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This tutorial shows the features of the Azure Cognitive Services Computer Vision REST API.
Explore a Java Swing application that uses the Computer Vision REST API to perform optical character recognition (OCR), create smart-cropped thumbnails, plus detect, categorize, tag, and describe visual features, including faces, in an image. This example lets you submit an image URL for analysis or processing. You can use this open source example as a template for building your own app in Java to use the Computer Vision REST API.
This tutorial will cover how to use Computer Vision to:
- Analyze an image
- Identify a natural or artificial landmark in an image
- Identify a celebrity in an image
- Create a quality thumbnail from an image
- Read printed text in an image
- Read handwritten text in an image
The Java Swing form application has already been written but has no functionality. In this tutorial, you add the code specific to the Computer Vision REST API to complete the application's functionality.
This tutorial has been developed using the NetBeans IDE. Specifically, the Java SE version of NetBeans, which you can download here.
Before creating the example, you must subscribe to Computer Vision API which is part of Azure Cognitive Services. For subscription and key management details, see Subscriptions. Both the primary and secondary keys are valid to use in this tutorial.
- Go to the Cognitive Services Java Computer Vision Tutorial repository.
- Click the Clone or download button.
- Click Download ZIP to download a .zip file of the tutorial project.
There is no need to extract the contents of the .zip file because NetBeans imports the project from the .zip file.
Import the cognitive-services-java-computer-vision-tutorial-master.zip file into NetBeans.
- In NetBeans, click File > Import Project > From ZIP.... The Import Project(s) from ZIP dialog box appears.
- In the ZIP File: field, click the Browse button to locate the cognitive-services-java-computer-vision-tutorial-master.zip file, then click Open.
- Click Import from the Import Project(s) from ZIP dialog box.
- In the Projects panel, expand ComputerVision > Source Packages > <default package>. Some versions of NetBeans use src instead of Source Packages > <default package>. In that case, expand src.
- Double-click MainFrame.java to load the file into the NetBeans editor. The Design tab of the MainFrame.java file appears.
- Click the Source tab to view the Java source code.
Press F6 to build and run the tutorial application.
In the tutorial application, click a tab to bring up the pane for that feature. The buttons have empty methods, so they do nothing.
At the bottom of the window are the fields Subscription Key and Subscription Region. These fields must be filled with a valid subscription key and the correct region for that subscription key.
Exit the tutorial application.
The Java Swing application is set up with six tabs. Each tab demonstrates a different function of Computer Vision (analyze, OCR, and so on). The six tutorial sections do not have interdependencies, so you can add one section, all six sections, or any subset. You can add the sections in any order.
The Analyze feature of Computer Vision scans an image for more than 2,000 recognizable objects, living things, scenery, and actions. Once the analysis is complete, Analyze returns a JSON object that describes the image with descriptive tags, color analysis, captions, and more.
To complete the Analyze feature of the tutorial application, perform the following steps:
The analyzeImageButtonActionPerformed event handler method clears the form, displays the image specified in the URL, then calls the AnalyzeImage method to analyze the image. When AnalyzeImage returns, the method displays the formatted JSON response in the Response text area, extracts the first caption from the JSONObject, and displays the caption and the confidence level that the caption is correct.
Copy and paste the following code into the analyzeImageButtonActionPerformed method.
Note
NetBeans won't let you paste to the method definition line (private void) or to the closing curly brace of that method. To copy the code, copy the lines between the method definition and the closing curly brace, and paste them over the contents of the method.
private void analyzeImageButtonActionPerformed(java.awt.event.ActionEvent evt) {
URL analyzeImageUrl;
// Clear out the previous image, response, and caption, if any.
analyzeImage.setIcon(new ImageIcon());
analyzeCaptionLabel.setText("");
analyzeResponseTextArea.setText("");
// Display the image specified in the text box.
try {
analyzeImageUrl = new URL(analyzeImageUriTextBox.getText());
BufferedImage bImage = ImageIO.read(analyzeImageUrl);
scaleAndShowImage(bImage, analyzeImage);
} catch(IOException e) {
analyzeResponseTextArea.setText("Error loading Analyze image: " + e.getMessage());
return;
}
// Analyze the image.
JSONObject jsonObj = AnalyzeImage(analyzeImageUrl.toString());
// A return of null indicates failure.
if (jsonObj == null) {
return;
}
// Format and display the JSON response.
analyzeResponseTextArea.setText(jsonObj.toString(2));
// Extract the text and confidence from the first caption in the description object.
if (jsonObj.has("description") && jsonObj.getJSONObject("description").has("captions")) {
JSONObject jsonCaption = jsonObj.getJSONObject("description").getJSONArray("captions").getJSONObject(0);
if (jsonCaption.has("text") && jsonCaption.has("confidence")) {
analyzeCaptionLabel.setText("Caption: " + jsonCaption.getString("text") +
" (confidence: " + jsonCaption.getDouble("confidence") + ").");
}
}
}
The AnalyzeImage method wraps the REST API call to analyze an image. The method returns a JSONObject describing the image, or null if there was an error.
Copy and paste the AnalyzeImage method to just underneath the analyzeImageButtonActionPerformed method.
/**
* Encapsulates the Microsoft Cognitive Services REST API call to analyze an image.
* @param imageUrl: The string URL of the image to analyze.
* @return: A JSONObject describing the image, or null if a runtime error occurs.
*/
private JSONObject AnalyzeImage(String imageUrl) {
try (CloseableHttpClient httpclient = HttpClientBuilder.create().build())
{
// Create the URI to access the REST API call for Analyze Image.
String uriString = uriBasePreRegion +
String.valueOf(subscriptionRegionComboBox.getSelectedItem()) +
uriBasePostRegion + uriBaseAnalyze;
URIBuilder builder = new URIBuilder(uriString);
// Request parameters. All of them are optional.
builder.setParameter("visualFeatures", "Categories,Description,Color,Adult");
builder.setParameter("language", "en");
// Prepare the URI for the REST API call.
URI uri = builder.build();
HttpPost request = new HttpPost(uri);
// Request headers.
request.setHeader("Content-Type", "application/json");
request.setHeader("Ocp-Apim-Subscription-Key", subscriptionKeyTextField.getText());
// Request body.
StringEntity reqEntity = new StringEntity("{\"url\":\"" + imageUrl + "\"}");
request.setEntity(reqEntity);
// Execute the REST API call and get the response entity.
HttpResponse response = httpclient.execute(request);
HttpEntity entity = response.getEntity();
// If we got a response, parse it and display it.
if (entity != null)
{
// Return the JSONObject.
String jsonString = EntityUtils.toString(entity);
return new JSONObject(jsonString);
} else {
// No response. Return null.
return null;
}
}
catch (Exception e)
{
// Display error message.
System.out.println(e.getMessage());
return null;
}
}
Press F6 to run the application. Put your subscription key into the Subscription Key field and verify that you are using the correct region in Subscription Region. Enter a URL to an image to analyze, then click the Analyze Image button to analyze an image and see the result.
The Landmark feature of Computer Vision analyzes an image for natural and artificial landmarks, such as mountains or famous buildings. Once the analysis is complete, Landmark returns a JSON object that identifies the landmarks found in the image.
To complete the Landmark feature of the tutorial application, perform the following steps:
The landmarkImageButtonActionPerformed event handler method clears the form, displays the image specified in the URL, then calls the LandmarkImage method to analyze the image. When LandmarkImage returns, the method displays the formatted JSON response in the Response text area, then extracts the first landmark name from the JSONObject and displays it on the window along with the confidence level that the landmark was identified correctly.
Copy and paste the following code into the landmarkImageButtonActionPerformed method.
Note
NetBeans won't let you paste to the method definition line (private void) or to the closing curly brace of that method. To copy the code, copy the lines between the method definition and the closing curly brace, and paste them over the contents of the method.
private void landmarkImageButtonActionPerformed(java.awt.event.ActionEvent evt) {
URL landmarkImageUrl;
// Clear out the previous image, response, and caption, if any.
landmarkImage.setIcon(new ImageIcon());
landmarkCaptionLabel.setText("");
landmarkResponseTextArea.setText("");
// Display the image specified in the text box.
try {
landmarkImageUrl = new URL(landmarkImageUriTextBox.getText());
BufferedImage bImage = ImageIO.read(landmarkImageUrl);
scaleAndShowImage(bImage, landmarkImage);
} catch(IOException e) {
landmarkResponseTextArea.setText("Error loading Landmark image: " + e.getMessage());
return;
}
// Identify the landmark in the image.
JSONObject jsonObj = LandmarkImage(landmarkImageUrl.toString());
// A return of null indicates failure.
if (jsonObj == null) {
return;
}
// Format and display the JSON response.
landmarkResponseTextArea.setText(jsonObj.toString(2));
// Extract the text and confidence from the first caption in the description object.
if (jsonObj.has("result") && jsonObj.getJSONObject("result").has("landmarks")) {
JSONObject jsonCaption = jsonObj.getJSONObject("result").getJSONArray("landmarks").getJSONObject(0);
if (jsonCaption.has("name") && jsonCaption.has("confidence")) {
landmarkCaptionLabel.setText("Caption: " + jsonCaption.getString("name") +
" (confidence: " + jsonCaption.getDouble("confidence") + ").");
}
}
}
The LandmarkImage method wraps the REST API call to analyze an image. The method returns a JSONObject describing the landmarks found in the image, or null if there was an error.
Copy and paste the LandmarkImage method to just underneath the landmarkImageButtonActionPerformed method.
/**
* Encapsulates the Microsoft Cognitive Services REST API call to identify a landmark in an image.
* @param imageUrl: The string URL of the image to process.
* @return: A JSONObject describing the image, or null if a runtime error occurs.
*/
private JSONObject LandmarkImage(String imageUrl) {
try (CloseableHttpClient httpclient = HttpClientBuilder.create().build())
{
// Create the URI to access the REST API call to identify a Landmark in an image.
String uriString = uriBasePreRegion +
String.valueOf(subscriptionRegionComboBox.getSelectedItem()) +
uriBasePostRegion + uriBaseLandmark;
URIBuilder builder = new URIBuilder(uriString);
// Request parameters. All of them are optional.
builder.setParameter("visualFeatures", "Categories,Description,Color");
builder.setParameter("language", "en");
// Prepare the URI for the REST API call.
URI uri = builder.build();
HttpPost request = new HttpPost(uri);
// Request headers.
request.setHeader("Content-Type", "application/json");
request.setHeader("Ocp-Apim-Subscription-Key", subscriptionKeyTextField.getText());
// Request body.
StringEntity reqEntity = new StringEntity("{\"url\":\"" + imageUrl + "\"}");
request.setEntity(reqEntity);
// Execute the REST API call and get the response entity.
HttpResponse response = httpclient.execute(request);
HttpEntity entity = response.getEntity();
// If we got a response, parse it and display it.
if (entity != null)
{
// Return the JSONObject.
String jsonString = EntityUtils.toString(entity);
return new JSONObject(jsonString);
} else {
// No response. Return null.
return null;
}
}
catch (Exception e)
{
// Display error message.
System.out.println(e.getMessage());
return null;
}
}
Press F6 to run the application. Put your subscription key into the Subscription Key field and verify that you are using the correct region in Subscription Region. Click the Landmark tab, enter a URL to an image of a landmark, then click the Analyze Image button to analyze an image and see the result.
The Celebrities feature of Computer Vision analyzes an image for famous people. Once the analysis is complete, Celebrities returns a JSON object that identifies the Celebrities found in the image.
To complete the Celebrities feature of the tutorial application, perform the following steps:
The celebritiesImageButtonActionPerformed event handler method clears the form, displays the image specified in the URL, then calls the CelebritiesImage method to analyze the image. When CelebritiesImage returns, the method displays the formatted JSON response in the Response text area, then extracts the first celebrity name from the JSONObject and displays the name on the window along with the confidence level that the celebrity was identified correctly.
Copy and paste the following code into the celebritiesImageButtonActionPerformed method.
Note
NetBeans won't let you paste to the method definition line (private void) or to the closing curly brace of that method. To copy the code, copy the lines between the method definition and the closing curly brace, and paste them over the contents of the method.
private void celebritiesImageButtonActionPerformed(java.awt.event.ActionEvent evt) {
URL celebritiesImageUrl;
// Clear out the previous image, response, and caption, if any.
celebritiesImage.setIcon(new ImageIcon());
celebritiesCaptionLabel.setText("");
celebritiesResponseTextArea.setText("");
// Display the image specified in the text box.
try {
celebritiesImageUrl = new URL(celebritiesImageUriTextBox.getText());
BufferedImage bImage = ImageIO.read(celebritiesImageUrl);
scaleAndShowImage(bImage, celebritiesImage);
} catch(IOException e) {
celebritiesResponseTextArea.setText("Error loading Celebrity image: " + e.getMessage());
return;
}
// Identify the celebrities in the image.
JSONObject jsonObj = CelebritiesImage(celebritiesImageUrl.toString());
// A return of null indicates failure.
if (jsonObj == null) {
return;
}
// Format and display the JSON response.
celebritiesResponseTextArea.setText(jsonObj.toString(2));
// Extract the text and confidence from the first caption in the description object.
if (jsonObj.has("result") && jsonObj.getJSONObject("result").has("celebrities")) {
JSONObject jsonCaption = jsonObj.getJSONObject("result").getJSONArray("celebrities").getJSONObject(0);
if (jsonCaption.has("name") && jsonCaption.has("confidence")) {
celebritiesCaptionLabel.setText("Caption: " + jsonCaption.getString("name") +
" (confidence: " + jsonCaption.getDouble("confidence") + ").");
}
}
}
The CelebritiesImage method wraps the REST API call to analyze an image. The method returns a JSONObject describing the celebrities found in the image, or null if there was an error.
Copy and paste the CelebritiesImage method to just underneath the celebritiesImageButtonActionPerformed method.
/**
* Encapsulates the Microsoft Cognitive Services REST API call to identify celebrities in an image.
* @param imageUrl: The string URL of the image to process.
* @return: A JSONObject describing the image, or null if a runtime error occurs.
*/
private JSONObject CelebritiesImage(String imageUrl) {
try (CloseableHttpClient httpclient = HttpClientBuilder.create().build())
{
// Create the URI to access the REST API call to identify celebrities in an image.
String uriString = uriBasePreRegion +
String.valueOf(subscriptionRegionComboBox.getSelectedItem()) +
uriBasePostRegion + uriBaseCelebrities;
URIBuilder builder = new URIBuilder(uriString);
// Request parameters. All of them are optional.
builder.setParameter("visualFeatures", "Categories,Description,Color");
builder.setParameter("language", "en");
// Prepare the URI for the REST API call.
URI uri = builder.build();
HttpPost request = new HttpPost(uri);
// Request headers.
request.setHeader("Content-Type", "application/json");
request.setHeader("Ocp-Apim-Subscription-Key", subscriptionKeyTextField.getText());
// Request body.
StringEntity reqEntity = new StringEntity("{\"url\":\"" + imageUrl + "\"}");
request.setEntity(reqEntity);
// Execute the REST API call and get the response entity.
HttpResponse response = httpclient.execute(request);
HttpEntity entity = response.getEntity();
// If we got a response, parse it and display it.
if (entity != null)
{
// Return the JSONObject.
String jsonString = EntityUtils.toString(entity);
return new JSONObject(jsonString);
} else {
// No response. Return null.
return null;
}
}
catch (Exception e)
{
// Display error message.
System.out.println(e.getMessage());
return null;
}
}
Press F6 to run the application. Put your subscription key into the Subscription Key field and verify that you are using the correct region in Subscription Region. Click the Celebrities tab, enter a URL to an image of a celebrity, then click the Analyze Image button to analyze an image and see the result.
The Thumbnail feature of Computer Vision generates a thumbnail from an image. By using the Smart Crop feature, the Thumbnail feature will identify the area of interest in an image and center the thumbnail on this area, to generate more aesthetically pleasing thumbnail images.
To complete the Thumbnail feature of the tutorial application, perform the following steps:
The thumbnailImageButtonActionPerformed event handler method clears the form, displays the image specified in the URL, then calls the getThumbnailImage method to create the thumbnail. When getThumbnailImage returns, the method displays the generated thumbnail.
Copy and paste the following code into the thumbnailImageButtonActionPerformed method.
