Azure AI services - Document intelligence - Extract Data from Forms:
Source:
Source:
https://microsoftlearning.github.io/AI-102-AIEngineer/
https://github.com/MicrosoftLearning/AI-102-AIEngineer
1. Create Azure AI services - Document intelligence in Azure Portal
2. Run Powershell script to create Storage account
3. Train the Model
4. Test the Model
Required Dlls;
dotnet add package Azure.Core --version 1.44.1
dotnet add package Azure.AI.FormRecognizer --version 4.1.0
dotnet add package Azure.AI.FormRecognizer --version 3.0.0
dotnet add package Tabulate.NET --version 1.0.5
2. Run Powershell script to create Storage account
@echo off
SETLOCAL ENABLEDELAYEDEXPANSION
rem Set variable values
set subscription_id=129b2bb6-asdf-asdf-83ba-85bf570bebca
set resource_group=rg1
set location=eastus
set expiry_date=2026-01-01T00:00:00Z
rem Get random numbers to create unique resource names
set unique_id=!random!!random!
rem Create a storage account in your Azure resource group
echo Creating storage...
call az storage account create --name ai102form!unique_id! --subscription !subscription_id!
--resource-group !resource_group! --location !location! --sku Standard_LRS
--encryption-services blob --default-action Allow --output none --allow-blob-public-access true
echo Uploading files...
rem Get storage key to create a container in the storage account
for /f "tokens=*" %%a in (
'az storage account keys list --subscription !subscription_id! --resource-group !resource_group!
--account-name ai102form!unique_id! --query
"[?keyName=='key1'].{keyName:keyName, permissions:permissions, value:value}"'
) do (
set key_json=!key_json!%%a
)
set key_string=!key_json:[ { "keyName": "key1", "permissions": "Full", "value": "=!
set AZURE_STORAGE_KEY=!key_string:" } ]=!
rem Create container
call az storage container create --account-name ai102form!unique_id! --name sampleforms
--auth-mode key --account-key %AZURE_STORAGE_KEY% --output none
rem Upload files from your local sampleforms folder to a container called sampleforms
in the storage account
rem Each file is uploaded as a blob
call az storage blob upload-batch -d sampleforms -s ./sample-forms
--account-name ai102form!unique_id! --auth-mode key --account-key %AZURE_STORAGE_KEY% --output none
rem Set a variable value for future use
set STORAGE_ACCT_NAME=ai102form!unique_id!
rem Get a Shared Access Signature (a signed URI that points to one or more storage resources)
for the blobs in sampleforms
for /f "tokens=*" %%a in (
'az storage container generate-sas --account-name ai102form!unique_id! --name sampleforms
--expiry !expiry_date! --permissions rwl'
) do (
set SAS_TOKEN=%%a
set SAS_TOKEN=!SAS_TOKEN:~1,-1!
)
set URI=https://!STORAGE_ACCT_NAME!.blob.core.windows.net/sampleforms?!SAS_TOKEN!
rem Print the generated Shared Access Signature URI, which is used by Azure Storage to
authorize access to the storage resource
echo -------------------------------------
echo SAS URI: !URI!
Run the code : dotnet run
OutPut:
3. Train the Model
using System;
using System.IO;
using System.Collections.Generic;
using System.Threading.Tasks;
using Microsoft.Extensions.Configuration;
// import namespaces
using Azure;
using Azure.AI.FormRecognizer;
using Azure.AI.FormRecognizer.Models;
using Azure.AI.FormRecognizer.Training;
namespace train_model
{
class Program
{
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"];
// "YOUR_FORM_RECOGNIZER_ENDPOINT"
string formEndpoint = "https://a.cognitiveservices.azure.com/";
// "YOUR_FORM_RECOGNIZER_KEY"
string formKey = "1E7gEDsZ2pUAiximoBAACYeBjFXJ3w3AAALACOGu5mm";
// "YOUR_SAS_URI"
string trainingStorageUri = "https://8IqQY2WOeCJRHTPFg%3D";
// 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: true)
.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($" Training model completed on: {model.TrainingCompletedOn}");
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
}
}
}
Run the code : dotnet run
OutPut:
4. Test the Model
using System;
using System.IO;
using System.Collections.Generic;
using System.Threading.Tasks;
using Microsoft.Extensions.Configuration;
// import namespaces
using Azure;
using Azure.AI.FormRecognizer;
using Azure.AI.FormRecognizer.Models;
using Azure.AI.FormRecognizer.Training;
namespace test_model
{
class Program
{
static async Task Main(string[] args)
{
try
{
// Get configuration settings from AppSettings
// IConfigurationBuilder builder = new ConfigurationBuilder().AddJsonFile("appsettings.json");
// IConfigurationRoot configuration = builder.Build();
// string formEndpoint = configuration["FormEndpoint"];
// string formKey = configuration["FormKey"];
// string modelId = configuration["ModelId"];
// "YOUR_FORM_RECOGNIZER_ENDPOINT";
string formEndpoint = "https://a.cognitiveservices.azure.com/";
// "YOUR_FORM_RECOGNIZER_KEY";
string formKey = "1E7gEDsZ2pUAiximAAALACOGu5mm";
// "YOUR_MODEL_ID";
string modelId = "7891e019-9cc2-48a9-a9e6-08ac408484c5";
// Authenticate Azure AI Document Intelligence Client
var credential = new AzureKeyCredential(formKey);
var recognizerClient = new FormRecognizerClient(new Uri(formEndpoint), credential);
// Get form url for testing
string image_file = "test1.jpg";
using (var image_data = File.OpenRead(image_file))
{
// Use trained model with new form
RecognizedFormCollection forms = await recognizerClient
.StartRecognizeCustomForms(modelId, image_data)
.WaitForCompletionAsync();
foreach (RecognizedForm form in forms)
{
Console.WriteLine($"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}");
}
}
}
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
}
}
}
OutPut:
