public void StartTrainingArgumentValidation()
{
FormTrainingClient client = CreateInstrumentedClient();
Assert.ThrowsAsync <UriFormatException>(() => client.StartTrainingAsync(new Uri(string.Empty), useTrainingLabels: false));
Assert.ThrowsAsync <ArgumentNullException>(() => client.StartTrainingAsync((Uri)null, useTrainingLabels: false));
}
private static async Task <string> TrainModelWithLabelsAsync(
FormTrainingClient trainingClient, string trainingFileUrl)
{
CustomFormModel model = await trainingClient
.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : true).WaitForCompletionAsync();
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {model.ModelId}");
Console.WriteLine($" Model Status: {model.Status}");
Console.WriteLine($" Requested on: {model.TrainingStartedOn}");
Console.WriteLine($" Completed on: {model.TrainingCompletedOn}");
foreach (CustomFormSubmodel submodel in model.Submodels)
{
Console.WriteLine($"Submodel Form Type: {submodel.FormType}");
foreach (CustomFormModelField field in submodel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Accuracy != null)
{
Console.Write($", Accuracy: {field.Accuracy}");
}
Console.WriteLine("");
}
}
return(model.ModelId);
}
public async Task OutputModelsTrainedWithoutLabels()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
string formFilePath = FormRecognizerTestEnvironment.CreatePath("Form_1.jpg");
FormRecognizerClient client = new FormRecognizerClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
FormTrainingClient trainingClient = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
// Model trained without labels
CustomFormModel modelTrainedWithoutLabels = await trainingClient.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : false).WaitForCompletionAsync();
using (FileStream stream = new FileStream(formFilePath, FileMode.Open))
{
RecognizedFormCollection forms = await client.StartRecognizeCustomFormsAsync(modelTrainedWithoutLabels.ModelId, stream).WaitForCompletionAsync();
// With a form recognized by a model trained without labels, the 'field.Name' property will be denoted
// by a numeric index. To look for the labels identified during the training step,
// use the `field.LabelText` property.
Console.WriteLine("---------Recognizing forms using models trained without labels---------");
foreach (RecognizedForm form in forms)
{
Console.WriteLine($"Form of type: {form.FormType}");
foreach (FormField field in form.Fields.Values)
{
Console.WriteLine($"Field {field.Name}: ");
if (field.LabelData != null)
{
Console.WriteLine($" Label: '{field.LabelData.Text}");
}
Console.WriteLine($" Value: '{field.ValueData.Text}");
Console.WriteLine($" Confidence: '{field.Confidence}");
}
}
// Find the value of unlabeled fields.
foreach (RecognizedForm form in forms)
{
// Find the value of a specific unlabeled field.
Console.WriteLine("Find the value for a specific unlabeled field:");
foreach (FormField field in form.Fields.Values)
{
if (field.LabelData != null && field.LabelData.Text == "Vendor Name:")
{
Console.WriteLine($"The Vendor Name is {field.ValueData.Text}");
}
}
// Find the value of unlabeled fields with specific words
Console.WriteLine("Find the value for labeled field with specific words:");
form.Fields.Values.Where(field => field.LabelData.Text.StartsWith("Ven"))
.ToList().ForEach(v => Console.WriteLine($"{v.LabelData.Text} is {v.ValueData.Text}"));
form.Fields.Values.Where(field => field.LabelData.Text.Contains("Name"))
.ToList().ForEach(v => Console.WriteLine($"{v.LabelData.Text} is {v.ValueData.Text}"));
}
}
}
public async Task ManageCustomModelsAsync()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
#region Snippet:FormRecognizerSampleManageCustomModelsAsync
FormTrainingClient client = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
// Check number of models in the FormRecognizer account, and the maximum number of models that can be stored.
AccountProperties accountProperties = await client.GetAccountPropertiesAsync();
Console.WriteLine($"Account has {accountProperties.CustomModelCount} models.");
Console.WriteLine($"It can have at most {accountProperties.CustomModelLimit} models.");
// List the models currently stored in the account.
AsyncPageable <CustomFormModelInfo> models = client.GetCustomModelsAsync();
await foreach (CustomFormModelInfo modelInfo in models)
{
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {modelInfo.ModelId}");
Console.WriteLine($" Model name: {modelInfo.ModelName}");
Console.WriteLine($" Is composed model: {modelInfo.Properties.IsComposedModel}");
Console.WriteLine($" Model Status: {modelInfo.Status}");
Console.WriteLine($" Training model started on: {modelInfo.TrainingStartedOn}");
Console.WriteLine($" Training model completed on: : {modelInfo.TrainingCompletedOn}");
}
// Create a new model to store in the account
CustomFormModel model = await client.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : false, new TrainingOptions()
{
ModelName = "My new model"
}).WaitForCompletionAsync();
// Get the model that was just created
CustomFormModel modelCopy = await client.GetCustomModelAsync(model.ModelId);
Console.WriteLine($"Custom Model with Id {modelCopy.ModelId} and name {modelCopy.ModelName} recognizes the following form types:");
foreach (CustomFormSubmodel submodel in modelCopy.Submodels)
{
Console.WriteLine($"Submodel Form Type: {submodel.FormType}");
foreach (CustomFormModelField field in submodel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Label != null)
{
Console.Write($", FieldLabel: {field.Label}");
}
Console.WriteLine("");
}
}
// Delete the model from the account.
