AmazonRekognition-Java对接
AmazonRekognition类似于百度EasyDL，是一款图像分析服务，检测图像分类及图像内容等。
1、项目创建
项目创建的方式有一下三种方式：
1：AWS官网创建
2：CLI创建
3：编码创建（Java）
AWS官网创建文档见：
链接：https://pan.baidu.com/s/1WMnUIjNug53YEzWMXENVKw
提取码：flny
2、依赖
<!--AmazonRekognition依赖--> <dependency> <groupId>com.amazonaws</groupId> <artifactId>aws-java-sdk-rekognition</artifactId> <version>1.11.759</version> </dependency>
3、功能代码
1、客户端验证连接
客户端连接方式及问题见：https://www.cnblogs.com/StefanieYang/p/13212508.html
2、功能
public class RekognitionClient{ private final static String regoin = "us-east-1"; //区域设置 private final static String projectArn = ""; //项目Arn private final static String versionName = ""; //模型 private final static String projectVersionArn = ""; //项目模型Arn private final static int minInferenceUnits = 1; //最小推理数 private final static String projectName = ""; //项目名称 // Rekognition客户端生成/连接 public static AmazonRekognition getRekognition(){ AWSCredentials credentials = new ProfileCredentialsProvider().getCredentials(); AmazonRekognition amazonRekognition = AmazonRekognitionClientBuilder.standard() .withCredentials(new AWSStaticCredentialsProvider(credentials)) .build(); return amazonRekognition; } // Create public static void createProject(AmazonRekognition amazonRekognition){ try{ CreateProjectRequest request = new CreateProjectRequest().withProjectName(projectName);//创建请求 CreateProjectResult result = amazonRekognition.createProject(request); log.info("Project ARN:" + result.getProjectArn()); }catch(Exception e){ log.error(e.getMessage()); } } // Delete public static void deleteProject(AmazonRekognition amazonRekognition){ try{ DeleteProjectRequest request = new DeleteProjectRequest().withPojectArn(projectArn); DeleteProjectResult result = amazonRekognition.deleteProject(request); log.info("Project Status:" + result.getStatus()); }catch(Exception e){ log.error(e.getMessage()); } } // Start public static void startProject(AmazonRekognition amazonRekognition){ try{ StartProjectVersionRequest request = new StartProjectVersionRequest().withProjectVersionArn(projectVersionArn).withMinInferenceUnits(minInferenceUnits); StartProjectVersionResult result = amazonRekognition.startProjectVersion(request); log.info("Project Status:" + result.getStatus()); }catch(Exception e){ log.error(e.getMessage()); } } // Stop public static void stopProject(AmazonRekognition amazonRekognition){ try{ StopProjectVersionRequest request = new StopProjectVersionRequest().withProjectVersionArn(projectVersionArn); StopProjectVersionResult result = amazonRekognition.stopProjectVersion(request); log.info("Project Status:" + result.getStatus()); }catch(Exception e){ log.error(e.getMessage()); } } // LocalImage Upload Detect（非自定义项目） public static void localImageDetect(String imagePath,AmazonRekognition amazonRekognition){ ByteBuffer imageBytes = null; InputStream in = null; DetectLabelsRequest request = null; Image image; try{ in = new FileInputStream(new File(imagePath)); try{ imageBytes = ByteBuffer.wrap(IOUtils.toByteArraay(in)); request = new DetectLabelsRequest().withImage(new Image().withBytes(imageBytes)) .withMaxLabels(10).withMinconfidence(77F); }catch(IOException e){ log.error("输入流转ByteBuffer失败！") } }catch(FileNotFoundException e){ log.error("文件不存在！")； } DetectLabelsResult result = amazonRekognition.detectLabels(request); List<Label> list = result.getLabels(); for(Label label : list){ log.info("标签名："+label.getName+"标签Confidence:"+label.getConfidence()); } if(in!=null){ try{ in.close(); }catch(IOException e){ log.error(e.getMessage()); } } } // Bucket Image Detect(非自定义项目) public static void bucketImageDetect(String key,String bucketName,AmazonRekognition amazonRekognition){ DetectLabelsRequest request = new DetectLabelsRequest(); request.withImage(new Image().withS3Object(new S3Object().withName(key).withBucket(bucketName))).withMaxLabels(10).withConfidence(75F); try{ DetectLabelsResult result = amazonRekognition.detectLabes(request); List<Label> list = result.getLabels(); for(Label label : list){ log.info("标签名："+label.getName+"标签Confidence"+label.getConfidence()); } }catch(IOException e){ log.error(e.getMessage()); } } }
AmazonS3 File Detect
