async Task MakePredictionRequest(MediaFile file) { var client = new System.Net.Http.HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "49918e8a54e64e948382c2657e5343e3"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/70c2cbca-16cb-4848-a9fb-f959ce7686fc/image?iterationId=f3042f17-a2a7-4670-b0f9-ee3ef66ea57a"; System.Net.Http.HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (var content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); double max = responseModel.Predictions.Max(m => m.Probability); TagLabel.Text = (max >= 0.5) ? "THIS PERSON IS LIKELY AN ALIEN" : "NOT AN ALIEN, YOU'RE SAFE"; } //Get rid of file once we have finished using it file.Dispose(); } }
public RepositoryResponse LoadEmpNominationDetails(long ID, string nominationID, string empNum) { baseModel = new RepositoryResponse(); try { using (objSOMEntities = new SOMEntities()) using (objIPEntities = new IntranetPortalEntities()) { EmpMaster a = new EmpMaster(); Nomination c = new Nomination(); var _NomDetails = (from em in objIPEntities.EmpMasters.AsEnumerable() join nom in objSOMEntities.Nominations.AsEnumerable() on em.EmployeeNumber equals nom.EmployeeNumber.ToString() where nom.IsActive == true && nom.NominationId == nominationID && em.EmployeeNumber == empNum select new { em, nom }).OrderByDescending(r => r.nom.ID).FirstOrDefault(); var _data = objSOMEntities.Evaluations.Where(r => r.ID == ID && r.IsActive == true).FirstOrDefault(); EvaluationModel model = ConvertEvaluation_DB2Model(_NomDetails.em, _data, _NomDetails.nom, 1); baseModel = new RepositoryResponse { success = true, message = "Get Evaluation details Successfully", Data = model }; } } catch (Exception ex) { baseModel = new RepositoryResponse { success = false, message = ex.ToString() }; } return(baseModel); }
public ActionResult Create(EvaluationModel Model) { Authentication("EVAF"); try { tblEvaluationHeader tbl = new tblEvaluationHeader(); tbl.AccedamicYear = DateTime.Now.Year.ToString(); tbl.CreatedBy = USession.User_Id; tbl.CreatedDate = DateTime.Today; tbl.EvaluationDescription = Model.EvaluationDescription; tbl.EvaluationType = Model.EvaluationType; tbl.isActive = "Y"; tbl.TestPaperFee = Model.TestPaperFee; tbl.SchoolId = USession.School_Id; Connection.tblEvaluationHeaders.Add(tbl); Connection.SaveChanges(); dropdowns(); return(RedirectToAction("Create")); } catch { return(View()); } }
async Task MakePredictionRequest(MediaFile file) { var client = new HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "4609999dc6134d9d8faa66f6d90b66ce"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/204bc4e4-a878-4f13-a349-17986d43538c/image"; HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (var content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); double max = responseModel.Predictions.Max(m => m.Probability); TagLabel.Text = (max >= 0.5) ? "BigCat" : "Not BigCat"; } file.Dispose(); } }
// GET: User/Edit/5 public async Task <IActionResult> Edit(long id) { EvaluationModel evals = await _evaluationService.GetAsync(HttpContext.Session, id); CompteModel compte = _compteService.GetConnectedCompte(HttpContext.Session); SujetModel sujets = await _sujetService.GetAsync(HttpContext.Session, id); List <UserModel> lstUser = await _userService.GetListUserByManagerAsync(HttpContext.Session, compte.User.Id.GetValueOrDefault(0)); var lstUserByEval = (await _evaluationService.GetListUserByEvalAsync(HttpContext.Session, evals.Id.GetValueOrDefault(0))).Select(s => new { Id = s.Id, Nom = s.Nom, Prenom = s.Prenom, Selected = true }).ToList(); var listUserTolal = lstUser.Where(w => lstUserByEval == null || lstUserByEval.Where(x => x.Id == w.Id).Count() == 0) .Select(s => new { Id = s.Id, Nom = s.Nom, Prenom = s.Prenom, Selected = false }).Concat(lstUserByEval).ToList(); //for(int i = 0; i < listUserTolal.Count();i++) { } ViewBag.lstUser = listUserTolal ?? new[] { new { Id = (long?)0, Nom = "", Prenom = "", Selected = false } }.ToList(); List <SujetModel> lstsujet = await _sujetService.GetListAsync(HttpContext.Session); var lstSujetsByEval = (await _evaluationService.GetListSujetByEvalAsync(HttpContext.Session, evals.Id.GetValueOrDefault(0))).Select(s => new { Id = s.Id, Titre = s.Titre, Selected = true }).ToList(); var listTotal = lstsujet.Where(w => lstSujetsByEval == null || lstSujetsByEval.Where(x => x.Id == w.Id).Count() == 0) .Select(s => new { Id = s.Id, Titre = s.Titre, Selected = false }).Concat(lstSujetsByEval).ToList(); //for(int i = 0; i < listUserTolal.Count();i++) { } ViewBag.lstsujet = listTotal ?? new[] { new { Id = (long?)0, Titre = "", Selected = false } }.ToList(); ViewData.Model = evals; return(View()); }
async Task MakePrediction(MediaFile image) { var client = new HttpClient { DefaultRequestHeaders = { { "Prediction-Key", "0e0a735690e14bccafd0ac94acd572e5" } } }; const string apiUrl = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/3f3b150a-e19c-4acb-ae03-5d7078f5c288/image?iterationId=ec6c19e5-4f8e-4385-87c5-3754f8ce4102"; var dataInBytes = ImageToByteArray(image); List <string> prediction = null; using (var content = new ByteArrayContent(dataInBytes)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); var response = await client.PostAsync(apiUrl, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseContent = JsonConvert.DeserializeObject <EvaluationModel>(responseString); prediction = responseContent.Predictions.Where(p => p.Probability > 0.7).Select(p => p.Tag).ToList(); } else { await DisplayAlert("Error", "Something went wrong, please try again\n" + response.StatusCode, "OK"); return; } _predictions = prediction; } }
async Task MakePredictionRequest(MediaFile file) { var client = new HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "bf91ca6d1e614b6ead6193761c9ede2d"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/bcb49c89-078b-4a5c-a127-7027e82f974e/image?iterationId=3ced66ed-a8ef-46c7-a28a-db3d9b0118d0"; HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (var content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); double max = responseModel.Predictions.Max(m => m.Probability); TagLabel.Text = (max >= 0.5) ? "NMD" : "NOT NMD"; } //Get rid of file once we have finished using it file.Dispose(); } }
async Task MakePredictionRequest(MediaFile file) { var client = new HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "e255f72dcb9b4f69917f05309ab246d2"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/f4777059-a48b-4ab0-b43f-d585c83e164e/image?iterationId=92c71ce9-4e94-4ced-a344-031e5939af17"; HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (var content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); double max = responseModel.Predictions.Max(m => m.Probability); TagLabel.Text = (max >= 0.5) ? "This is a photo of rice (Probability: " + max + ")." : " This is not a photo of rice (Probability: " + max + ")."; file.Dispose(); } } }
public ActionResult EvaluationPopupValues(string ID) { long _id = long.Parse(ID); _evaluationRepo = new EvaluationRepo(); _repoResponse = new RepositoryResponse(); if (_id > 0) { _repoResponse = _evaluationRepo.LoadEvaluationDataByID(_id); } //else //{ // _repoResponse = _evaluationRepo.LoadEmpNominationDetails(_id, long.Parse(nominationID), empNum); //} if (_repoResponse.success == true) { EvaluationModel model = new EvaluationModel(); model = _repoResponse.Data; //return JSon(model); return(Json(new { success = _repoResponse.success, message = _repoResponse.message, data = model })); } else { EvaluationModel model = new EvaluationModel(); return(Json(new { success = _repoResponse.success, message = _repoResponse.message, data = model })); } }
public ActionResult AddOrUpdate(EvaluationModel model) { if (!ModelState.IsValid) { return(View(model)); } var isCreated = model.Id == Guid.Empty; var evaluation = new Evaluations(); if (!isCreated) { evaluation = EvaluationRepository.GetById(model.Id); } evaluation.Date = model.Date; evaluation.Classroom_Id = model.ClassroomId; evaluation.Classrooms = ClassroomRepository.GetById(model.ClassroomId); evaluation.User_Id = model.UserId; evaluation.Users = UserRepository.GetById(model.UserId); evaluation.TotalPoint = model.TotalPoint; evaluation.Periods = PeriodRepository.GetById(model.PeriodId); if (isCreated) { EvaluationRepository.Add(evaluation); } EvaluationRepository.Save(); return(Redirect(Url.Action("Get", "Evaluation", new { id = evaluation.Id }))); }