await client.DeleteModelAsync(model.ModelId);
#endregion
}
static async Task Main(string[] args)
{
try
{
// Get configuration settings
IConfigurationBuilder builder = new ConfigurationBuilder().AddJsonFile("appsettings.json");
IConfigurationRoot configuration = builder.Build();
string formEndpoint = configuration["FormEndpoint"];
string formKey = configuration["FormKey"];
string trainingStorageUri = configuration["StorageUri"];
// Authenticate Form Training Client
var credential = new AzureKeyCredential(formKey);
var trainingClient = new FormTrainingClient(new Uri(formEndpoint), credential);
// Train model
CustomFormModel model = await trainingClient
.StartTrainingAsync(new Uri(trainingStorageUri), useTrainingLabels : false)
.WaitForCompletionAsync();
// Get model info
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {model.ModelId}");
Console.WriteLine($" Model Status: {model.Status}");
Console.WriteLine($" Training model started on: {model.TrainingStartedOn}");
Console.WriteLine($" Training model completed on: {model.TrainingCompletedOn}");
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
}
// </snippet_receipt_print>
// <snippet_train>
private static async Task <String> TrainModel(
FormTrainingClient trainingClient, string trainingDataUrl)
{
CustomFormModel model = await trainingClient
.StartTrainingAsync(new Uri(trainingDataUrl), useTrainingLabels : false)
.WaitForCompletionAsync();
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {model.ModelId}");
Console.WriteLine($" Model Status: {model.Status}");
Console.WriteLine($" Training model started on: {model.TrainingStartedOn}");
Console.WriteLine($" Training model completed on: {model.TrainingCompletedOn}");
// </snippet_train>
// <snippet_train_response>
foreach (CustomFormSubmodel submodel in model.Submodels)
{
Console.WriteLine($"Submodel Form Type: {submodel.FormType}");
foreach (CustomFormModelField field in submodel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Label != null)
{
Console.Write($", FieldLabel: {field.Label}");
}
Console.WriteLine("");
}
}
// </snippet_train_response>
// <snippet_train_return>
return(model.ModelId);
}
public async Task RecognizeCustomFormsFromUri()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
// Firstly, create a trained model we can use to recognize the custom form. Please note that
// models can also be trained using a graphical user interface such as the Form Recognizer
// Labeling Tool found here:
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/quickstarts/label-tool
FormTrainingClient trainingClient = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
CustomFormModel model = await trainingClient.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : false, "My Model").WaitForCompletionAsync();
// Proceed with the custom form recognition.
FormRecognizerClient client = new FormRecognizerClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
#region Snippet:FormRecognizerSampleRecognizeCustomFormsFromUri
#if SNIPPET
string modelId = "<modelId>";
Uri formUri = < formUri >;
#else
Uri formUri = FormRecognizerTestEnvironment.CreateUri("Form_1.jpg");
string modelId = model.ModelId;
#endif
RecognizeCustomFormsOperation operation = await client.StartRecognizeCustomFormsFromUriAsync(modelId, formUri);
Response <RecognizedFormCollection> operationResponse = await operation.WaitForCompletionAsync();
RecognizedFormCollection forms = operationResponse.Value;
foreach (RecognizedForm form in forms)
{
Console.WriteLine($"Form of type: {form.FormType}");
if (form.FormTypeConfidence.HasValue)
{
Console.WriteLine($"Form type confidence: {form.FormTypeConfidence.Value}");
}
Console.WriteLine($"Form was analyzed with model with ID: {form.ModelId}");
foreach (FormField field in form.Fields.Values)
{
Console.WriteLine($"Field '{field.Name}': ");
if (field.LabelData != null)
{
Console.WriteLine($" Label: '{field.LabelData.Text}'");
}
Console.WriteLine($" Value: '{field.ValueData.Text}'");
Console.WriteLine($" Confidence: '{field.Confidence}'");
}
}
#endregion
// Delete the model on completion to clean environment.
await trainingClient.DeleteModelAsync(model.ModelId);
}
public async Task TrainModelWithFormsAndLabels()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
#region Snippet:FormRecognizerSampleTrainModelWithFormsAndLabels
// For this sample, you can use the training forms found in the `trainingFiles` folder.
// Upload the forms to your storage container and then generate a container SAS URL. Note
// that a container URI without SAS is accepted only when the container is public or has a
// managed identity configured.
//
// For instructions to set up forms for training in an Azure Blob Storage Container, please see:
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/build-training-data-set#upload-your-training-data
// For instructions to create a label file for your training forms, please see:
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/label-tool?tabs=v2-1
#if SNIPPET
Uri trainingFileUri = new Uri("<trainingFileUri>");
#else
Uri trainingFileUri = new Uri(TestEnvironment.BlobContainerSasUrlV2);
#endif
string modelName = "My Model with labels";
FormTrainingClient client = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
TrainingOperation operation = await client.StartTrainingAsync(trainingFileUri, useTrainingLabels : true, modelName);
Response <CustomFormModel> operationResponse = await operation.WaitForCompletionAsync();
CustomFormModel model = operationResponse.Value;
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {model.ModelId}");
Console.WriteLine($" Model name: {model.ModelName}");
Console.WriteLine($" Model Status: {model.Status}");
Console.WriteLine($" Is composed model: {model.Properties.IsComposedModel}");
Console.WriteLine($" Training model started on: {model.TrainingStartedOn}");
Console.WriteLine($" Training model completed on: {model.TrainingCompletedOn}");
foreach (CustomFormSubmodel submodel in model.Submodels)
{
Console.WriteLine($"Submodel Form Type: {submodel.FormType}");
foreach (CustomFormModelField field in submodel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Accuracy != null)
{
Console.Write($", Accuracy: {field.Accuracy}");
}
Console.WriteLine("");
}
}
#endregion
// Delete the model on completion to clean environment.
await client.DeleteModelAsync(model.ModelId);
}
public async Task OutputModelsTrainedWithLabels()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
string formFilePath = FormRecognizerTestEnvironment.CreatePath("Form_1.jpg");
FormRecognizerClient client = new FormRecognizerClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
FormTrainingClient trainingClient = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
// Model trained with labels
CustomFormModel modelTrainedWithLabels = await trainingClient.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : true, new TrainingOptions()
{
ModelDisplayName = "My Model with labels"
}).WaitForCompletionAsync();
using (FileStream stream = new FileStream(formFilePath, FileMode.Open))
{
RecognizedFormCollection forms = await client.StartRecognizeCustomFormsAsync(modelTrainedWithLabels.ModelId, stream).WaitForCompletionAsync();
// With a form recognized by a model trained with labels, the 'field.Name' key will be the label
// that you gave it at training time.
