Amazon Rekognition examples using SDK for C++

The following code examples show you how to perform actions and implement common scenarios by using the AWS SDK for C++ with Amazon Rekognition.

Actions are code excerpts from larger programs and must be run in context. While actions show you how to call individual service functions, you can see actions in context in their related scenarios.

Scenarios are code examples that show you how to accomplish specific tasks by calling multiple functions within a service or combined with other AWS services.

Each example includes a link to the complete source code, where you can find instructions on how to set up and run the code in context.

Get started

Hello Amazon Rekognition

The following code example shows how to get started using Amazon Rekognition.

SDK for C++

Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

Code for the CMakeLists.txt CMake file.

# Set the minimum required version of CMake for this project.
cmake_minimum_required(VERSION 3.13)

# Set the AWS service components used by this project.
set(SERVICE_COMPONENTS rekognition)

# Set this project's name.
project("hello_rekognition")

# Set the C++ standard to use to build this target.
# At least C++ 11 is required for the AWS SDK for C++.
set(CMAKE_CXX_STANDARD 11)

# Use the MSVC variable to determine if this is a Windows build.
set(WINDOWS_BUILD ${MSVC})

if (WINDOWS_BUILD) # Set the location where CMake can find the installed libraries for the AWS SDK.
    string(REPLACE ";" "/aws-cpp-sdk-all;" SYSTEM_MODULE_PATH "${CMAKE_SYSTEM_PREFIX_PATH}/aws-cpp-sdk-all")
    list(APPEND CMAKE_PREFIX_PATH ${SYSTEM_MODULE_PATH})
endif ()

# Find the AWS SDK for C++ package.
find_package(AWSSDK REQUIRED COMPONENTS ${SERVICE_COMPONENTS})

if (WINDOWS_BUILD AND AWSSDK_INSTALL_AS_SHARED_LIBS) 
     # Copy relevant AWS SDK for C++ libraries into the current binary directory for running and debugging.

     # set(BIN_SUB_DIR "/Debug") # If you are building from the command line, you may need to uncomment this 
                                    # and set the proper subdirectory to the executables' location.

     AWSSDK_CPY_DYN_LIBS(SERVICE_COMPONENTS "" ${CMAKE_CURRENT_BINARY_DIR}${BIN_SUB_DIR})
endif ()

add_executable(${PROJECT_NAME}
        hello_rekognition.cpp)

target_link_libraries(${PROJECT_NAME}
        ${AWSSDK_LINK_LIBRARIES})

Code for the hello_rekognition.cpp source file.

#include <aws/core/Aws.h>
#include <aws/rekognition/RekognitionClient.h>
#include <aws/rekognition/model/ListCollectionsRequest.h>
#include <iostream>

/*
 *  A "Hello Rekognition" starter application which initializes an Amazon Rekognition client and
 *  lists the Amazon Rekognition collections in the current account and region.
 *
 *  main function
 *
 *  Usage: 'hello_rekognition'
 *
 */

int main(int argc, char **argv) {
    Aws::SDKOptions options;
    //  Optional: change the log level for debugging.
    //  options.loggingOptions.logLevel = Aws::Utils::Logging::LogLevel::Debug;
    Aws::InitAPI(options); // Should only be called once.
    {
        Aws::Client::ClientConfiguration clientConfig;
        // Optional: Set to the AWS Region (overrides config file).
        // clientConfig.region = "us-east-1";

        Aws::Rekognition::RekognitionClient rekognitionClient(clientConfig);
        Aws::Rekognition::Model::ListCollectionsRequest request;
        Aws::Rekognition::Model::ListCollectionsOutcome outcome =
                rekognitionClient.ListCollections(request);

        if (outcome.IsSuccess()) {
            const Aws::Vector<Aws::String>& collectionsIds = outcome.GetResult().GetCollectionIds();
            if (!collectionsIds.empty()) {
                std::cout << "collectionsIds: " << std::endl;
                for (auto &collectionId : collectionsIds) {
                    std::cout << "- " << collectionId << std::endl;
                }
            } else {
                std::cout << "No collections found" << std::endl;
            }
        } else {
            std::cerr << "Error with ListCollections: " << outcome.GetError()
                      << std::endl;
        }
    }


    Aws::ShutdownAPI(options); // Should only be called once.
    return 0;
}

• For API details, see ListCollections in AWS SDK for C++ API Reference.

Actions

DetectLabels

The following code example shows how to use DetectLabels.

For more information, see Detecting labels in an image.

SDK for C++

Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

//! Detect instances of real-world entities within an image by using Amazon Rekognition
/*!
  \param imageBucket: The Amazon Simple Storage Service (Amazon S3) bucket containing an image.
  \param imageKey: The Amazon S3 key of an image object.
  \param clientConfiguration: AWS client configuration.
  \return bool: Function succeeded.
 */
bool AwsDoc::Rekognition::detectLabels(const Aws::String &imageBucket,
                                       const Aws::String &imageKey,
                                       const Aws::Client::ClientConfiguration &clientConfiguration) {
    Aws::Rekognition::RekognitionClient rekognitionClient(clientConfiguration);

    Aws::Rekognition::Model::DetectLabelsRequest request;
    Aws::Rekognition::Model::S3Object s3Object;
    s3Object.SetBucket(imageBucket);
    s3Object.SetName(imageKey);

    Aws::Rekognition::Model::Image image;
    image.SetS3Object(s3Object);

    request.SetImage(image);

    const Aws::Rekognition::Model::DetectLabelsOutcome outcome = rekognitionClient.DetectLabels(request);

    if (outcome.IsSuccess()) {
        const Aws::Vector<Aws::Rekognition::Model::Label> &labels = outcome.GetResult().GetLabels();
        if (labels.empty()) {
            std::cout << "No labels detected" << std::endl;
        } else {
            for (const Aws::Rekognition::Model::Label &label: labels) {
                std::cout << label.GetName() << ": " << label.GetConfidence() << std::endl;
            }
        }
    } else {
        std::cerr << "Error while detecting labels: '"
                  << outcome.GetError().GetMessage()
                  << "'" << std::endl;
    }

    return outcome.IsSuccess();
}

• For API details, see DetectLabels in AWS SDK for C++ API Reference.

Scenarios

Create a serverless application to manage photos

The following code example shows how to create a serverless application that lets users manage photos using labels.

SDK for C++

Shows how to develop a photo asset management application that detects labels in images using Amazon Rekognition and stores them for later retrieval.

For complete source code and instructions on how to set up and run, see the full example on GitHub.

For a deep dive into the origin of this example see the post on AWS Community.

Services used in this example

• API Gateway

• DynamoDB

• Lambda

• Amazon Rekognition

• Amazon S3

• Amazon SNS