Note
NetBeans won't let you paste to the method definition line (private void) or to the closing curly brace of that method. To copy the code, copy the lines between the method definition and the closing curly brace, and paste them over the contents of the method.
private void thumbnailImageButtonActionPerformed(java.awt.event.ActionEvent evt) {
URL thumbnailImageUrl;
JSONObject jsonError[] = new JSONObject[1];
// Clear out the previous image, response, and thumbnail, if any.
thumbnailSourceImage.setIcon(new ImageIcon());
thumbnailResponseTextArea.setText("");
thumbnailImage.setIcon(new ImageIcon());
// Display the image specified in the text box.
try {
thumbnailImageUrl = new URL(thumbnailImageUriTextBox.getText());
BufferedImage bImage = ImageIO.read(thumbnailImageUrl);
scaleAndShowImage(bImage, thumbnailSourceImage);
} catch(IOException e) {
thumbnailResponseTextArea.setText("Error loading image to thumbnail: " + e.getMessage());
return;
}
// Get the thumbnail for the image.
BufferedImage thumbnail = getThumbnailImage(thumbnailImageUrl.toString(), jsonError);
// A non-null value indicates error.
if (jsonError[0] != null) {
// Format and display the JSON error.
thumbnailResponseTextArea.setText(jsonError[0].toString(2));
return;
}
// Display the thumbnail.
if (thumbnail != null) {
scaleAndShowImage(thumbnail, thumbnailImage);
}
}
The getThumbnailImage method wraps the REST API call to analyze an image. The method returns a BufferedImage that contains the thumbnail, or null if there was an error. The error message will be returned in the first element of the jsonError string array.
Copy and paste the following getThumbnailImage method to just underneath the thumbnailImageButtonActionPerformed method.
/**
* Encapsulates the Microsoft Cognitive Services REST API call to create a thumbnail for an image.
* @param imageUrl: The string URL of the image to process.
* @return: A BufferedImage containing the thumbnail, or null if a runtime error occurs. In the case
* of an error, the error message will be returned in the first element of the jsonError string array.
*/
private BufferedImage getThumbnailImage(String imageUrl, JSONObject[] jsonError) {
try (CloseableHttpClient httpclient = HttpClientBuilder.create().build())
{
// Create the URI to access the REST API call to identify celebrities in an image.
String uriString = uriBasePreRegion +
String.valueOf(subscriptionRegionComboBox.getSelectedItem()) +
uriBasePostRegion + uriBaseThumbnail;
URIBuilder uriBuilder = new URIBuilder(uriString);
// Request parameters.
uriBuilder.setParameter("width", "100");
uriBuilder.setParameter("height", "150");
uriBuilder.setParameter("smartCropping", "true");
// Prepare the URI for the REST API call.
URI uri = uriBuilder.build();
HttpPost request = new HttpPost(uri);
// Request headers.
request.setHeader("Content-Type", "application/json");
request.setHeader("Ocp-Apim-Subscription-Key", subscriptionKeyTextField.getText());
// Request body.
StringEntity requestEntity = new StringEntity("{\"url\":\"" + imageUrl + "\"}");
request.setEntity(requestEntity);
// Execute the REST API call and get the response entity.
HttpResponse response = httpclient.execute(request);
HttpEntity entity = response.getEntity();
// Check for success.
if (response.getStatusLine().getStatusCode() == 200)
{
// Return the thumbnail.
return ImageIO.read(entity.getContent());
}
else
{
// Format and display the JSON error message.
String jsonString = EntityUtils.toString(entity);
jsonError[0] = new JSONObject(jsonString);
return null;
}
}
catch (Exception e)
{
String errorMessage = e.getMessage();
System.out.println(errorMessage);
jsonError[0] = new JSONObject(errorMessage);
return null;
}
}
Press F6 to run the application. Put your subscription key into the Subscription Key field and verify that you are using the correct region in Subscription Region. Click the Thumbnail tab, enter a URL to an image, then click the Generate Thumbnail button to analyze an image and see the result.
The Optical Character Recognition (OCR) feature of Computer Vision analyzes an image of printed text. After the analysis is complete, OCR returns a JSON object that contains the text and the location of the text in the image.
To complete the OCR feature of the tutorial application, perform the following steps:
The ocrImageButtonActionPerformed event handler method clears the form, displays the image specified in the URL, then calls the OcrImage method to analyze the image. When OcrImage returns, the method displays the detected text as formatted JSON in the Response text area.
Copy and paste the following code into the ocrImageButtonActionPerformed method.