// Note that Label data is not returned for model trained with labels, as the trained model
// contains this information and therefore the service returns the value of the recognized label.
Console.WriteLine("---------Recognizing forms using models trained with labels---------");
foreach (RecognizedForm form in forms)
{
Console.WriteLine($"Form of type: {form.FormType}");
Console.WriteLine($"Form has form type confidence: {form.FormTypeConfidence.Value}");
Console.WriteLine($"Form was analyzed with model with ID: {form.ModelId}");
foreach (FormField field in form.Fields.Values)
{
Console.WriteLine($"Field {field.Name}: ");
Console.WriteLine($" Value: '{field.ValueData.Text}");
Console.WriteLine($" Confidence: '{field.Confidence}");
}
}
// Find labeled field.
foreach (RecognizedForm form in forms)
{
// Find the specific labeled field.
Console.WriteLine("Find the value for a specific labeled field:");
if (form.Fields.TryGetValue("VendorName", out FormField field))
{
Console.WriteLine($"VendorName is {field.ValueData.Text}");
}
// Find labeled fields with specific words
Console.WriteLine("Find the value for labeled field with specific words:");
form.Fields.Where(kv => kv.Key.StartsWith("Ven"))
.ToList().ForEach(v => Console.WriteLine($"{v.Key} is {v.Value.ValueData.Text}"));
form.Fields.Where(kv => kv.Key.Contains("Name"))
.ToList().ForEach(v => Console.WriteLine($"{v.Key} is {v.Value.ValueData.Text}"));
}
}
}
public override async Task SetupAsync()
{
var trainingClient = new FormTrainingClient(new Uri(Endpoint), new AzureKeyCredential(ApiKey));
var op = await trainingClient.StartTrainingAsync(new Uri(BlobContainerSasUrl), useTrainingLabels : false);
CustomFormModel model = await op.WaitForCompletionAsync();
_modelId = model.ModelId;
}
public async Task CopyModel()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
Uri trainingFileUri = new Uri(TestEnvironment.BlobContainerSasUrl);
string resourceId = TestEnvironment.TargetResourceId;
string resourceRegion = TestEnvironment.TargetResourceRegion;
#region Snippet:FormRecognizerSampleCreateCopySourceClient
//@@ string endpoint = "<source_endpoint>";
//@@ string apiKey = "<source_apiKey>";
var sourcecredential = new AzureKeyCredential(apiKey);
var sourceClient = new FormTrainingClient(new Uri(endpoint), sourcecredential);
#endregion
// For the purpose of this sample, we are going to create a trained model to copy. Please note that
// if you already have a model, this is not necessary.
//@@ Uri trainingFileUri = <trainingFileUri>;
TrainingOperation operation = await sourceClient.StartTrainingAsync(trainingFileUri, useTrainingLabels : false);
Response <CustomFormModel> operationResponse = await operation.WaitForCompletionAsync();
CustomFormModel model = operationResponse.Value;
string modelId = model.ModelId;
#region Snippet:FormRecognizerSampleCreateCopyTargetClient
//@@ string endpoint = "<target_endpoint>";
//@@ string apiKey = "<target_apiKey>";
var targetCredential = new AzureKeyCredential(apiKey);
var targetClient = new FormTrainingClient(new Uri(endpoint), targetCredential);
#endregion
#region Snippet:FormRecognizerSampleGetCopyAuthorization
//@@ string resourceId = "<resourceId>";
//@@ string resourceRegion = "<region>";
CopyAuthorization targetAuth = await targetClient.GetCopyAuthorizationAsync(resourceId, resourceRegion);
#endregion
#region Snippet:FormRecognizerSampleToJson
string jsonTargetAuth = targetAuth.ToJson();
#endregion
#region Snippet:FormRecognizerSampleFromJson
CopyAuthorization targetCopyAuth = CopyAuthorization.FromJson(jsonTargetAuth);
#endregion
#region Snippet:FormRecognizerSampleCopyModel
//@@ string modelId = "<source_modelId>";
CustomFormModelInfo newModel = await sourceClient.StartCopyModelAsync(modelId, targetCopyAuth).WaitForCompletionAsync();
Console.WriteLine($"Original model ID => {modelId}");
Console.WriteLine($"Copied model ID => {newModel.ModelId}");
#endregion
}
// </snippet_analyze_response>
// <snippet_manage>
private static async Task ManageModels(
FormTrainingClient trainingClient, string trainingFileUrl)
{
// </snippet_manage>
// <snippet_manage_model_count>
// Check number of models in the FormRecognizer account,
// and the maximum number of models that can be stored.
AccountProperties accountProperties = trainingClient.GetAccountProperties();
Console.WriteLine($"Account has {accountProperties.CustomModelCount} models.");
Console.WriteLine($"It can have at most {accountProperties.CustomModelLimit} models.");
// </snippet_manage_model_count>
// <snippet_manage_model_list>
Pageable <CustomFormModelInfo> models = trainingClient.GetCustomModels();
foreach (CustomFormModelInfo modelInfo in models)
{
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {modelInfo.ModelId}");
Console.WriteLine($" Model Status: {modelInfo.Status}");
Console.WriteLine($" Training model started on: {modelInfo.TrainingStartedOn}");
Console.WriteLine($" Training model completed on: {modelInfo.TrainingCompletedOn}");
}
// </snippet_manage_model_list>
// <snippet_manage_model_get>
// Create a new model to store in the account
CustomFormModel model = await trainingClient.StartTrainingAsync(
new Uri(trainingFileUrl)).WaitForCompletionAsync();
// Get the model that was just created
CustomFormModel modelCopy = trainingClient.GetCustomModel(model.ModelId);
Console.WriteLine($"Custom Model {modelCopy.ModelId} recognizes the following form types:");
foreach (CustomFormSubmodel submodel in modelCopy.Submodels)
{
Console.WriteLine($"Submodel Form Type: {submodel.FormType}");
foreach (CustomFormModelField field in submodel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Label != null)
{
Console.Write($", FieldLabel: {field.Label}");
}
Console.WriteLine("");
}
}
// </snippet_manage_model_get>
// <snippet_manage_model_delete>
// Delete the model from the account.
trainingClient.DeleteModel(model.ModelId);
}
public async Task ManageCustomModels()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
#region Snippet:FormRecognizerSample6ManageCustomModels
FormTrainingClient client = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
// Check number of models in the FormRecognizer account, and the maximum number of models that can be stored.
AccountProperties accountProperties = client.GetAccountProperties();
Console.WriteLine($"Account has {accountProperties.CustomModelCount} models.");
Console.WriteLine($"It can have at most {accountProperties.CustomModelLimit} models.");
// List the first ten or fewer models currently stored in the account.
Pageable <CustomFormModelInfo> models = client.GetCustomModels();
foreach (CustomFormModelInfo modelInfo in models.Take(10))
{
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {modelInfo.ModelId}");
Console.WriteLine($" Model Status: {modelInfo.Status}");
Console.WriteLine($" Created On: {modelInfo.CreatedOn}");
Console.WriteLine($" Last Modified: {modelInfo.LastModified}");
}
// Create a new model to store in the account
CustomFormModel model = await client.StartTrainingAsync(new Uri(trainingFileUrl)).WaitForCompletionAsync();
// Get the model that was just created
CustomFormModel modelCopy = client.GetCustomModel(model.ModelId);
Console.WriteLine($"Custom Model {modelCopy.ModelId} recognizes the following form types:");
foreach (CustomFormSubModel subModel in modelCopy.Models)
{
Console.WriteLine($"SubModel Form Type: {subModel.FormType}");
foreach (CustomFormModelField field in subModel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Label != null)
{
Console.Write($", FieldLabel: {field.Label}");
}
Console.WriteLine("");
}
}
// Delete the model from the account.
client.DeleteModel(model.ModelId);
#endregion
}
/// <summary>
/// For testing purposes, we are training our models using the client library functionalities.
/// Please note that models can also be trained using a graphical user interface
/// such as the Form Recognizer Labeling Tool found here:
/// <a href="https://docs.microsoft.com/azure/cognitive-services/form-recognizer/quickstarts/label-tool"/>.
/// </summary>
private async Task <string> GetModelIdAsync(bool useLabels = false)
{
FormTrainingClient trainingClient = InstrumentClient(new FormTrainingClient(_endpoint, _credential));
TrainingOperation trainedModel = await trainingClient.StartTrainingAsync(_containerUri, useLabels);
await trainedModel.WaitForCompletionAsync();
Assert.IsTrue(trainedModel.HasValue);
return(trainedModel.Value.ModelId);
}
/// <summary>
/// Trains a model using the specified <see cref="FormTrainingClient"/> and the specified set of training files. A
/// <see cref="DisposableTrainedModel"/> instance is returned, from which the model ID can be obtained. Upon disposal,
/// the associated model will be deleted.
/// </summary>
/// <param name="trainingClient">The client to use for training and for deleting the model upon disposal.</param>
/// <param name="trainingFilesUri">An externally accessible Azure storage blob container Uri.</param>
/// <param name="useTrainingLabels">If <c>true</c>, use a label file created in the <link-to-label-tool-doc> to provide training-time labels for training a model. If <c>false</c>, the model will be trained from forms only.</param>
/// <param name="modelName">Optional model name.</param>
/// <returns>A <see cref="DisposableTrainedModel"/> instance from which the trained model ID can be obtained.</returns>
public static async Task <DisposableTrainedModel> TrainModelAsync(FormTrainingClient trainingClient, Uri trainingFilesUri, bool useTrainingLabels, string modelName = default)
{
TrainingOperation operation = await trainingClient.StartTrainingAsync(trainingFilesUri, useTrainingLabels, modelName);
await operation.WaitForCompletionAsync();
Assert.IsTrue(operation.HasValue);
Assert.AreEqual(CustomFormModelStatus.Ready, operation.Value.Status);
return(new DisposableTrainedModel(trainingClient, operation.Value.ModelId));
}
private static async Task AnalyzeDynamicCustomForm(FormRecognizerClient recognizerClient, string trainingFileUrl, string formUrl)
{
RecognizeCustomFormsOptions options = new RecognizeCustomFormsOptions();
//train model
FormTrainingClient trainingClient = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
CustomFormModel model = await trainingClient.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : false,
$"VIS-Dynamic-Model-{DateTime.Now.ToShortDateString()}-{DateTime.Now.ToLongTimeString()}").WaitForCompletionAsync();
//string modelId = inModelID;
string modelId = model.ModelId;
//recognize form
RecognizeCustomFormsOperation operation = await recognizerClient.StartRecognizeCustomFormsFromUriAsync(modelId, new Uri(formUrl));
Response <RecognizedFormCollection> operationResponse = await operation.WaitForCompletionAsync();
RecognizedFormCollection forms = operationResponse.Value;
foreach (RecognizedForm form in forms)
{
returnString += $"Form of type: {form.FormType}{Environment.NewLine}";
foreach (FormField field in form.Fields.Values)
{
returnString += $"Field '{field.Name}: ";
if (field.LabelData != null)
{
returnString += $" Label: '{field.LabelData.Text}";
}
returnString += $" Value: '{field.ValueData.Text}";
returnString += $" Confidence: '{field.Confidence}{Environment.NewLine}";
}
returnString += $"Table data:{Environment.NewLine}";
foreach (FormPage page in form.Pages)
{
for (int i = 0; i < page.Tables.Count; i++)
{
FormTable table = page.Tables[i];
//Console.WriteLine($"Table {i} has {table.RowCount} rows and {table.ColumnCount} columns.");
foreach (FormTableCell cell in table.Cells)
{
returnString += $" Cell ({cell.RowIndex}, {cell.ColumnIndex}) contains {(cell.IsHeader ? "header" : "text")}: '{cell.Text}'{Environment.NewLine}";
}
}
}
}
// Delete the model on completion to clean environment.
await trainingClient.DeleteModelAsync(model.ModelId);
}
public async Task RecognizeCustomFormsFromFile()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
// Firstly, create a trained model we can use to recognize the custom form. Please note that
// models can also be trained using a graphical user interface such as the Form Recognizer
// Labeling Tool found here:
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/quickstarts/label-tool
FormTrainingClient trainingClient = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
CustomFormModel model = await trainingClient.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : false, new TrainingOptions()
{
ModelName = "My Model"
}).WaitForCompletionAsync();
// Proceed with the custom form recognition.
FormRecognizerClient client = new FormRecognizerClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
string formFilePath = FormRecognizerTestEnvironment.CreatePath("Form_1.jpg");
string modelId = model.ModelId;
using (FileStream stream = new FileStream(formFilePath, FileMode.Open))
{
RecognizedFormCollection forms = await client.StartRecognizeCustomFormsAsync(modelId, stream).WaitForCompletionAsync();
foreach (RecognizedForm form in forms)
{
Console.WriteLine($"Form of type: {form.FormType}");
Console.WriteLine($"Form was analyzed with model with ID: {form.ModelId}");
foreach (FormField field in form.Fields.Values)
{
Console.WriteLine($"Field '{field.Name}: ");
if (field.LabelData != null)
{
Console.WriteLine($" Label: '{field.LabelData.Text}");
}
Console.WriteLine($" Value: '{field.ValueData.Text}");
Console.WriteLine($" Confidence: '{field.Confidence}");
}
}
}
// Delete the model on completion to clean environment.
await trainingClient.DeleteModelAsync(model.ModelId);
}
public async Task TrainModelWithForms()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
#region Snippet:FormRecognizerSampleTrainModelWithForms
// For this sample, you can use the training forms found in the `trainingFiles` folder.
// Upload the forms to your storage container and then generate a container SAS URL.
// For instructions on setting up forms for training in an Azure Storage Blob Container, see
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/build-training-data-set#upload-your-training-data
#if SNIPPET
Uri trainingFileUri = < trainingFileUri >;
#else
Uri trainingFileUri = new Uri(TestEnvironment.BlobContainerSasUrlV2);
#endif
FormTrainingClient client = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
TrainingOperation operation = await client.StartTrainingAsync(trainingFileUri, useTrainingLabels : false, "My Model");
Response <CustomFormModel> operationResponse = await operation.WaitForCompletionAsync();
CustomFormModel model = operationResponse.Value;
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {model.ModelId}");
Console.WriteLine($" Model name: {model.ModelName}");
Console.WriteLine($" Model Status: {model.Status}");
Console.WriteLine($" Is composed model: {model.Properties.IsComposedModel}");
Console.WriteLine($" Training model started on: {model.TrainingStartedOn}");
Console.WriteLine($" Training model completed on: {model.TrainingCompletedOn}");
foreach (CustomFormSubmodel submodel in model.Submodels)
{
Console.WriteLine($"Submodel Form Type: {submodel.FormType}");
foreach (CustomFormModelField field in submodel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Label != null)
{
Console.Write($", FieldLabel: {field.Label}");
}
Console.WriteLine("");
}
}
#endregion
// Delete the model on completion to clean environment.
await client.DeleteModelAsync(model.ModelId);
}
private static async Task ManageModels(
FormTrainingClient trainingClient, string trainingFileUrl)
{
// Check number of models in the FormRecognizer account,
// and the maximum number of models that can be stored.
AccountProperties accountProperties = trainingClient.GetAccountProperties();
Console.WriteLine($"Account has {accountProperties.CustomModelCount} models.");
Console.WriteLine($"It can have at most {accountProperties.CustomModelLimit}" +
$" models.");
// List the first ten or fewer models currently stored in the account.
Pageable <CustomFormModelInfo> models = trainingClient.GetCustomModels();
foreach (CustomFormModelInfo modelInfo in models.Take(10))
{
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {modelInfo.ModelId}");
Console.WriteLine($" Model Status: {modelInfo.Status}");
Console.WriteLine($" Created On: {modelInfo.TrainingStartedOn}");
Console.WriteLine($" Last Modified: {modelInfo.TrainingCompletedOn}");
}
// Create a new model to store in the account
CustomFormModel model = await trainingClient.StartTrainingAsync(
new Uri(trainingFileUrl), useTrainingLabels : false).WaitForCompletionAsync();
// Get the model that was just created
CustomFormModel modelCopy = trainingClient.GetCustomModel(model.ModelId);
Console.WriteLine($"Custom Model {modelCopy.ModelId} recognizes the following" +
" form types:");
foreach (CustomFormSubmodel subModel in modelCopy.Submodels)
{
Console.WriteLine($"SubModel Form Type: {subModel.FormType}");
foreach (CustomFormModelField field in subModel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Label != null)
{
Console.Write($", FieldLabel: {field.Label}");
}
Console.WriteLine("");
}
}
// Delete the model from the account.
trainingClient.DeleteModel(model.ModelId);
}
public async Task TrainModelWithFormsAndLabels()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
#region Snippet:FormRecognizerSampleTrainModelWithFormsAndLabels
// For this sample, you can use the training forms found in the `trainingFiles` folder.