async Task MakePredictionRequest(MediaFile file) { var client = new HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "9edb926f637d4217a56323b6538e14a4"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/29e9309a-cc47-4123-b301-edaa3047ff89/image?iterationId=c8d11c4e-4192-4cef-8291-127ad9a74fcc"; HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (var content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); double max = responseModel.Predictions.Max(m => m.Probability); TagLabel.Text = (max >= 0.2) ? "SuperHero" : "Not SuperHero"; } //Get rid of file once we have finished using it file.Dispose(); } }
private static void CrossValidate() { var evaluationModel = new EvaluationModel(LoadModel()); var result = evaluationModel.Evaluate(); Console.WriteLine(result); Console.ReadKey(); }
private async Task MakePredictionRequest(MediaFile file) { try { Contract.Ensures(Contract.Result <Task>() != null); var client = new HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "9b2cd115e674489c892a12aa9b4747f2"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/9ced7a98-a868-45b5-a7ca-e9112877744a/image?iterationId=decd2fad-4dfe-4c98-a7f3-7b82e1b058e6"; HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (var content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); List <Prediction> predictions = responseModel.Predictions; foreach (Prediction prediction in predictions) { if (prediction.Probability >= 0.8) { var locator = CrossGeolocator.Current; locator.DesiredAccuracy = 50; var position = await locator.GetPositionAsync(10000); foodLabel.Text = prediction.Tag; shareButton.IsVisible = true; unsentModel = new FoodLocationModel() { Title = prediction.Tag, Longitude = (float)position.Longitude, Latitude = (float)position.Latitude }; file.Dispose(); return; } } foodLabel.Text = "What is this? Is this even food?"; } //Get rid of file once we have finished using it file.Dispose(); } } catch (Exception e) { Console.WriteLine("{0} Exception caught", e); } }
public ActionResult DeleteEvaluationDetail(string EvaluationDetailSeqNo, string EvaluationNo) { EvaluationModel Model = new EvaluationModel(); Model.EvaluationDetailSeqNo = long.Parse(EvaluationDetailSeqNo); Model.EvaluationNo = long.Parse(EvaluationNo); Model.SchoolId = USession.School_Id; return(PartialView("DeleteEvaluationDetail", Model)); }
public ActionResult Create(EvaluationModel eval) { HttpClient client = new HttpClient(); client.BaseAddress = new Uri("http://localhost:9080/UserManager-web/"); var result = client.PostAsJsonAsync <EvaluationModel>("api/evaluations", eval).Result; return(RedirectToAction("Index")); }
public static void EvalGeneCscc() { var models = MostCommonGene(LoadGeneCsccTrainingModel()); foreach (var model in models) { var evaluationModel = new EvaluationModel(model); Console.WriteLine(evaluationModel.Evaluate()); } Console.ReadKey(); }
public IActionResult AddReport([FromBody] EvaluationModel evaluation) { var report = _dataService.AddReport(evaluation.evaluation_id, evaluation.report); if (report == null) { return(NotFound()); } return(Ok(report)); }
public ActionResult Edit(EvaluationModel evaluation) { HttpClient Client = new HttpClient(); Client.BaseAddress = new Uri("http://localhost:9080/UserManager-web/"); Client.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json")); // EvaluationModel eval = evaluation; HttpResponseMessage result = Client.PutAsJsonAsync <EvaluationModel>("api/evaluations/" + evaluation.id, evaluation).Result; return(RedirectToAction("Index")); }
/// <summary> /// /// </summary> /// <param name="sender"></param> /// <param name="e"></param> protected void InsertEvaluationByGroup(object sender, DirectEventArgs e) { try { if (!string.IsNullOrEmpty(hdfGroupFilter.Text)) { var criterionModels = CriterionController.GetAll(null, Convert.ToInt32(hdfGroupFilter.Text), false, KpiStatus.Active, null, null, null); //create new all employee var records = RecordController.GetAll(null, null, DepartmentIds, RecordType.Default, null, null); foreach (var criterion in criterionModels) { foreach (var item in records) { var model = new EvaluationModel() { RecordId = item.Id, CriterionId = criterion.Id, Month = DateTime.Now.Month, Year = DateTime.Now.Year, Value = "" }; //get value GetValueCriterionWorkbook(model, criterion, Convert.ToInt32(hdfGroupFilter.Text)); //check exist var evaluation = EvaluationController.CheckExist(model.RecordId, model.CriterionId, model.Month, model.Year); if (evaluation != null) { model.Id = evaluation.Id; //update EvaluationController.Update(model); } else { //create EvaluationController.Create(model); } } } //hide window wdEvaluation.Hide(); // reload grid gpEvaluation.Reload(); } } catch (Exception exception) { Dialog.ShowError(exception); } }