Note
NetBeans won't let you paste to the method definition line (private void) or to the closing curly brace of that method. To copy the code, copy the lines between the method definition and the closing curly brace, and paste them over the contents of the method.
private void ocrImageButtonActionPerformed(java.awt.event.ActionEvent evt) {
URL ocrImageUrl;
// Clear out the previous image, response, and caption, if any.
ocrImage.setIcon(new ImageIcon());
ocrResponseTextArea.setText("");
// Display the image specified in the text box.
try {
ocrImageUrl = new URL(ocrImageUriTextBox.getText());
BufferedImage bImage = ImageIO.read(ocrImageUrl);
scaleAndShowImage(bImage, ocrImage);
} catch(IOException e) {
ocrResponseTextArea.setText("Error loading OCR image: " + e.getMessage());
return;
}
// Read the text in the image.
JSONObject jsonObj = OcrImage(ocrImageUrl.toString());
// A return of null indicates failure.
if (jsonObj == null) {
return;
}
// Format and display the JSON response.
ocrResponseTextArea.setText(jsonObj.toString(2));
}
The OcrImage method wraps the REST API call to analyze an image. The method returns a JSONObject of the JSON data returned from the call, or null if there was an error.
Copy and paste the following OcrImage method to just underneath the ocrImageButtonActionPerformed method.
/**
* Encapsulates the Microsoft Cognitive Services REST API call to read text in an image.
* @param imageUrl: The string URL of the image to process.
* @return: A JSONObject describing the image, or null if a runtime error occurs.
*/
private JSONObject OcrImage(String imageUrl) {
try (CloseableHttpClient httpclient = HttpClientBuilder.create().build())
{
// Create the URI to access the REST API call to read text in an image.
String uriString = uriBasePreRegion +
String.valueOf(subscriptionRegionComboBox.getSelectedItem()) +
uriBasePostRegion + uriBaseOcr;
URIBuilder uriBuilder = new URIBuilder(uriString);
// Request parameters.
uriBuilder.setParameter("language", "unk");
uriBuilder.setParameter("detectOrientation ", "true");
// Prepare the URI for the REST API call.
URI uri = uriBuilder.build();
HttpPost request = new HttpPost(uri);
// Request headers.
request.setHeader("Content-Type", "application/json");
request.setHeader("Ocp-Apim-Subscription-Key", subscriptionKeyTextField.getText());
// Request body.
StringEntity reqEntity = new StringEntity("{\"url\":\"" + imageUrl + "\"}");
request.setEntity(reqEntity);
// Execute the REST API call and get the response entity.
HttpResponse response = httpclient.execute(request);
HttpEntity entity = response.getEntity();
// If we got a response, parse it and display it.
if (entity != null)
{
// Return the JSONObject.
String jsonString = EntityUtils.toString(entity);
return new JSONObject(jsonString);
} else {
// No response. Return null.
return null;
}
}
catch (Exception e)
{
// Display error message.
System.out.println(e.getMessage());
return null;
}
}
Press F6 to run the application. Put your subscription key into the Subscription Key field and verify that you are using the correct region in Subscription Region. Click the OCR tab, enter a URL to an image of printed text, then click the Read Image button to analyze an image and see the result.
The Handwriting Recognition feature of Computer Vision analyzes an image of handwritten text. After the analysis is complete, Handwriting Recognition returns a JSON object that contains the text and the location of the text in the image.
To complete the Handwriting Recognition feature of the tutorial application, perform the following steps:
The handwritingImageButtonActionPerformed event handler method clears the form, displays the image specified in the URL, then calls the HandwritingImage method to analyze the image. When HandwritingImage returns, the method displays the detected text as formatted JSON in the Response text area.
Copy and paste the following code into the handwritingImageButtonActionPerformed method.
Note
NetBeans won't let you paste to the method definition line (private void) or to the closing curly brace of that method. To copy the code, copy the lines between the method definition and the closing curly brace, and paste them over the contents of the method.
private void handwritingImageButtonActionPerformed(java.awt.event.ActionEvent evt) {
URL handwritingImageUrl;
// Clear out the previous image, response, and caption, if any.
handwritingImage.setIcon(new ImageIcon());
handwritingResponseTextArea.setText("");
// Display the image specified in the text box.
try {
handwritingImageUrl = new URL(handwritingImageUriTextBox.getText());
BufferedImage bImage = ImageIO.read(handwritingImageUrl);
scaleAndShowImage(bImage, handwritingImage);
} catch(IOException e) {
handwritingResponseTextArea.setText("Error loading Handwriting image: " + e.getMessage());
return;
}
// Read the text in the image.