// Upload the forms to your storage container and then generate a container SAS URL.
// For instructions to set up forms for training in an Azure Storage Blob Container, please see:
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/build-training-data-set#upload-your-training-data
// For instructions to create a label file for your training forms, please see:
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/quickstarts/label-tool
FormTrainingClient client = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
CustomFormModel model = await client.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : true, new TrainingOptions()
{
ModelName = "My Model with labels"
}).WaitForCompletionAsync();
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {model.ModelId}");
Console.WriteLine($" Model name: {model.ModelName}");
Console.WriteLine($" Model Status: {model.Status}");
Console.WriteLine($" Is composed model: {model.Properties.IsComposedModel}");
Console.WriteLine($" Training model started on: {model.TrainingStartedOn}");
Console.WriteLine($" Training model completed on: {model.TrainingCompletedOn}");
foreach (CustomFormSubmodel submodel in model.Submodels)
{
Console.WriteLine($"Submodel Form Type: {submodel.FormType}");
foreach (CustomFormModelField field in submodel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Accuracy != null)
{
Console.Write($", Accuracy: {field.Accuracy}");
}
Console.WriteLine("");
}
}
#endregion
// Delete the model on completion to clean environment.
await client.DeleteModelAsync(model.ModelId);
}
/// <summary>
/// For testing purposes, we are training our models using the client library functionalities.
/// Please note that models can also be trained using a graphical user interface
/// such as the Form Recognizer Labeling Tool found here:
/// <a href="https://docs.microsoft.com/azure/cognitive-services/form-recognizer/quickstarts/label-tool"/>.
/// </summary>
/// <param name="useLabels">If <c>true</c>, use a label file created in the <link-to-label-tool-doc> to provide training-time labels for training a model. If <c>false</c>, the model will be trained from forms only.</param>
/// <returns>The identifier of the trained model.</returns>
private async Task <string> GetModelIdAsync(bool useLabels = false)
{
var trainingFiles = new Uri(TestEnvironment.BlobContainerSasUrl);
FormTrainingClient client = CreateInstrumentedFormTrainingClient();
TrainingOperation trainedModel;
// TODO: sanitize body and enable body recording here.
using (Recording.DisableRequestBodyRecording())
{
trainedModel = await client.StartTrainingAsync(trainingFiles, useLabels);
}
await trainedModel.WaitForCompletionAsync();
Assert.IsTrue(trainedModel.HasValue);
Assert.AreEqual(CustomFormModelStatus.Ready, trainedModel.Value.Status);
return(trainedModel.Value.ModelId);
}
public async Task TrainModelWithFormsAndLabels()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
#region Snippet:FormRecognizerSample5TrainModelWithFormsAndLabels
// For instructions to set up forms for training in an Azure Storage Blob Container, please see:
// https://docs.microsoft.com/en-us/azure/cognitive-services/form-recognizer/quickstarts/curl-train-extract#train-a-form-recognizer-model
// For instructions to create a label file for your training forms, please see:
// https://docs.microsoft.com/en-us/azure/cognitive-services/form-recognizer/quickstarts/label-tool
FormTrainingClient client = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
CustomFormModel model = await client.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : true).WaitForCompletionAsync();
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {model.ModelId}");
Console.WriteLine($" Model Status: {model.Status}");
Console.WriteLine($" Requested on: {model.RequestedOn}");
Console.WriteLine($" Completed on: {model.CompletedOn}");
foreach (CustomFormSubModel subModel in model.Models)
{
Console.WriteLine($"SubModel Form Type: {subModel.FormType}");
foreach (CustomFormModelField field in subModel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Accuracy != null)
{
Console.Write($", Accuracy: {field.Accuracy}");
}
Console.WriteLine("");
}
}
#endregion
// Delete the model on completion to clean environment.
client.DeleteModel(model.ModelId);
}
// </snippet_maintask>
// <snippet_train>
// Train model using training form data (pdf, jpg, png files)
private static async Task <string> TrainModelAsync(
FormTrainingClient formTrainingClient, string trainingDataUrl)
{
if (!Uri.IsWellFormedUriString(trainingDataUrl, UriKind.Absolute))
{
Console.WriteLine("\nInvalid trainingDataUrl:\n{0} \n", trainingDataUrl);
return(null);
}
try
{
CustomFormModel result = await formTrainingClient.StartTrainingAsync(new Uri(trainingDataUrl), useTrainingLabels : false).WaitForCompletionAsync();
DisplayModelStatus(result);
return(result.ModelId);
}
catch (RequestFailedException e)
{
Console.WriteLine("Train Model : " + e.Message);
return(null);
}
}
public async Task TrainModelWithForms()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
#region Snippet:FormRecognizerSample4TrainModelWithForms
// For instructions on setting up forms for training in an Azure Storage Blob Container, see
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/quickstarts/curl-train-extract#train-a-form-recognizer-model
FormTrainingClient client = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
CustomFormModel model = await client.StartTrainingAsync(new Uri(trainingFileUrl)).WaitForCompletionAsync();
Console.WriteLine($"Custom Model Info:");
Console.WriteLine($" Model Id: {model.ModelId}");
Console.WriteLine($" Model Status: {model.Status}");
Console.WriteLine($" Created On: {model.CreatedOn}");
Console.WriteLine($" Last Modified: {model.LastModified}");
foreach (CustomFormSubModel subModel in model.Models)
{
Console.WriteLine($"SubModel Form Type: {subModel.FormType}");
foreach (CustomFormModelField field in subModel.Fields.Values)
{
Console.Write($" FieldName: {field.Name}");
if (field.Label != null)
{
Console.Write($", FieldLabel: {field.Label}");
}
Console.WriteLine("");
}
}
#endregion
// Delete the model on completion to clean environment.
