private bool Classify(string imagePath, byte[] imageData, OnClassify callback, string[] owners = default(string[]), string[] classifierIDs = default(string[]), float threshold = default(float), string acceptLanguage = "en")
{
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, SERVICE_CLASSIFY);
if (connector == null)
{
return(false);
}
ClassifyReq req = new ClassifyReq();
req.Callback = callback;
req.Timeout = REQUEST_TIMEOUT;
req.OnResponse = OnClassifyResp;
req.AcceptLanguage = acceptLanguage;
req.Parameters["api_key"] = mp_ApiKey;
req.Parameters["version"] = VisualRecognitionVersion.Version;
req.Headers["Content-Type"] = "application/x-www-form-urlencoded";
req.Headers["Accept-Language"] = acceptLanguage;
if (imageData != null)
{
req.Send = imageData;
}
return(connector.Send(req));
}
/// <summary>
/// Classifies image specified by URL.
/// </summary>
/// <param name="url">URL.</param>
/// <param name="callback">Callback.</param>
/// <param name="owners">Owners.</param>
/// <param name="classifierIDs">Classifier IDs to be classified against.</param>
/// <param name="threshold">Threshold.</param>
/// <param name="acceptLanguage">Accept language.</param>
public bool Classify(string url, OnClassify callback, string[] owners = default(string[]), string[] classifierIDs = default(string[]), float threshold = default(float), string acceptLanguage = "en")
{
if (string.IsNullOrEmpty(mp_ApiKey))
{
mp_ApiKey = Config.Instance.GetAPIKey(SERVICE_ID);
}
if (string.IsNullOrEmpty(mp_ApiKey))
{
throw new WatsonException("FindClassifier - VISUAL_RECOGNITION_API_KEY needs to be defined in config.json");
}
if (string.IsNullOrEmpty(url))
{
throw new ArgumentNullException("url");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, SERVICE_CLASSIFY);
if (connector == null)
{
return(false);
}
ClassifyReq req = new ClassifyReq();
req.Callback = callback;
req.OnResponse = OnClassifyResp;
req.AcceptLanguage = acceptLanguage;
req.Headers["Accepted-Language"] = acceptLanguage;
req.Parameters["api_key"] = mp_ApiKey;
req.Parameters["url"] = url;
req.Parameters["version"] = VisualRecognitionVersion.Version;
if (owners != default(string[]))
{
req.Parameters["owners"] = string.Join(",", owners);
}
if (classifierIDs != default(string[]))
{
req.Parameters["classifier_ids"] = string.Join(",", classifierIDs);
}
if (threshold != default(float))
{
req.Parameters["threshold"] = threshold;
}
return(connector.Send(req));
}
public string Classify(T NewNods)
{
List <KeyValuePair <T, float> > TrainedResultDistancePair = new List <KeyValuePair <T, float> >();
foreach (T Center in TrainedResult)
{
float DistanceGet = Center.GetEuclideanDistance(NewNods);
TrainedResultDistancePair.Add(new KeyValuePair <T, float>(Center, DistanceGet));
}
var ShortestGroup = TrainedResultDistancePair.OrderBy(x => x.Value).Select(x => x.Key);
var ShortestGroupTag = ShortestGroup.First().Tag;
OnClassify?.Invoke(NewNods, ShortestGroup, ShortestGroupTag);
NewNods.Tag = ShortestGroupTag;
return(ShortestGroupTag);
}
/// <summary>
/// Classifies a posted image.
/// </summary>
/// <param name="callback">Callback.</param>
/// <param name="imagePath">Image path.</param>
/// <param name="owners">Owners.</param>
/// <param name="classifierIDs">Classifier I ds.</param>
/// <param name="threshold">Threshold.</param>
/// <param name="acceptLanguage">Accept language.</param>
public bool Classify(OnClassify callback, string imagePath, string[] owners = default(string[]), string[] classifierIDs = default(string[]), float threshold = default(float), string acceptLanguage = "en")
{
if (string.IsNullOrEmpty(mp_ApiKey))
{
mp_ApiKey = Config.Instance.GetAPIKey(SERVICE_ID);
}
if (string.IsNullOrEmpty(mp_ApiKey))
{
throw new WatsonException("FindClassifier - VISUAL_RECOGNITION_API_KEY needs to be defined in config.json");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
if (string.IsNullOrEmpty(imagePath))
{
throw new ArgumentNullException("Define an image path to classify!");
}
byte[] imageData = null;
if (!string.IsNullOrEmpty(imagePath))
{
if (LoadFile != null)
{
imageData = LoadFile(imagePath);
}
else
{
#if !UNITY_WEBPLAYER
imageData = File.ReadAllBytes(imagePath);
#endif
}
if (imageData == null)
{
Log.Error("VisualRecognition", "Failed to upload {0}!", imagePath);
}
}
return(Classify(imagePath, imageData, callback, owners, classifierIDs, threshold, acceptLanguage));
}
public KnnClassifyResult Classify(int k, T NewNode)
{
List <KeyValuePair <T, float> > NodeDistance = new List <KeyValuePair <T, float> >();
foreach (var ClassifiedNode in ClassifiedNodes)
{
var distance = ClassifiedNode.GetEuclideanDistance(NewNode);
if (Threshold != null && distance < Threshold)
{
NodeDistance.Add(new KeyValuePair <T, float>(ClassifiedNode, distance));
}
else
{
NodeDistance.Add(new KeyValuePair <T, float>(ClassifiedNode, distance));
}
}
var ClosestKPoints = NodeDistance.OrderBy(x => x.Value).Take(k);
var MostElementsGroup = ClosestKPoints
.GroupBy(node => node.Key.Tag)
.OrderByDescending(group => group.Count())
.First();
float confidence = ((float)MostElementsGroup.Count()) / ((float)k);
string MostTag = MostElementsGroup.Key;
NewNode.Tag = MostTag;
OnClassify?.Invoke(NewNode, ClosestKPoints.Select(x => x.Key), MostTag, ClassifiedNodes);
return(new KnnClassifyResult()
{
Tag = MostTag, Confidence = confidence
});
}
/// <summary>
/// Classifies the given text, invokes the callback with the results.
/// </summary>
/// <param name="classifierId">The ID of the classifier to use.</param>
/// <param name="text">The text to classify.</param>
/// <param name="callback">The callback to invoke with the results.</param>
/// <returns>Returns false if we failed to submit the request.</returns>
public bool Classify(string classifierId, string text, OnClassify callback)
{
if (string.IsNullOrEmpty(classifierId))
{
throw new ArgumentNullException("classifierId");
}
if (string.IsNullOrEmpty(text))
{
throw new ArgumentNullException("text");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v1/classifiers");
if (connector == null)
{
return(false);
}
ClassifyReq req = new ClassifyReq();
req.ClassiferId = classifierId;
req.Callback = callback;
req.OnResponse = OnClassifyResp;
req.Function = "/" + classifierId + "/classify";
req.Headers["Content-Type"] = "application/json";
Dictionary <string, object> body = new Dictionary <string, object>();
body["text"] = text;
req.Send = Encoding.UTF8.GetBytes(Json.Serialize(body));
return(connector.Send(req));
}
/// <summary>
/// Classifies the given text, invokes the callback with the results.
/// </summary>
/// <param name="classifierId">The ID of the classifier to use.</param>
/// <param name="text">The text to classify.</param>
/// <param name="callback">The callback to invoke with the results.</param>
/// <returns>Returns false if we failed to submit the request.</returns>
public bool Classify(string classifierId, string text, OnClassify callback)
{
if (string.IsNullOrEmpty(classifierId))
{
throw new ArgumentNullException("classifierId");
}
if (string.IsNullOrEmpty(text))
{
throw new ArgumentNullException("text");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
string textId = Utility.GetMD5(text);
if (!DisableCache)
{
DataCache cache = null;
if (!m_ClassifyCache.TryGetValue(classifierId, out cache))
{
cache = new DataCache("NaturalLanguageClassifier_" + classifierId);
m_ClassifyCache[classifierId] = cache;
}
byte[] cached = cache.Find(textId);
if (cached != null)
{
ClassifyResult res = ProcessClassifyResult(cached);
if (res != null)
{
callback(res);
return(true);
}
}
}
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, "/v1/classifiers");
if (connector == null)
{
return(false);
}
ClassifyReq req = new ClassifyReq();
req.TextId = textId;
req.ClassiferId = classifierId;
req.Callback = callback;
req.OnResponse = OnClassifyResp;
req.Function = "/" + classifierId + "/classify";
req.Headers["Content-Type"] = "application/json";
Dictionary <string, object> body = new Dictionary <string, object>();
body["text"] = text;
req.Send = Encoding.UTF8.GetBytes(Json.Serialize(body));
return(connector.Send(req));
}