async Task MakePredictionRequest(MediaFile file) { var client = new HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "c318d58e642d4da0a94252bbbd87a76e"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/ceeb2fc1-b383-407e-88cb-f1ec50db4054/image?iterationId=db0244c3-7eeb-4ba9-80b0-4ea7ff96df89"; HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (var content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); double max = responseModel.Predictions.Max(m => m.Probability); foreach (var item in responseModel.Predictions) { if (max <= 0.5) { await DisplayAlert("Wow", "Hmm, I can't really tell.", "Ok"); break; } else if (item.Tag == "male" && item.Probability > 0.7) { await DisplayAlert("Wow", "Hmm, I think this is a male.", "Ok"); break; } else if (item.Tag == "female" && item.Probability > 0.7) { await DisplayAlert("Wow", "Hmm, I think this is a female.", "Ok"); break; } } } //Get rid of file once we have finished using it file.Dispose(); } }
async Task MakePredictionRequest(MediaFile file) { Contract.Ensures(Contract.Result <Task>() != null); var client = new HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "4acc8969a66e4e6a8566c55658bbe9d2"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.1/Prediction/ce6463c9-a4b5-4af6-aed2-18babd9f8483/image?iterationId=1ddec163-8098-4387-b095-fa55183c512e"; HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (var content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); double max = responseModel.Predictions.Max(m => m.Probability); if (max >= 0.5) { TagLabel.Text = "There is a heavy traffic in TinFactory"; await CrossTextToSpeech.Current.Speak(TagLabel.Text); await Navigation.PushAsync(new TrafficEvaluationPage()); // CrossLocalNotifications.Current.Show("Alert", "We have send the informaton to local concen autheroties"); } else { TagLabel.Text = " There is no heavy Traffic in Tin Factory"; await CrossTextToSpeech.Current.Speak(TagLabel.Text); await Navigation.PushAsync(new TrafficEvaluationPage()); } } //Get rid of file once we have finished using it file.Dispose(); } }
/// <summary> /// /// </summary> /// <param name="model"></param> /// <param name="criterion"></param> /// <param name="groupId"></param> private static void GetValueCriterionWorkbook(EvaluationModel model, CriterionModel criterion, int?groupId) { var empArgument = EmployeeArgumentController.GetAll(null, null, groupId, model.RecordId, model.Month, model.Year, null, null); var workbook = new WorkBook { AutoCalc = false }; foreach (var argument in empArgument) { switch (argument.ValueType) { case KpiValueType.String: workbook.setText($"{argument.ArgumentCalculateCode}1", argument.Value); break; case KpiValueType.Number: workbook.setNumber($"{argument.ArgumentCalculateCode}1", double.TryParse(argument.Value, out var parseResultNumber) ? parseResultNumber : 0); break; case KpiValueType.Percent: workbook.setFormula($"{argument.ArgumentCalculateCode}1", double.TryParse(argument.Value, out var parseResultPercent) ? $"{parseResultPercent} * 0.01" : "0"); break; case KpiValueType.Formula: workbook.setFormula($"{argument.ArgumentCalculateCode}1", argument.Value.TrimStart('=')); break; } } workbook.setFormula("A1", criterion.Formula.TrimStart('=')); workbook.recalc(); switch (criterion.ValueType) { case KpiValueType.Number: model.Value = workbook.getNumber("A1").ToString("#,##0.##"); break; case KpiValueType.Percent: model.Value = (workbook.getNumber("A1") * 100).ToString("0.00"); break; default: model.Value = workbook.getText("A1"); break; } }
async Task MakePredictionRequest(MediaFile file) { var client = new HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "6b188bd282ac425a8e3755635c55f37e"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/34669e80-95d0-4bc7-8062-1f1d94f76082/image?iterationId=a7ea51b3-732b-4588-b424-3a2b7af7c800"; HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (var content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { var responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); var probability = responseModel.Predictions.OrderByDescending(probabilityH => probabilityH.Probability); var output_result = probability.Take(1).Single(); BarIndicator.IsVisible = true; if (output_result.Probability > 0.5) { TagLabel.Text = output_result.Tag; AzureManager.AzureManagerInstance.SetIngredient(output_result.Tag); await BarIndicator.ProgressTo(1, 80, Easing.Linear); BarIndicator.IsVisible = false; BarIndicator.ProgressTo(0, 80, Easing.Linear); Globals.exist = true; } else { await BarIndicator.ProgressTo(1, 80, Easing.Linear); TagLabel.Text = "Doesn't exist in the database"; BarIndicator.IsVisible = false; BarIndicator.ProgressTo(0, 80, Easing.Linear); } } file.Dispose(); } }
private Evaluation ConvertEvaluation_Model2DB(EvaluationModel model, string _loggedInUserID, bool isSubmit) { Evaluation db = new Evaluation(); if (model != null) { db.AheadOfPlan = model.AheadOfPlan; db.AsPerPlan = model.AsPerPlan; db.BasedOnInstruction = model.BasedOnInstruction; db.BreakthroughImprovement = model.BreakthroughImprovement; db.CoordiantionWithInTheDept = model.CoordiantionWithInTheDept; db.CoordinationWithAnotherFunction = model.CoordinationWithAnotherFunction; db.CoordinationWithMultipleFunctions = model.CoordinationWithMultipleFunctions; db.Delayed = model.Delayed; db.EmployeeNumber = model.EmployeeNumber; db.NominationID = model.NominationID; db.EvaluatorID = model.EvaluatorID; db.FollowedUp = model.FollowedUp; db.ID = model.ID; db.Implemented = model.Implemented; db.ImplementedInAllApplicableAreas = model.ImplementedInAllApplicableAreas; db.ImplementedPartially = model.ImplementedPartially; db.ImprovementFromCurrentSituation = model.ImprovementFromCurrentSituation; db.IsActive = true; db.Participated = model.Participated; db.PreventionOfaFailure = model.PreventionOfaFailure; db.ProactiveIdeaGeneratedBySelf = model.ProactiveIdeaGeneratedBySelf; db.ReactiveIdeaDrivenBySituation = model.ReactiveIdeaDrivenBySituation; db.ScopeIdentified = model.ScopeIdentified; if (isSubmit) { db.Status = (int)NominationStatus.Evaluators_Assign_TQC; } else { db.Status = (int)NominationStatus.Evaluators_Save; } db.TotalScore = int.Parse(model.TotalScore); db.CreatedBy = _loggedInUserID;; } return(db); }
async Task MakePredictionRequest(MediaFile file) { HttpClient client = new HttpClient(); client.DefaultRequestHeaders.Add("Prediction-Key", "c11b49980c4f42e0a34b8820a0607713"); string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/d094d72a-8e5e-48e5-bfb1-d5b8be2f070c/image?iterationId=ec824ab3-e526-4b65-9662-b69f1069954a"; HttpResponseMessage response; byte[] byteData = GetImageAsByteArray(file); using (ByteArrayContent content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); TagLabel.Text = "Processing..."; response = await client.PostAsync(url, content); if (response.IsSuccessStatusCode) { string responseString = await response.Content.ReadAsStringAsync(); EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString); String predictionData = ""; Prediction mostProbable = null; foreach (Prediction prediction in responseModel.Predictions) { predictionData += prediction.Tag + " with probability " + prediction.Probability + "\n"; if (mostProbable == null || mostProbable.Probability < prediction.Probability) { mostProbable = prediction; } } TagLabel.Text = (mostProbable != null && mostProbable.Probability > 0.5d) ? "It is a " + mostProbable.Tag + "!" : "No result"; TagLabel.Text = TagLabel.Text + "\n\n" + predictionData; file.Dispose(); } else { TagLabel.Text = "Operation Failed! " + response.StatusCode; } } }
