Amazon Rekognition Rekognition-Beispiele mit SDK for C++

Code für die CMake Datei CMake Lists.txt.

# 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 für die Quelldatei hello_rekognition.cpp.

#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;
}

//! 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();
}

Zeigt, wie eine Anwendung zur Verwaltung von Fotobeständen entwickelt wird, die mithilfe von Amazon Rekognition Labels in Bildern erkennt und sie für einen späteren Abruf speichert.

Den vollständigen Quellcode und Anweisungen zur Einrichtung und Ausführung finden Sie im vollständigen Beispiel unter GitHub.

Einen tiefen Einblick in den Ursprung dieses Beispiels finden Sie im Beitrag in der AWS -Community.