Analyzing an image loaded from a local file system - Amazon Rekognition

Analyzing an image loaded from a local file system

Amazon Rekognition Image operations can analyze images that are supplied as image bytes or images stored in an Amazon S3 bucket.

These topics provide examples of supplying image bytes to Amazon Rekognition Image API operations by using a file loaded from a local file system. You pass image bytes to an Amazon Rekognition API operation by using the Image input parameter. Within Image, you specify the Bytes property to pass base64-encoded image bytes.

Image bytes passed to an Amazon Rekognition API operation by using the Bytes input parameter must be base64 encoded. The AWS SDKs that these examples use automatically base64-encode images. You don't need to encode image bytes before calling an Amazon Rekognition API operation. For more information, see Image specifications.

In this example JSON request for DetectLabels, the source image bytes are passed in the Bytes input parameter.

{ "Image": { "Bytes": "/9j/4AAQSk....." }, "MaxLabels": 10, "MinConfidence": 77 }

The following examples use various AWS SDKs and the AWS CLI to call DetectLabels. For information about the DetectLabels operation response, see DetectLabels response.

For a client-side JavaScript example, see Using JavaScript.

To detect labels in a local image

  1. If you haven't already:

    1. Create or update an IAM user with AmazonRekognitionFullAccess and AmazonS3ReadOnlyAccess permissions. For more information, see Step 1: Set up an AWS account and create an IAM user.

    2. Install and configure the AWS CLI and the AWS SDKs. For more information, see Step 2: Set up the AWS CLI and AWS SDKs.

  2. Use the following examples to call the DetectLabels operation.

    Java

    The following Java example shows how to load an image from the local file system and detect labels by using the detectLabels AWS SDK operation. Change the value of photo to the path and file name of an image file (.jpg or .png format).

    //Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. //PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.) package aws.example.rekognition.image; import java.io.File; import java.io.FileInputStream; import java.io.InputStream; import java.nio.ByteBuffer; import java.util.List; import com.amazonaws.services.rekognition.AmazonRekognition; import com.amazonaws.services.rekognition.AmazonRekognitionClientBuilder; import com.amazonaws.AmazonClientException; import com.amazonaws.services.rekognition.model.AmazonRekognitionException; import com.amazonaws.services.rekognition.model.DetectLabelsRequest; import com.amazonaws.services.rekognition.model.DetectLabelsResult; import com.amazonaws.services.rekognition.model.Image; import com.amazonaws.services.rekognition.model.Label; import com.amazonaws.util.IOUtils; public class DetectLabelsLocalFile { public static void main(String[] args) throws Exception { String photo="input.jpg"; ByteBuffer imageBytes; try (InputStream inputStream = new FileInputStream(new File(photo))) { imageBytes = ByteBuffer.wrap(IOUtils.toByteArray(inputStream)); } AmazonRekognition rekognitionClient = AmazonRekognitionClientBuilder.defaultClient(); DetectLabelsRequest request = new DetectLabelsRequest() .withImage(new Image() .withBytes(imageBytes)) .withMaxLabels(10) .withMinConfidence(77F); try { DetectLabelsResult result = rekognitionClient.detectLabels(request); List <Label> labels = result.getLabels(); System.out.println("Detected labels for " + photo); for (Label label: labels) { System.out.println(label.getName() + ": " + label.getConfidence().toString()); } } catch (AmazonRekognitionException e) { e.printStackTrace(); } } }
    Python

    The following AWS SDK for Python example shows how to load an image from the local file system and call the detect_labels operation. Change the value of photo to the path and file name of an image file (.jpg or .png format).

    #Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. #PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.) import boto3 def detect_labels_local_file(photo): client=boto3.client('rekognition') with open(photo, 'rb') as image: response = client.detect_labels(Image={'Bytes': image.read()}) print('Detected labels in ' + photo) for label in response['Labels']: print (label['Name'] + ' : ' + str(label['Confidence'])) return len(response['Labels']) def main(): photo='photo' label_count=detect_labels_local_file(photo) print("Labels detected: " + str(label_count)) if __name__ == "__main__": main()
    .NET

    The following example shows how to load an image from the local file system and detect labels by using the DetectLabels operation. Change the value of photo to the path and file name of an image file (.jpg or .png format).