client.DeleteModel(model.ModelId);
}
public async Task OutputModelsTrainedWithDynamicRowsTables()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.TableDynamicRowsContainerSasUrlV2;
string formFilePath = FormRecognizerTestEnvironment.CreatePath("label_table_dynamic_rows1.pdf");
FormRecognizerClient client = new FormRecognizerClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
FormTrainingClient trainingClient = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
// Model trained with labeled table with dynamic rows.
CustomFormModel modelTrainedWithLabels = await trainingClient.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : true).WaitForCompletionAsync();
using (FileStream stream = new FileStream(formFilePath, FileMode.Open))
{
RecognizedFormCollection forms = await client.StartRecognizeCustomFormsAsync(modelTrainedWithLabels.ModelId, stream).WaitForCompletionAsync();
Console.WriteLine("---------Recognized labeled table with dynamic rows---------");
foreach (RecognizedForm form in forms)
{
foreach (FormField field in form.Fields.Values)
{
/// Substitute "table" for the label given to the table tag during training
/// (if different than sample training docs).
if (field.Name == "table")
{
if (field.Value.ValueType == FieldValueType.List)
{
var table = field.Value.AsList();
//columns
for (int i = 0; i < table.Count; i++)
{
Console.WriteLine($"Row {i+1}:");
var row = table[i].Value.AsDictionary();
foreach (var colValues in row)
{
Console.Write($" Col {colValues.Key}. Value: ");
if (colValues.Value != null)
{
var rowContent = colValues.Value;
if (rowContent.Value.ValueType == FieldValueType.String)
{
Console.WriteLine($"'{rowContent.Value.AsString()}'");
}
}
else
{
Console.WriteLine("Empty cell.");
}
}
}
}
}
else
{
Console.WriteLine($"Field {field.Name}: ");
Console.WriteLine($" Value: '{field.ValueData.Text}");
Console.WriteLine($" Confidence: '{field.Confidence}");
}
}
}
}
}
public async Task RecognizeCustomFormsFromFile()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
// Firstly, create a trained model we can use to recognize the custom form. Please note that
// models can also be trained using a graphical user interface such as the Form Recognizer
// Labeling Tool found here:
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/label-tool?tabs=v2-1
FormTrainingClient trainingClient = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
CustomFormModel model = await trainingClient.StartTrainingAsync(new Uri(trainingFileUrl), useTrainingLabels : false, "My Model").WaitForCompletionAsync();
// Proceed with the custom form recognition.
FormRecognizerClient client = new FormRecognizerClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
#region Snippet:FormRecognizerRecognizeCustomFormsFromFile
#if SNIPPET
string modelId = "<modelId>";
string filePath = "<filePath>";
#else
string filePath = FormRecognizerTestEnvironment.CreatePath("Form_1.jpg");
string modelId = model.ModelId;
#endif
using var stream = new FileStream(filePath, FileMode.Open);
var options = new RecognizeCustomFormsOptions()
{
IncludeFieldElements = true
};
RecognizeCustomFormsOperation operation = await client.StartRecognizeCustomFormsAsync(modelId, stream, options);
Response <RecognizedFormCollection> operationResponse = await operation.WaitForCompletionAsync();
RecognizedFormCollection forms = operationResponse.Value;
foreach (RecognizedForm form in forms)
{
Console.WriteLine($"Form of type: {form.FormType}");
Console.WriteLine($"Form was analyzed with model with ID: {form.ModelId}");
foreach (FormField field in form.Fields.Values)
{
Console.WriteLine($"Field '{field.Name}': ");
if (field.LabelData != null)
{
Console.WriteLine($" Label: '{field.LabelData.Text}'");
}
Console.WriteLine($" Value: '{field.ValueData.Text}'");
Console.WriteLine($" Confidence: '{field.Confidence}'");
}
// Iterate over tables, lines, and selection marks on each page
foreach (var page in form.Pages)
{
for (int i = 0; i < page.Tables.Count; i++)
{
Console.WriteLine($"Table {i+1} on page {page.Tables[i].PageNumber}");
foreach (var cell in page.Tables[i].Cells)
{
Console.WriteLine($" Cell[{cell.RowIndex}][{cell.ColumnIndex}] has text '{cell.Text}' with confidence {cell.Confidence}");
}
}
Console.WriteLine($"Lines found on page {page.PageNumber}");
foreach (var line in page.Lines)
{
Console.WriteLine($" Line {line.Text}");
}
if (page.SelectionMarks.Count != 0)
{
Console.WriteLine($"Selection marks found on page {page.PageNumber}");
foreach (var selectionMark in page.SelectionMarks)
{
Console.WriteLine($" Selection mark is '{selectionMark.State}' with confidence {selectionMark.Confidence}");
}
}
}
}
#endregion
// Delete the model on completion to clean environment.
await trainingClient.DeleteModelAsync(model.ModelId);
}
public async Task CreateComposedModel()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
string trainingFileUrl = TestEnvironment.BlobContainerSasUrl;
FormTrainingClient client = new FormTrainingClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
string purchaseOrderOfficeSuppliesUrl = trainingFileUrl;
string purchaseOrderOfficeEquipmentUrl = trainingFileUrl;
string purchaseOrderFurnitureUrl = trainingFileUrl;
string purchaseOrderCleaningSuppliesUrl = trainingFileUrl;
#region Snippet:FormRecognizerSampleTrainVariousModels
// For this sample, you can use the training forms found in the `trainingFiles` folder.
// Upload the forms to your storage container and then generate a container SAS URL.
// For instructions on setting up forms for training in an Azure Storage Blob Container, see
// https://docs.microsoft.com/azure/cognitive-services/form-recognizer/build-training-data-set#upload-your-training-data
//@@ string purchaseOrderOfficeSuppliesUrl = "<purchaseOrderOfficeSupplies>";
//@@ string purchaseOrderOfficeEquipmentUrl = "<purchaseOrderOfficeEquipment>";
//@@ string purchaseOrderFurnitureUrl = "<purchaseOrderFurniture>";
//@@ string purchaseOrderCleaningSuppliesUrl = "<purchaseOrderCleaningSupplies>";
CustomFormModel purchaseOrderOfficeSuppliesModel = (await client.StartTrainingAsync(new Uri(purchaseOrderOfficeSuppliesUrl), useTrainingLabels: true, "Purchase order - Office supplies").WaitForCompletionAsync()).Value;
CustomFormModel purchaseOrderOfficeEquipmentModel = (await client.StartTrainingAsync(new Uri(purchaseOrderOfficeEquipmentUrl), useTrainingLabels: true, "Purchase order - Office Equipment").WaitForCompletionAsync()).Value;
CustomFormModel purchaseOrderFurnitureModel = (await client.StartTrainingAsync(new Uri(purchaseOrderFurnitureUrl), useTrainingLabels: true, "Purchase order - Furniture").WaitForCompletionAsync()).Value;
CustomFormModel purchaseOrderCleaningSuppliesModel = (await client.StartTrainingAsync(new Uri(purchaseOrderCleaningSuppliesUrl), useTrainingLabels: true, "Purchase order - Cleaning Supplies").WaitForCompletionAsync()).Value;
#endregion
#region Snippet:FormRecognizerSampleCreateComposedModel
List <string> modelIds = new List <string>()
{
purchaseOrderOfficeSuppliesModel.ModelId,
purchaseOrderOfficeEquipmentModel.ModelId,
purchaseOrderFurnitureModel.ModelId,
purchaseOrderCleaningSuppliesModel.ModelId
};
CustomFormModel purchaseOrderModel = (await client.StartCreateComposedModelAsync(modelIds, "Composed Purchase order").WaitForCompletionAsync()).Value;
Console.WriteLine($"Purchase Order Model Info:");
Console.WriteLine($" Is composed model: {purchaseOrderModel.Properties.IsComposedModel}");
Console.WriteLine($" Model Id: {purchaseOrderModel.ModelId}");
Console.WriteLine($" Model name: {purchaseOrderModel.ModelName}");
Console.WriteLine($" Model Status: {purchaseOrderModel.Status}");
Console.WriteLine($" Create model started on: {purchaseOrderModel.TrainingStartedOn}");
Console.WriteLine($" Create model completed on: {purchaseOrderModel.TrainingCompletedOn}");
#endregion
#region Snippet:FormRecognizerSampleSubmodelsInComposedModel
Dictionary <string, List <TrainingDocumentInfo> > trainingDocsPerModel = purchaseOrderModel.TrainingDocuments.GroupBy(doc => doc.ModelId).ToDictionary(g => g.Key, g => g.ToList());
Console.WriteLine($"The purchase order model is based on {purchaseOrderModel.Submodels.Count} model{(purchaseOrderModel.Submodels.Count > 1 ? "s" : "")}.");
foreach (CustomFormSubmodel model in purchaseOrderModel.Submodels)
{
Console.WriteLine($" Model Id: {model.ModelId}");
Console.WriteLine(" The documents used to trained the model are: ");
foreach (var doc in trainingDocsPerModel[model.ModelId])
{
Console.WriteLine($" {doc.Name}");
}
}
#endregion
string purchaseOrderFilePath = FormRecognizerTestEnvironment.CreatePath("Form_1.jpg");
#region Snippet:FormRecognizerSampleRecognizeCustomFormWithComposedModel
//@@ string purchaseOrderFilePath = "<purchaseOrderFilePath>";
FormRecognizerClient formRecognizerClient = client.GetFormRecognizerClient();
RecognizedFormCollection forms;
using (FileStream stream = new FileStream(purchaseOrderFilePath, FileMode.Open))
{
forms = await formRecognizerClient.StartRecognizeCustomFormsAsync(purchaseOrderModel.ModelId, stream).WaitForCompletionAsync();
// Find labeled field.
foreach (RecognizedForm form in forms)
{
// Setting an arbitrary confidence level
if (form.FormTypeConfidence.Value > 0.9)
{
if (form.Fields.TryGetValue("Total", out FormField field))
{
Console.WriteLine($"Total value in the form `{form.FormType}` is `{field.ValueData.Text}`");
}
}
else
{
Console.WriteLine("Unable to recognize form.");
}
}
}
#endregion
// Delete the models on completion to clean environment.
await client.DeleteModelAsync(purchaseOrderOfficeSuppliesModel.ModelId).ConfigureAwait(false);
await client.DeleteModelAsync(purchaseOrderOfficeEquipmentModel.ModelId).ConfigureAwait(false);
await client.DeleteModelAsync(purchaseOrderFurnitureModel.ModelId).ConfigureAwait(false);
await client.DeleteModelAsync(purchaseOrderCleaningSuppliesModel.ModelId).ConfigureAwait(false);
await client.DeleteModelAsync(purchaseOrderModel.ModelId).ConfigureAwait(false);
}
