Improve your workflow with built-in OCR

What is OCR?

What is the purpose of OCR in Causeway Ermeo?

How to use OCR in Causeway Ermeo?

Use OCR via API in a form

Use OCR in your databases

Use and implementation of Lectur’IA in Causeway Ermeo

1. What is OCR?

Optical character recognition (OCR) is a feature that automatically extracts text from an image or scanned document (PDF, photo, etc.). This allows you to search, copy, or process the text content without having to type it manually.

2. What is the purpose of OCR in Causeway Ermeo?

OCR (Optical Character Recognition) saves you time and improves data accuracy by automating document reading. You can use it to:

• Automatically extract information from a data sheet or paper document.
• Pre-fill fields on a form by scanning or photographing a document.
• Preserve images while making their content accessible and indexable in your databases.

3. How to use OCR in Causeway Ermeo?

First, you must request to enable OCR for your workspace.

You can contact your Account Manager directly or submit a support ticket.

There are two ways to use OCR in Causeway Ermeo for two purposes: via API brick or via databases.

Let's take the example of this dynamic display in a factory:

Via API:

In your editing studio, add a photo tile available in the task tiles:

To avoid having to come back to this, you can already copy the value of the brick:

Next, go to the Workflows tiles and drag and drop the API tile. Then click on ‘Configure request’ represented by a ⚙️ icon.

You will now be taken to the request configuration section, where you can select ‘Ermeo Workflows’:

By clicking on “➡️ Next”, you will be taken to the query settings page. Here is the information you need to fill in:

`Méthode : POST`

`URL de la requête : /ocr_analyze_file_Zpv4X2hJ508wt7hF8EEKEEDnyut69cvr`

`Contenu de la requête : JSON`

As shown below:

By clicking on ‘➡️ Next’ again, you will be asked to enter the body and headers of the request. Here is the information you need to fill in:

Request headers: leave blank

Request body:

{
   "file":{
      "id":"##Image tag copied beforehand:id##"
   },
   "questions":{
      "Nom de l’attribut que vous souhaitez récupérer":"Name of the attribute you want, question to be entered in English, allowing the image to be queried"
   }
}

Example below with our use case:

{
   "file":{
      "id":"##image_LXsgT0zW:id##"
   },
   "questions":{
      "Productions":"How much asbestos has been produced since 1 January?"
   }
}

By clicking on ‘➡️ Next’ again, you can provide an example photo to visualise the results by clicking on ‘Enter tags’:

Here, we add the photo from our use case, and we can retrieve the output information following OCR:

{ "file": { "id": "##image_LXsgT0zW:id##"
 
	}, 
	
	"questions": { "name": "How much asbestos has been produced since 1 January?" 
	},
	
	"productions": { "name": "573 446"
	}, 
	
	"confidence": { "name": 99 
	}
	 
}

You have configured your API brick for OCR!

Now open a text brick and enter the OCR tag in the default value:

Now, click on the pen:

You can now specify what you want to retrieve by indicating it in the JSON Path, here:

answers.Productions

You can now test directly with the preview.

Example:

Via databases:

Once OCR has been activated on your workspace, two databases will be created in your workspace:

• OCR Logs database
• OCR Questions database

The names of these databases cannot be changed.

The OCR Logs database will simply be used to store and retain logs. It can be used to:

• Diagnose problems (errors, defects)
• Retrieve information (file, date)

The OCR Questions Database will be used to record questions related to your image analysis.

To return to our example:

Four attributes to indicate:

Next, as suggested by the attribute “OCR - Database”, you can create the database (if you haven't already done so) that will receive your image.

Here, still using the same example:

A minimum of three attributes will be required to perform the basic OCR analysis.

Once the resource has been created manually or via a form, here is the expected result:

You are now ready to use Lectur'IA within Causeway Ermeo on your own. Please do not hesitate to contact us via support if you have any questions about its use.