    //Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. //PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.) using System; using System.IO; using Amazon.Rekognition; using Amazon.Rekognition.Model; public class DetectLabelsLocalfile { public static void Example() { String photo = "input.jpg"; Amazon.Rekognition.Model.Image image = new Amazon.Rekognition.Model.Image(); try { using (FileStream fs = new FileStream(photo, FileMode.Open, FileAccess.Read)) { byte[] data = null; data = new byte[fs.Length]; fs.Read(data, 0, (int)fs.Length); image.Bytes = new MemoryStream(data); } } catch (Exception) { Console.WriteLine("Failed to load file " + photo); return; } AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(); DetectLabelsRequest detectlabelsRequest = new DetectLabelsRequest() { Image = image, MaxLabels = 10, MinConfidence = 77F }; try { DetectLabelsResponse detectLabelsResponse = rekognitionClient.DetectLabels(detectlabelsRequest); Console.WriteLine("Detected labels for " + photo); foreach (Label label in detectLabelsResponse.Labels) Console.WriteLine("{0}: {1}", label.Name, label.Confidence); } catch (Exception e) { Console.WriteLine(e.Message); } } }
    PHP

    The following AWS SDK for PHP example shows how to load an image from the local file system and call the DetectFaces API operation. Change the value of photo to the path and file name of an image file (.jpg or .png format).

    <?php //Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. //PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.) require 'vendor/autoload.php'; use Aws\Rekognition\RekognitionClient; $options = [ 'region' => 'us-west-2', 'version' => 'latest' ]; $rekognition = new RekognitionClient($options); // Get local image $photo = 'input.jpg'; $fp_image = fopen($photo, 'r'); $image = fread($fp_image, filesize($photo)); fclose($fp_image); // Call DetectFaces $result = $rekognition->DetectFaces(array( 'Image' => array( 'Bytes' => $image, ), 'Attributes' => array('ALL') ) ); // Display info for each detected person print 'People: Image position and estimated age' . PHP_EOL; for ($n=0;$n<sizeof($result['FaceDetails']); $n++){ print 'Position: ' . $result['FaceDetails'][$n]['BoundingBox']['Left'] . " " . $result['FaceDetails'][$n]['BoundingBox']['Top'] . PHP_EOL . 'Age (low): '.$result['FaceDetails'][$n]['AgeRange']['Low'] . PHP_EOL . 'Age (high): ' . $result['FaceDetails'][$n]['AgeRange']['High'] . PHP_EOL . PHP_EOL; } ?>
    Ruby

    This example displays a list of labels that were detected in the input image. Change the value of photo to the path and file name of an image file (.jpg or .png format).

    #Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. #PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.) # gem 'aws-sdk-rekognition' require 'aws-sdk-rekognition' credentials = Aws::Credentials.new( ENV['AWS_ACCESS_KEY_ID'], ENV['AWS_SECRET_ACCESS_KEY'] ) client = Aws::Rekognition::Client.new credentials: credentials photo = 'photo.jpg' path = File.expand_path(photo) # expand path relative to the current directory file = File.read(path) attrs = { image: { bytes: file }, max_labels: 10 } response = client.detect_labels attrs puts "Detected labels for: #{photo}" response.labels.each do |label| puts "Label: #{label.name}" puts "Confidence: #{label.confidence}" puts "Instances:" label['instances'].each do |instance| box = instance['bounding_box'] puts " Bounding box:" puts " Top: #{box.top}" puts " Left: #{box.left}" puts " Width: #{box.width}" puts " Height: #{box.height}" puts " Confidence: #{instance.confidence}" end puts "Parents:" label.parents.each do |parent| puts " #{parent.name}" end puts "------------" puts "" end
    Java V2

    This code is taken from the AWS Documentation SDK examples GitHub repository. See the full example here.

    public static void detectImageLabels(RekognitionClient rekClient, String sourceImage) { try { InputStream sourceStream = new URL("https://images.unsplash.com/photo-1557456170-0cf4f4d0d362?ixid=MnwxMjA3fDB8MHxzZWFyY2h8MXx8bGFrZXxlbnwwfHwwfHw%3D&ixlib=rb-1.2.1&w=1000&q=80").openStream(); // InputStream sourceStream = new FileInputStream(sourceImage); SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream); // Create an Image object for the source image. Image souImage = Image.builder() .bytes(sourceBytes) .build(); DetectLabelsRequest detectLabelsRequest = DetectLabelsRequest.builder() .image(souImage) .maxLabels(10) .build(); DetectLabelsResponse labelsResponse = rekClient.detectLabels(detectLabelsRequest); List<Label> labels = labelsResponse.labels(); System.out.println("Detected labels for the given photo"); for (Label label: labels) { System.out.println(label.name() + ": " + label.confidence().toString()); } } catch (RekognitionException | FileNotFoundException | MalformedURLException e) { System.out.println(e.getMessage()); System.exit(1); } catch (IOException e) { e.printStackTrace(); } }