chore(visual recognition): Apply manual changes

Author: mediumTaj

src/IBM.WatsonDeveloperCloud.VisualRecognition.v3/IVisualRecognitionService.cs

@@ -24,12 +24,9 @@ public partial interface IVisualRecognitionService
     {
         ClassifiedImages Classify(System.IO.FileStream imagesFile = null, string acceptLanguage = null, string url = null, float? threshold = null, List<string> owners = null, List<string> classifierIds = null, string imagesFileContentType = null, Dictionary<string, object> customData = null);
         DetectedFaces DetectFaces(System.IO.FileStream imagesFile = null, string url = null, string imagesFileContentType = null, Dictionary<string, object> customData = null);
-        Classifier CreateClassifier(string name, System.IO.FileStream classnamePositiveExamples, System.IO.FileStream negativeExamples = null, Dictionary<string, object> customData = null);
         BaseModel DeleteClassifier(string classifierId, Dictionary<string, object> customData = null);
         Classifier GetClassifier(string classifierId, Dictionary<string, object> customData = null);
         Classifiers ListClassifiers(bool? verbose = null, Dictionary<string, object> customData = null);
-        Classifier UpdateClassifier(string classifierId, System.IO.FileStream classnamePositiveExamples = null, System.IO.FileStream negativeExamples = null, Dictionary<string, object> customData = null);
-        System.IO.MemoryStream GetCoreMlModel(string classifierId, Dictionary<string, object> customData = null);
         BaseModel DeleteUserData(string customerId, Dictionary<string, object> customData = null);
     }
 }

src/IBM.WatsonDeveloperCloud.VisualRecognition.v3/VisualRecognitionService.cs

@@ -291,102 +291,6 @@ public DetectedFaces DetectFaces(System.IO.FileStream imagesFile = null, string
 
             return result;
         }
-        /// <summary>
-        /// Create a classifier.
-        ///
-        /// Train a new multi-faceted classifier on the uploaded image data. Create your custom classifier with positive
-        /// or negative examples. Include at least two sets of examples, either two positive example files or one
-        /// positive and one negative file. You can upload a maximum of 256 MB per call.
-        ///
-        /// Encode all names in UTF-8 if they contain non-ASCII characters (.zip and image file names, and classifier
-        /// and class names). The service assumes UTF-8 encoding if it encounters non-ASCII characters.
-        /// </summary>
-        /// <param name="name">The name of the new classifier. Encode special characters in UTF-8.</param>
-        /// <param name="classnamePositiveExamples">A .zip file of images that depict the visual subject of a class in
-        /// the new classifier. You can include more than one positive example file in a call.
-        ///
-        /// Specify the parameter name by appending `_positive_examples` to the class name. For example,
-        /// `goldenretriever_positive_examples` creates the class **goldenretriever**.
-        ///
-        /// Include at least 10 images in .jpg or .png format. The minimum recommended image resolution is 32X32 pixels.
-        /// The maximum number of images is 10,000 images or 100 MB per .zip file.
-        ///
-        /// Encode special characters in the file name in UTF-8.</param>
-        /// <param name="negativeExamples">A .zip file of images that do not depict the visual subject of any of the
-        /// classes of the new classifier. Must contain a minimum of 10 images.
-        ///
-        /// Encode special characters in the file name in UTF-8. (optional)</param>
-        /// <param name="customData">Custom data object to pass data including custom request headers.</param>
-        /// <returns><see cref="Classifier" />Classifier</returns>
-        public Classifier CreateClassifier(string name, System.IO.FileStream classnamePositiveExamples, System.IO.FileStream negativeExamples = null, Dictionary<string, object> customData = null)
-        {
-            if (string.IsNullOrEmpty(name))
-                throw new ArgumentNullException(nameof(name));
-            if (classnamePositiveExamples == null)
-                throw new ArgumentNullException(nameof(classnamePositiveExamples));
-
-            if(string.IsNullOrEmpty(VersionDate))
-                throw new ArgumentNullException("versionDate cannot be null.");
-
-            Classifier result = null;
-
-            try
-            {
-                var formData = new MultipartFormDataContent();
-
-                if (name != null)
-                {
-                    var nameContent = new StringContent(name, Encoding.UTF8, HttpMediaType.TEXT_PLAIN);
-                    nameContent.Headers.ContentType = null;
-                    formData.Add(nameContent, "name");
-                }
-
-                if (classnamePositiveExamples != null)
-                {
-                    var classnamePositiveExamplesContent = new ByteArrayContent((classnamePositiveExamples as Stream).ReadAllBytes());
-                    System.Net.Http.Headers.MediaTypeHeaderValue contentType;
-                    System.Net.Http.Headers.MediaTypeHeaderValue.TryParse("application/octet-stream", out contentType);
-                    classnamePositiveExamplesContent.Headers.ContentType = contentType;
-                    formData.Add(classnamePositiveExamplesContent, "classname_positive_examples", classnamePositiveExamples.Name);
-                }
-
-                if (negativeExamples != null)
-                {
-                    var negativeExamplesContent = new ByteArrayContent((negativeExamples as Stream).ReadAllBytes());
-                    System.Net.Http.Headers.MediaTypeHeaderValue contentType;
-                    System.Net.Http.Headers.MediaTypeHeaderValue.TryParse("application/octet-stream", out contentType);
-                    negativeExamplesContent.Headers.ContentType = contentType;
-                    formData.Add(negativeExamplesContent, "negative_examples", negativeExamples.Name);
-                }
-
-                IClient client;
-                if(_tokenManager == null)
-                {
-                    client = this.Client;
-                }
-                else
-                {
-                    client = this.Client.WithAuthentication(_tokenManager.GetToken());
-                }
-                var restRequest = client.PostAsync($"{this.Endpoint}/v3/classifiers");
-
-                restRequest.WithArgument("version", VersionDate);
-                restRequest.WithArgument("api_key", ApiKey);
-                restRequest.WithBodyContent(formData);
-                if (customData != null)
-                    restRequest.WithCustomData(customData);
-                result = restRequest.As<Classifier>().Result;
-                if(result == null)
-                    result = new Classifier();
-                result.CustomData = restRequest.CustomData;
-            }
-            catch(AggregateException ae)
-            {
-                throw ae.Flatten();
-            }
-
-            return result;
-        }
 
