClassifiersPerClassifierVerbose classifier, string customData = default(string))
{
Log.Debug("TestVisualRecognition", "classifier {0} is {1}!", classifier.classifier_id, classifier.status);
if (classifier.status == "retraining")
{
CheckClassifierStatus(OnCheckUpdatedClassifierStatus);
}
else if (classifier.status == "ready")
{
m_IsUpdatedClassifierReady = true;
}
}
public GetClassifiersPerClassifierVerbose UpdateClassifier(string classifierId, Dictionary <string, byte[]> positiveExamplesData = null, byte[] negativeExamplesData = null)
{
GetClassifiersPerClassifierVerbose result = null;
if (string.IsNullOrEmpty(classifierId))
{
throw new ArgumentNullException(nameof(classifierId));
}
if (positiveExamplesData == null && negativeExamplesData == null)
{
throw new ArgumentNullException("Positive example data and/or negative example data are required to update a classifier.");
}
try
{
var formData = new MultipartFormDataContent();
if (positiveExamplesData != null)
{
foreach (var kvp in positiveExamplesData)
{
var positiveExampleDataContent = new ByteArrayContent(kvp.Value);
positiveExampleDataContent.Headers.ContentType = MediaTypeHeaderValue.Parse("application/zip");
formData.Add(positiveExampleDataContent, string.Format("{0}_positive_examples", kvp.Key), string.Format("{0}_positive_examples.zip", kvp.Key));
}
}
if (negativeExamplesData != null)
{
var negativeExamplesDataContent = new ByteArrayContent(negativeExamplesData);
negativeExamplesDataContent.Headers.ContentType = MediaTypeHeaderValue.Parse("application/zip");
formData.Add(negativeExamplesDataContent, "negative_examples", "negative_examples.zip");
}
result = this.Client.PostAsync($"{ this.Endpoint}{string.Format(PATH_CLASSIFIER, classifierId)}")
.WithArgument("version", VERSION_DATE_2016_05_20)
.WithArgument("api_key", ApiKey)
.WithBodyContent(formData)
.WithFormatter(new MediaTypeHeaderValue("application/octet-stream"))
.As <GetClassifiersPerClassifierVerbose>()
.Result;
}
catch (AggregateException ae)
{
throw ae.Flatten();
}
return(result);
}
private void OnGetClassifier(GetClassifiersPerClassifierVerbose classifier, string customData)
{
Test(classifier != null);
if (classifier != null)
{
Log.Debug("TestVisualRecognition", "Classifier {0} found! Classifier name: {1}", classifier.classifier_id, classifier.name);
foreach (Class classifierClass in classifier.classes)
{
if (classifierClass.m_Class == m_ClassName_Turtle)
{
m_HasUpdatedClassifier = true;
}
}
}
m_GetClassifierTested = true;
}
private void OnUpdateClassifier(GetClassifiersPerClassifierVerbose classifier, string customData)
{
if (classifier != null)
{
Log.Status("TestVisualRecognition", "Classifier ID: {0}, Classifier name: {1}, Status: {2}", classifier.classifier_id, classifier.name, classifier.status);
foreach (Class classifierClass in classifier.classes)
{
if (classifierClass.m_Class == m_ClassName_Turtle)
{
m_HasUpdatedClassifier = true;
}
}
// store classifier id
//m_ClassifierId = classifier.classifier_id;
}
m_UpdateClassifierTested = true;
}
private void OnCheckClassifierStatus(GetClassifiersPerClassifierVerbose classifier, string customData)
{
Log.Debug("TestVisualRecognition", "classifier {0} is {1}!", classifier.classifier_id, classifier.status);
if (classifier.status == "unavailable" || classifier.status == "failed")
{
Log.Debug("TestVisualRecognition", "Deleting classifier!");
// classifier failed - delete!
if (!m_VisualRecognition.DeleteClassifier(OnCheckClassifierStatusDelete, classifier.classifier_id))
{
Log.Debug("TestVisualRecognition", "Failed to delete classifier {0}!", m_ClassifierId);
}
}
else if (classifier.status == "training")
{
CheckClassifierStatus(OnCheckClassifierStatus);
}
else if (classifier.status == "ready")
{
m_IsClassifierReady = true;
m_ClassifierId = classifier.classifier_id;
}
}
private void OnFindClassifier(GetClassifiersPerClassifierVerbose classifier, string customData)
{
if (classifier != null)
{
Log.Status("TestVisualRecognition", "Find Result, Classifier ID: {0}, Status: {1}", classifier.classifier_id, classifier.status);
if (classifier.status == "ready")
{
m_TrainClassifier = false;
m_IsClassifierReady = true;
m_ClassifierId = classifier.classifier_id;
}
else
{
m_TrainClassifier = false;
}
}
else
{
m_TrainClassifier = true;
}
m_FindClassifierTested = true;
}
private void OnGetClassifier(GetClassifiersPerClassifierVerbose classifier, Dictionary <string, object> customData)
{
Log.Debug("ExampleVisualRecognition.OnGetClassifier()", "VisualRecognition - GetClassifier Response: {0}", customData["json"].ToString());
_getClassifierTested = true;
}
private void OnGetClassifier(GetClassifiersPerClassifierVerbose classifier, string data)
{
Log.Debug("ExampleVisualRecognition", "VisualRecognition - GetClassifier Response: {0}", data);
Test(classifier != null);
_getClassifierTested = true;
}