public async Task ExecuteAsync(ICommandUpdateFascicleData command) { _logger.WriteInfo(new LogMessage($"{command.CommandName} is arrived"), LogCategories); FascicleBuildModel fascicleBuildModel = command.ContentType.ContentTypeValue; FascicleModel fascicleModel = fascicleBuildModel.Fascicle; try { if (RetryPolicyEvaluation != null && !string.IsNullOrEmpty(RetryPolicyEvaluation.ReferenceModel)) { _logger.WriteDebug(new LogMessage("Load reference model from RetryPolicyEvaluation"), LogCategories); fascicleModel = JsonConvert.DeserializeObject <FascicleModel>(RetryPolicyEvaluation.ReferenceModel, _serializerSettings); } else { _logger.WriteDebug(new LogMessage("Generate new RetryPolicyEvaluation model"), LogCategories); RetryPolicyEvaluation = new EvaluationModel(); } _logger.WriteInfo(new LogMessage($"Cancel requested for fascicle {fascicleModel.Title}/{fascicleModel.UniqueId}-{fascicleModel.FascicleObject}"), LogCategories); _logger.WriteDebug(new LogMessage($"Cancel requested from WorkflowName {fascicleBuildModel.WorkflowName} and IdWorkflowActivity {fascicleBuildModel.IdWorkflowActivity}"), LogCategories); if (!RetryPolicyEvaluation.Steps.Any(f => f.Name == "ENTITY_UPDATED")) { Fascicle updatedFascicle = await UpdateData(fascicleBuildModel, fascicleModel); _logger.WriteInfo(new LogMessage($"Fascicle {updatedFascicle.GetTitle()} has been updated"), LogCategories); RetryPolicyEvaluation.Steps.Add(new StepModel() { Name = "ENTITY_UPDATED", LocalReference = JsonConvert.SerializeObject(fascicleModel, _serializerSettings) }); _logger.WriteDebug(new LogMessage("Set ENTITY_UPDATED RetryPolicyEvaluation"), LogCategories); } else { StepModel fascicleStatus = RetryPolicyEvaluation.Steps.First(f => f.Name == "ENTITY_UPDATED"); fascicleModel = JsonConvert.DeserializeObject <FascicleModel>(fascicleStatus.LocalReference); _logger.WriteDebug(new LogMessage("Load fascicle entity from RetryPolicyEvaluation ENTITY_UPDATED"), LogCategories); } } catch (Exception ex) { RetryPolicyEvaluation.ReferenceModel = JsonConvert.SerializeObject(fascicleModel, _serializerSettings); _logger.WriteError(ex, LogCategories); throw new ServiceBusEvaluationException(RetryPolicyEvaluation); } }
public ActionResult AddOrUpdate(Guid?Id, Guid?classroomId) { var model = new EvaluationModel(); model.Date = DateTime.Now; if (Id.HasValue) { model = EvaluationModel.ToModel(EvaluationRepository.GetById(Id.Value)); } if (classroomId.HasValue) { model.ClassroomId = classroomId.Value; } return(View(model)); }
/// <summary> /// /// </summary> /// <param name="sender"></param> /// <param name="e"></param> protected void EvaluationClick(object sender, DirectEventArgs e) { try { if (!string.IsNullOrEmpty(hdfId.Text)) { //create new all employee var records = RecordController.GetAll(null, null, DepartmentIds, RecordType.Default, null, null); var criterion = CriterionController.GetById(Convert.ToInt32(hdfId.Text)); foreach (var item in records) { var model = new EvaluationModel() { RecordId = item.Id, CriterionId = Convert.ToInt32(hdfId.Text), Month = DateTime.Now.Month, Year = DateTime.Now.Year, Value = "" }; //get value GetValueCriterionWorkbook(model, criterion, null); //check exist var evaluation = EvaluationController.CheckExist(model.RecordId, model.CriterionId, model.Month, model.Year); if (evaluation != null) { model.Id = evaluation.Id; //update EvaluationController.Update(model); } else { //create EvaluationController.Create(model); } } } } catch (Exception exception) { Dialog.ShowError(exception); } }
public ActionResult DeleteEvaluationHeader(EvaluationModel Model) { try { // Model.SchoolId="121127"; string evalNo = Model.EvaluationNo.ToString(); Connection.SMGTModifyEvaluationHeaderStatus(Model.SchoolId, evalNo); // Connection.tblHouses. Connection.SaveChanges(); return(Json(Model.SchoolId, JsonRequestBehavior.AllowGet)); } catch { return(Json("Error", JsonRequestBehavior.AllowGet)); } }