JSONObject jsonObj = HandwritingImage(handwritingImageUrl.toString());
// A return of null indicates failure.
if (jsonObj == null) {
return;
}
// Format and display the JSON response.
handwritingResponseTextArea.setText(jsonObj.toString(2));
}
The HandwritingImage method wraps the two REST API calls needed to analyze an image. Because handwriting recognition is a time consuming process, a two step process is used. The first call submits the image for processing; the second call retrieves the detected text when the processing is complete.
After the text is retrieved, the HandwritingImage method returns a JSONObject describing the text and the locations of the text, or null if there was an error.
Copy and paste the following HandwritingImage method to just underneath the handwritingImageButtonActionPerformed method.
/**
* Encapsulates the Microsoft Cognitive Services REST API call to read handwritten text in an image.
* @param imageUrl: The string URL of the image to process.
* @return: A JSONObject describing the image, or null if a runtime error occurs.
*/
private JSONObject HandwritingImage(String imageUrl) {
try (CloseableHttpClient textClient = HttpClientBuilder.create().build();
CloseableHttpClient resultClient = HttpClientBuilder.create().build())
{
// Create the URI to access the REST API call to read text in an image.
String uriString = uriBasePreRegion +
String.valueOf(subscriptionRegionComboBox.getSelectedItem()) +
uriBasePostRegion + uriBaseHandwriting;
URIBuilder uriBuilder = new URIBuilder(uriString);
// Request parameters.
uriBuilder.setParameter("handwriting", "true");
// Prepare the URI for the REST API call.
URI uri = uriBuilder.build();
HttpPost request = new HttpPost(uri);
// Request headers.
request.setHeader("Content-Type", "application/json");
request.setHeader("Ocp-Apim-Subscription-Key", subscriptionKeyTextField.getText());
// Request body.
StringEntity reqEntity = new StringEntity("{\"url\":\"" + imageUrl + "\"}");
request.setEntity(reqEntity);
// Execute the REST API call and get the response.
HttpResponse textResponse = textClient.execute(request);
// Check for success.
if (textResponse.getStatusLine().getStatusCode() != 202) {
// An error occurred. Return the JSON error message.
HttpEntity entity = textResponse.getEntity();
String jsonString = EntityUtils.toString(entity);
return new JSONObject(jsonString);
}
String operationLocation = null;
// The 'Operation-Location' in the response contains the URI to retrieve the recognized text.
Header[] responseHeaders = textResponse.getAllHeaders();
for(Header header : responseHeaders) {
if(header.getName().equals("Operation-Location"))
{
// This string is the URI where you can get the text recognition operation result.
operationLocation = header.getValue();
break;
}
}
// NOTE: The response may not be immediately available. Handwriting recognition is an
// async operation that can take a variable amount of time depending on the length
// of the text you want to recognize. You may need to wait or retry this operation.
//
// This example checks once per second for ten seconds.
JSONObject responseObj = null;
int i = 0;
do {
// Wait one second.
Thread.sleep(1000);
// Check to see if the operation completed.
HttpGet resultRequest = new HttpGet(operationLocation);
resultRequest.setHeader("Ocp-Apim-Subscription-Key", subscriptionKeyTextField.getText());
HttpResponse resultResponse = resultClient.execute(resultRequest);
HttpEntity responseEntity = resultResponse.getEntity();
if (responseEntity != null)
{
// Get the JSON response.
String jsonString = EntityUtils.toString(responseEntity);
responseObj = new JSONObject(jsonString);
}
}
while (i < 10 && responseObj != null &&
!responseObj.getString("status").equalsIgnoreCase("Succeeded"));
// If the operation completed, return the JSON object.
if (responseObj != null) {
return responseObj;
} else {
// Return null for timeout error.
System.out.println("Timeout error.");
return null;
}
}
catch (Exception e)
{
// Display error message.
System.out.println(e.getMessage());
return null;
}
}
To run the application, press F6. Put your subscription key into the Subscription Key field and verify that you are using the correct region in Subscription Region. Click the Read Handwritten Text tab, enter a URL to an image of handwritten text, then click the Read Image button to analyze an image and see the result.
In this guide, you used the Computer Vision REST API with Java to test many of the available image analysis features. Next, see the reference documentation to learn more about the APIs involved.