Getting started with SAP Leonardo Machine Learning Foundation

[Former Member]

You want to know how to actually start using SAP Leonardo Machine Learning? The Machine Learning foundation offers a wide range of functional services, from image to text classification that are easy to consume. You can find a first overview of all these services available on the SAP API Business Hub and try them out through APIs calls. The only prerequisites you will need are the SAP Cloud Platform Tools for Java in your Eclipse IDE, SAP Cloud Platform Software  Development Kit, Eclipse (they can be set up and configured with this tutorial).

 

Steps

1. Open Eclipse and create new project

• Select „File“ menu > „New“ in drop-down > „Dynamic Web Project“ in drop-down.

 



2. Start the project

• Set project name to “MLConsumption” and choose "Finish".
  Check that Target Runtime is set to “Java Web Tomcat 8” (or “Java Web Tomcat 7”).

3. Create new Servlet

• Right click on project and select “New” in drop-down > “Servlet”.

4. Set class name

• Set Java packages to “mlconsumption" and the Class name to “MLConsumptionServlet”.
  Click on “Next”.

5. Set URL Mapping

• Click on “MLConsumptionServlet” > "Edit". Set Pattern to “/”. Choose “OK" and on “Finish”.

6. Paste code into Eclipse

• Replace code in method doGet (line 29 and 30) with
  

      	// create a new URLConnection object to configure our HTTP request
  
      	URLConnection connection = new URL("https://sandbox.api.sap.com/ml/prodimgclassifier/inference_sync").openConnection();
  
      	connection.setDoOutput(true); // send data through this connection --> HTTP POST request
  
      	
  
      	// user authentication and authorization
  
     	    connection.setRequestProperty("APIKey", "<API_KEY>");
  
      	 
  
  	    // random boundary between different files of multipart/form-data request
  
      	String boundary = Long.toHexString(System.currentTimeMillis());
  
      	// line separator required by multipart/form-data format
  
      	String CRLF = "\r\n";
  
      	// for sending files we need multipart/form-data
  
      	connection.setRequestProperty("Content-Type", "multipart/form-data; boundary=" + boundary);
  
  
  
      	// character encoding used in our http requests
  
      	String charset = java.nio.charset.StandardCharsets.UTF_8.name();
  
      	// the image file we want to classify
  
  		String path = "";
  
  
  
  		    OutputStream output = connection.getOutputStream();
  
  		    PrintWriter writer = new PrintWriter(new OutputStreamWriter(output, charset), true);
  
  		) {
  
  			 // send image file
  
  		    writer.append("--" + boundary).append(CRLF);
  
  		    writer.append("Content-Disposition: form-data; name=\"files\"; filename=\"" + imgFile.getName() + "\"").append(CRLF);
  
  		    writer.append("Content-Type: " + URLConnection.guessContentTypeFromName(imgFile.getName())).append(CRLF);
  
  		    writer.append("Content-Transfer-Encoding: binary").append(CRLF);
  
  		    writer.append(CRLF).flush();
  
  
  
  		    Files.copy(imgFile.toPath(), output);
  
  		    output.flush(); // need to flush before continuing with writer
  
  		    writer.append(CRLF);
  
  
  
  		    // mark end of multipart/form-data
  
  		    writer.append("--" + boundary + "--").append(CRLF).flush();
  
  		}
  
  
  
      	// performing the http request against the Leonardo ML service endpoint
  
      	InputStream mlServiceResponse = connection.getInputStream();
  
     
  
  		try (Scanner scanner = new Scanner(mlServiceResponse)) {
  
  			// reading the response from the Leonardo ML service endpoint
  
  		    String responseBody = scanner.useDelimiter("\\A").next();
  
  		    // sending a response to the client
  
  		    userResp.getWriter().println(responseBody);
  
  		}
  
  ​

  
  

 

7.  Add missing imports

• Insert the following code below line 8:
  

  import java.net.URISyntaxException;
  
  import java.net.URL;
  
  import java.net.URLConnection;
  
  import java.io.File;
  
  import java.io.InputStream;
  
  import java.io.OutputStream;
  
  import java.io.PrintWriter;
  
  import java.io.OutputStreamWriter;
  
  import java.util.Scanner;
  
  import java.nio.file.Files;
  
  ​

  
   

8. Login to API Business Hub

• Open API Business Hub in your browser and choose "APIs". Click on “Login” (alternatively click “Register” and follow registration wizard). 

9. Select Product Image Classification

• Search for “SAP Leonardo Machine Learning”. Select “SAP Leonardo Machine Learning -Functional Services” and click on “Artifacts” >  “Product Image Classification API”.

10. Generate API Key

• Switch back to Browser, click on key icon and “Copy API Key”.

11. Insert API Key

• Return to Eclipse and select <API_KEY> in line 40, then Press [CTRL]+[c].

12. Add product image to the project

• Download “smartphone.jpg” and drop image into the “mlconsumption” package.

(Source)

 

13. Deploy and Execute Project

• To deploy and execute browse to https://www.sap.com/developer/tutorials/hcp-java-basic-app.html and follow: Step 12 (for local deployment), Step 15 (for deployment on SAP Cloud Platform).