public async Task ExecuteAsync(ICommandUpdateDossierData command) { _logger.WriteInfo(new LogMessage($"{command.CommandName} is arrived"), LogCategories); Dossier dossier = command.ContentType.ContentTypeValue; try { if (RetryPolicyEvaluation != null && !string.IsNullOrEmpty(RetryPolicyEvaluation.ReferenceModel)) { _logger.WriteDebug(new LogMessage("Load reference model from RetryPolicyEvaluation"), LogCategories); dossier = JsonConvert.DeserializeObject <Dossier>(RetryPolicyEvaluation.ReferenceModel, _serializerSettings); } else { _logger.WriteDebug(new LogMessage("Generate new RetryPolicyEvaluation model"), LogCategories); RetryPolicyEvaluation = new EvaluationModel(); } if (!RetryPolicyEvaluation.Steps.Any(f => f.Name == STEP_UPDATE_DOSSIER)) { Dossier updatedDossier = await UpdateDossierEntity(dossier); _logger.WriteInfo(new LogMessage($"Dossier {updatedDossier.GetTitle()} has been updated"), LogCategories); RetryPolicyEvaluation.Steps.Add(new StepModel() { Name = STEP_UPDATE_DOSSIER, LocalReference = JsonConvert.SerializeObject(updatedDossier, _serializerSettings) }); } else { StepModel messageStatus = RetryPolicyEvaluation.Steps.First(f => f.Name == STEP_UPDATE_DOSSIER); dossier = JsonConvert.DeserializeObject <Dossier>(messageStatus.LocalReference); } } catch (Exception ex) { RetryPolicyEvaluation.ReferenceModel = JsonConvert.SerializeObject(dossier, _serializerSettings); _logger.WriteError(ex, LogCategories); throw new ServiceBusEvaluationException(RetryPolicyEvaluation); } }
public IEnumerable<EvaluationModel> GenerateEvaluationModel(List<AssetBase> assets) { List<EvaluationModel> models = new List<EvaluationModel>(); Ratios ratios = assets.GetAverageRatiosFor<InternationalEquity>(); Recommendation expected = assets.GetAverageExpectedFor<InternationalEquity>(); foreach (EvaluationInfo evaluation in Enum.GetValues(typeof(EvaluationInfo))) { EvaluationModel eachModel = new EvaluationModel { title = edisRepo.GetEnumDescription(evaluation) }; switch (evaluation) { case EvaluationInfo.OneYearReturn: eachModel.actual += ratios.OneYearReturn; eachModel.expected += expected.OneYearReturn == null ? 0 : (double)expected.OneYearReturn; break; case EvaluationInfo.FiveYearReturn: eachModel.actual += ratios.FiveYearReturn; eachModel.expected += expected.FiveYearTotalReturn == null ? 0 : (double)expected.OneYearReturn; break; case EvaluationInfo.DebtEquityRatio: eachModel.actual += ratios.DebtEquityRatio; eachModel.expected += expected.DebtEquityRatio; break; case EvaluationInfo.EpsGrowth: eachModel.actual += ratios.EpsGrowth; eachModel.expected += expected.EpsGrowth; break; case EvaluationInfo.DividendYield: eachModel.actual += ratios.DividendYield; eachModel.expected += expected.DividendYield; break; case EvaluationInfo.Frank: eachModel.actual += ratios.Frank; eachModel.expected += expected.Frank; break; case EvaluationInfo.InterestCover: eachModel.actual += ratios.InterestCover; eachModel.expected += expected.InterestCover; break; case EvaluationInfo.PriceEarningRatio: eachModel.actual += ratios.PriceEarningRatio; eachModel.expected += expected.PriceEarningRatio; break; case EvaluationInfo.ReturnOnAsset: eachModel.actual += ratios.ReturnOnAsset; eachModel.expected += expected.ReturnOnAsset; break; case EvaluationInfo.ReturnOnEquity: eachModel.actual += ratios.ReturnOnEquity; eachModel.expected += expected.ReturnOnEquity; break; } models.Add(eachModel); } return models; }
public IEnumerable<EvaluationModel> GetEvaluationModel_Client() { Client client = edisRepo.GetClientSync(User.Identity.GetUserId(), DateTime.Now); ClientGroup clientGroup = edisRepo.GetClientGroupSync(client.ClientGroupId, DateTime.Now); if (clientGroup.MainClientId == client.Id) { List<GroupAccount> groupAccounts = edisRepo.GetAccountsForClientGroupSync(clientGroup.ClientGroupNumber, DateTime.Now); List<ClientAccount> clientAccounts = edisRepo.GetAccountsForClientSync(client.ClientNumber, DateTime.Now); EvaluationModel model1 = new EvaluationModel { title = "One Year Return" }; EvaluationModel model3 = new EvaluationModel { title = "Debt Equity Ratio" }; EvaluationModel model4 = new EvaluationModel { title = "Eps Growth" }; EvaluationModel model5 = new EvaluationModel { title = "Dividend Yield" }; EvaluationModel model6 = new EvaluationModel { title = "Franking" }; EvaluationModel model7 = new EvaluationModel { title = "Interest Cover" }; EvaluationModel model8 = new EvaluationModel { title = "Price Earning Ratio" }; EvaluationModel model9 = new EvaluationModel { title = "Return On Asset" }; EvaluationModel model10 = new EvaluationModel { title = "Return On Equity" }; foreach (var account in groupAccounts) { List<AssetBase> assets = account.GetAssetsSync(); Ratios ratios = assets.GetAverageRatiosFor<InternationalEquity>(); Recommendation expected = assets.GetAverageExpectedFor<InternationalEquity>(); model1.actual += ratios.OneYearReturn; model1.expected += expected.OneYearReturn == null ? 