         /// <summary>
         /// Delete a classifier.
@@ -529,144 +433,6 @@ public Classifiers ListClassifiers(bool? verbose = null, Dictionary<string, obje
             return result;
         }
 
-        /// <summary>
-        /// Update a classifier.
-        ///
-        /// Update a custom classifier by adding new positive or negative classes (examples) or by adding new images to
-        /// existing classes. You must supply at least one set of positive or negative examples. For details, see
-        /// [Updating custom
-        /// classifiers](https://console.bluemix.net/docs/services/visual-recognition/customizing.html#updating-custom-classifiers).
-        ///
-        /// Encode all names in UTF-8 if they contain non-ASCII characters (.zip and image file names, and classifier
-        /// and class names). The service assumes UTF-8 encoding if it encounters non-ASCII characters.
-        ///
-        /// **Tip:** Don't make retraining calls on a classifier until the status is ready. When you submit retraining
-        /// requests in parallel, the last request overwrites the previous requests. The retrained property shows the
-        /// last time the classifier retraining finished.
-        /// </summary>
-        /// <param name="classifierId">The ID of the classifier.</param>
-        /// <param name="classnamePositiveExamples">A .zip file of images that depict the visual subject of a class in
-        /// the classifier. The positive examples create or update classes in the classifier. You can include more than
-        /// one positive example file in a call.
-        ///
-        /// Specify the parameter name by appending `_positive_examples` to the class name. For example,
-        /// `goldenretriever_positive_examples` creates the class `goldenretriever`.
-        ///
-        /// Include at least 10 images in .jpg or .png format. The minimum recommended image resolution is 32X32 pixels.
-        /// The maximum number of images is 10,000 images or 100 MB per .zip file.
-        ///
-        /// Encode special characters in the file name in UTF-8. (optional)</param>
-        /// <param name="negativeExamples">A .zip file of images that do not depict the visual subject of any of the
-        /// classes of the new classifier. Must contain a minimum of 10 images.
-        ///
-        /// Encode special characters in the file name in UTF-8. (optional)</param>
-        /// <param name="customData">Custom data object to pass data including custom request headers.</param>
-        /// <returns><see cref="Classifier" />Classifier</returns>
-        public Classifier UpdateClassifier(string classifierId, System.IO.FileStream classnamePositiveExamples = null, System.IO.FileStream negativeExamples = null, Dictionary<string, object> customData = null)
-        {
-            if (string.IsNullOrEmpty(classifierId))
-                throw new ArgumentNullException(nameof(classifierId));
-
-            if(string.IsNullOrEmpty(VersionDate))
-                throw new ArgumentNullException("versionDate cannot be null.");
-
-            Classifier result = null;
-
-            try
-            {
-                var formData = new MultipartFormDataContent();
-
-                if (classnamePositiveExamples != null)
-                {
-                    var classnamePositiveExamplesContent = new ByteArrayContent((classnamePositiveExamples as Stream).ReadAllBytes());
-                    System.Net.Http.Headers.MediaTypeHeaderValue contentType;
-                    System.Net.Http.Headers.MediaTypeHeaderValue.TryParse("application/octet-stream", out contentType);
-                    classnamePositiveExamplesContent.Headers.ContentType = contentType;
-                    formData.Add(classnamePositiveExamplesContent, "classname_positive_examples", classnamePositiveExamples.Name);
-                }
-
-                if (negativeExamples != null)
-                {
-                    var negativeExamplesContent = new ByteArrayContent((negativeExamples as Stream).ReadAllBytes());
-                    System.Net.Http.Headers.MediaTypeHeaderValue contentType;
-                    System.Net.Http.Headers.MediaTypeHeaderValue.TryParse("application/octet-stream", out contentType);
-                    negativeExamplesContent.Headers.ContentType = contentType;
-                    formData.Add(negativeExamplesContent, "negative_examples", negativeExamples.Name);
-                }
-
-                IClient client;
-                if(_tokenManager == null)
-                {
-                    client = this.Client;
-                }
-                else
-                {
-                    client = this.Client.WithAuthentication(_tokenManager.GetToken());
-                }
-                var restRequest = client.PostAsync($"{this.Endpoint}/v3/classifiers/{classifierId}");
-
-                restRequest.WithArgument("version", VersionDate);
-                restRequest.WithArgument("api_key", ApiKey);
-                restRequest.WithBodyContent(formData);
-                if (customData != null)
-                    restRequest.WithCustomData(customData);
-                result = restRequest.As<Classifier>().Result;
-                if(result == null)
-                    result = new Classifier();
-                result.CustomData = restRequest.CustomData;
-            }
-            catch(AggregateException ae)
-            {
-                throw ae.Flatten();
-            }
-
-            return result;
-        }
-        /// <summary>
-        /// Retrieve a Core ML model of a classifier.
-        ///
-        /// Download a Core ML model file (.mlmodel) of a custom classifier that returns <tt>"core_ml_enabled":
-        /// true</tt> in the classifier details.
-        /// </summary>
-        /// <param name="classifierId">The ID of the classifier.</param>
-        /// <param name="customData">Custom data object to pass data including custom request headers.</param>
-        /// <returns><see cref="System.IO.FileStream" />System.IO.FileStream</returns>
-        public System.IO.MemoryStream GetCoreMlModel(string classifierId, Dictionary<string, object> customData = null)
-        {
-            if (string.IsNullOrEmpty(classifierId))
-                throw new ArgumentNullException(nameof(classifierId));
-
-            if(string.IsNullOrEmpty(VersionDate))
-                throw new ArgumentNullException("versionDate cannot be null.");
-
-            System.IO.MemoryStream result = null;
-
-            try
-            {
-                IClient client;
-                if(_tokenManager == null)
-                {
-                    client = this.Client;
-                }
-                else
-                {
-                    client = this.Client.WithAuthentication(_tokenManager.GetToken());
-                }
-                var restRequest = client.GetAsync($"{this.Endpoint}/v3/classifiers/{classifierId}/core_ml_model");
-
-                restRequest.WithArgument("version", VersionDate);
-                restRequest.WithArgument("api_key", ApiKey);
-                if (customData != null)
-                    restRequest.WithCustomData(customData);
-                result = new System.IO.MemoryStream(restRequest.AsByteArray().Result);
-            }
-            catch(AggregateException ae)
-            {
-                throw ae.Flatten();
-            }
-
-            return result;
-        }
         /// <summary>
         /// Delete labeled data.
         ///