package com.stefanie.sun.bean.AWS.Rekognition; import com.amazonaws.services.rekognition.AmazonRekognition; import com.amazonaws.services.rekognition.model.*; import com.amazonaws.services.rekognition.model.Image; import com.amazonaws.services.s3.AmazonS3; import com.amazonaws.services.s3.model.S3ObjectInputStream; import lombok.extern.slf4j.Slf4j; import javax.imageio.ImageIO; import javax.swing.*; import java.awt.*; import java.awt.image.BufferedImage; import java.util.List; @Slf4j public class DisplayCustomLabels extends JPanel { private final static String projectVersionArn = "your projectVersionArn"; private static final long serialVersionUID = 1L; BufferedImage image; static int scale; DetectCustomLabelsResult result; public DisplayCustomLabels(DetectCustomLabelsResult labelsResult, BufferedImage bufImage) throws Exception { super(); scale = 4; // increase to shrink image size. result = labelsResult; image = bufImage; } // Draws the bounding box around the detected faces. public void paintComponent(Graphics g) { float left = 0; float top = 0; int height = image.getHeight(this); int width = image.getWidth(this); Graphics2D g2d = (Graphics2D) g; // Create a Java2D version of g. // Draw the image. g2d.drawImage(image, 0, 0, width / scale, height / scale, this); g2d.setColor(new Color(0, 212, 0)); // Iterate through faces and display bounding boxes. List<CustomLabel> customLabels = result.getCustomLabels(); for (CustomLabel customLabel : customLabels) { if (customLabel.getGeometry() != null) { BoundingBox box = customLabel.getGeometry().getBoundingBox(); left = width * box.getLeft(); top = height * box.getTop(); g2d.drawString(customLabel.getName(), left / scale, top / scale); g2d.drawRect(Math.round(left / scale), Math.round(top / scale), Math.round((width * box.getWidth()) / scale), Math.round((height * box.getHeight())) / scale); } } } public static void main(String arg[]) throws Exception { String photo = "assets/ifree-zy-test1.0/1592904311/img_20191109_171935.png"; String bucket = "custom-labels-console-us-east-1-5de227ce63"; float minConfidence = 90; int height = 0; int width = 0; // Get the image from an S3 Bucket // AmazonS3 s3client = AmazonS3ClientBuilder.defaultClient(); AmazonS3 s3client = S3client.amazonS36(); //见：https://www.cnblogs.com/StefanieYang/p/13229128.html 客户端连接方式第6种 com.amazonaws.services.s3.model.S3Object s3object = s3client.getObject(bucket, photo); S3ObjectInputStream inputStream = s3object.getObjectContent(); BufferedImage image = ImageIO.read(inputStream); DetectCustomLabelsRequest request = new DetectCustomLabelsRequest() .withProjectVersionArn(projectVersionArn) .withImage(new Image().withS3Object(new S3Object().withName(photo).withBucket(bucket))) .withMinConfidence(minConfidence); width = image.getWidth(); height = image.getHeight(); // Call DetectFaces AmazonRekognition amazonRekognition = RelognitionClient.getRekognition(); //见上面代码中获取方式 DetectCustomLabelsResult result = amazonRekognition.detectCustomLabels(request); //Show the bounding box info for each face. List<CustomLabel> customLabels = result.getCustomLabels(); log.info("----------" + request.toString() + "----------" + result.toString() + "----------" + customLabels .size() + "----------" + customLabels.toString() + "----------"); for (CustomLabel customLabel : customLabels) { if (customLabel.getGeometry() != null) { BoundingBox box = customLabel.getGeometry().getBoundingBox(); float left = width * box.getLeft(); float top = height * box.getTop(); System.out.println("Custom Label:"); System.out.println("Left: " + String.valueOf((int) left)); System.out.println("Top: " + String.valueOf((int) top)); System.out.println("Label Width: " + String.valueOf((int) (width * box.getWidth()))); System.out.println("Label Height: " + String.valueOf((int) (height * box.getHeight()))); System.out.println(); } } // Create frame and panel./download file // JFrame frame = new JFrame("RotateImage"); // frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); // DisplayCustomLabels panel = new DisplayCustomLabels(result, image); // panel.setPreferredSize(new Dimension(image.getWidth() / scale, // image.getHeight() / scale)); // frame.setContentPane(panel); // frame.pack(); // frame.setVisible(true); } }