0 : (double)expected.OneYearReturn; model3.actual += ratios.DebtEquityRatio; model3.expected += expected.DebtEquityRatio; model4.actual += ratios.EpsGrowth; model4.expected += expected.EpsGrowth; model5.actual += ratios.DividendYield; model5.expected += expected.DividendYield; model6.actual += ratios.Frank; model6.expected += expected.Frank; model7.actual += ratios.InterestCover; model7.expected += expected.InterestCover; model8.actual += ratios.PriceEarningRatio; model8.expected += expected.PriceEarningRatio; model9.actual += ratios.ReturnOnAsset; model9.expected += expected.ReturnOnAsset; model10.actual += ratios.ReturnOnEquity; model10.expected += expected.ReturnOnEquity; } foreach (var account in clientAccounts) { List<AssetBase> assets = account.GetAssetsSync(); Ratios ratios = assets.GetAverageRatiosFor<InternationalEquity>(); Recommendation expected = assets.GetAverageExpectedFor<InternationalEquity>(); model1.actual += ratios.OneYearReturn; model1.expected += expected.OneYearReturn == null ? 0 : (double)expected.OneYearReturn; model3.actual += ratios.DebtEquityRatio; model3.expected += expected.DebtEquityRatio; model4.actual += ratios.EpsGrowth; model4.expected += expected.EpsGrowth; model5.actual += ratios.DividendYield; model5.expected += expected.DividendYield; model6.actual += ratios.Frank; model6.expected += expected.Frank; model7.actual += ratios.InterestCover; model7.expected += expected.InterestCover; model8.actual += ratios.PriceEarningRatio; model8.expected += expected.PriceEarningRatio; model9.actual += ratios.ReturnOnAsset; model9.expected += expected.ReturnOnAsset; model10.actual += ratios.ReturnOnEquity; model10.expected += expected.ReturnOnEquity; } List<EvaluationModel> models = new List<EvaluationModel>(); models.Add(model1); models.Add(model3); models.Add(model4); models.Add(model5); models.Add(model6); models.Add(model7); models.Add(model8); models.Add(model9); models.Add(model10); return models; } else { List<ClientAccount> accounts = edisRepo.GetAccountsForClientSync(client.ClientNumber, DateTime.Now); EvaluationModel model1 = new EvaluationModel { title = "One Year Return" }; EvaluationModel model3 = new EvaluationModel { title = "Debt Equity Ratio" }; EvaluationModel model4 = new EvaluationModel { title = "Eps Growth" }; EvaluationModel model5 = new EvaluationModel { title = "Dividend Yield" }; EvaluationModel model6 = new EvaluationModel { title = "Franking" }; EvaluationModel model7 = new EvaluationModel { title = "Interest Cover" }; EvaluationModel model8 = new EvaluationModel { title = "Price Earning Ratio" }; EvaluationModel model9 = new EvaluationModel { title = "Return On Asset" }; EvaluationModel model10 = new EvaluationModel { title = "Return On Equity" }; foreach (var account in accounts) { List<AssetBase> assets = account.GetAssetsSync(); Ratios ratios = assets.GetAverageRatiosFor<InternationalEquity>(); Recommendation expected = assets.GetAverageExpectedFor<InternationalEquity>(); model1.actual += ratios.OneYearReturn; model1.expected += expected.OneYearReturn == null ? 0 : (double)expected.OneYearReturn; model3.actual += ratios.DebtEquityRatio; model3.expected += expected.DebtEquityRatio; model4.actual += ratios.EpsGrowth; model4.expected += expected.EpsGrowth; model5.actual += ratios.DividendYield; model5.expected += expected.DividendYield; model6.actual += ratios.Frank; model6.expected += expected.Frank; model7.actual += ratios.InterestCover; model7.expected += expected.InterestCover; model8.actual += ratios.PriceEarningRatio; model8.expected += expected.PriceEarningRatio; model9.actual += ratios.ReturnOnAsset; model9.expected += expected.ReturnOnAsset; model10.actual += ratios.ReturnOnEquity; model10.expected += expected.ReturnOnEquity; } List<EvaluationModel> models = new List<EvaluationModel>(); models.Add(model1); models.Add(model3); models.Add(model4); models.Add(model5); models.Add(model6); models.Add(model7); models.Add(model8); models.Add(model9); models.Add(model10); return models; } }