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    Cloud Optimized OpenCV for AWS Graviton 2

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    Sold by: OpenCV 
    Deployed on AWS
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    Cloud Optimized OpenCV delivers a high-performance build of OpenCV, enabling faster computation of core computer vision operations such as resize, adaptive gaussian, contour detection functions. This optimized edition is designed for accelerated computer vision workloads on AWS Graviton and ARM-based environments, helping developers achieve improved efficiency for AI, ML, and image processing applications.

    Overview

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    Cloud Optimized OpenCV is a high-performance distribution of OpenCV, designed specifically for ARM-based environments such as AWS Graviton. Built with Kleidicv optimizations, this edition delivers significant speedups for fundamental computer vision operations, including resize, resize, adaptive gaussian, contour detection functions and more. These enhancements allow developers and enterprises to process images and video streams more efficiently, making it ideal for AI, machine learning, robotics, and real-time analytics. By leveraging hardware-aware optimizations, OpenCV Graviton Optimized reduces computational overhead and ensures better utilization of ARM-based processors. This results in faster execution, lower latency, and improved scalability across a wide range of vision workloads. Whether you are deploying applications in the cloud, on the edge, or in embedded systems, this build provides a reliable foundation for high-throughput computer vision pipelines. With its lightweight and performance-focused design, Cloud Optimized OpenCV helps teams accelerate development cycles while lowering infrastructure costs. From prototyping AI models to deploying production-grade computer vision systems, this edition combines the flexibility of OpenCV with the efficiency of Kleidicv-powered optimizations, giving you the best of both worlds.

    Highlights

    • Optimized for ARM based AWS Graviton processors and accelerated OpenCV build with Kleidicv enhancements along with further tuning of parallelization for high-performance computer vision workloads.
    • Faster core operations and significant speedups for functions mostly used in pre and post image/video processing pipelines

    Details

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    Delivery method

    Delivery option
    64-bit (Arm) Amazon Machine Image (AMI)

    Latest version

    Operating system
    Ubuntu 24.04 LTS

    Deployed on AWS
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    Try this product free for 7 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.

    Cloud Optimized OpenCV for AWS Graviton 2

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (40)

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    Dimension
    Cost/hour
    c6g.2xlarge
    Recommended
    $0.02
    c6gn.medium
    $0.01
    m6gd.xlarge
    $0.01
    m6g.8xlarge
    $0.08
    m6g.large
    $0.01
    m6gd.12xlarge
    $0.15
    m6gd.2xlarge
    $0.02
    m6gd.4xlarge
    $0.04
    c6g.medium
    $0.01
    c6g.8xlarge
    $0.06

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    We offer a 7-day free trial to allow full testing of the software before purchase. Because you can test the product extensively for free, we do not offer refunds once a paid subscription begins.

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    Usage information

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    Delivery details

    64-bit (Arm) Amazon Machine Image (AMI)

    Amazon Machine Image (AMI)

    An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

    Version release notes

    Version 1.2

    We are pleased to introduce the Cloud Optimized OpenCV Library (COOL) for AWS Graviton 2. This edition is built specifically for ARM-based environments such as AWS Graviton, with Kleidicv-powered optimizations to deliver faster performance and lower latency for core computer vision workloads.

    Key features in v1.2:

    Optimized performance for AWS Graviton 2 processors.

    Accelerated implementations of core operations

    Hardware-aware optimizations using Kleidicv for reduced computational overhead.

    Lightweight and scalable design, suitable for cloud, edge, and embedded deployments.

    Ideal for AI/ML, robotics, and real-time video or image analytics.

    This foundation release provides a reliable and high-performance base for building and deploying advanced computer vision applications while reducing infrastructure costs.

    Additional details

    Usage instructions

    STEP 1: LAUNCH THE AMI After subscribing, launch an EC2 instance using this AMI.

    Recommended instance types:

    • c6g.2xlarge or larger for optimal performance on AWS Graviton2
    • Compatible instance families: c6g, m6g, r6g

    STEP 2: CONNECT TO THE INSTANCE Connect using SSH:

    ssh -i <your-key.pem> ubuntu@<public-ip>

    STEP 3: ACTIVATE THE OPTIMIZED ENVIRONMENT (RECOMMENDED) The optimized libraries are installed under:

    /opt/cool

    COOL provides preconfigured Python virtual environments that automatically set all required paths.

    Available Python environments:

    • python_3.10
    • python_3.11
    • python_3.12

    Example: Activate Python 3.12

    - source /opt/cool/venvs/python_3.12/bin/activate

    Verify that the optimized OpenCV build is active:

    - python3 -c "import cv2; print(f'Active OpenCV: {cv2.version} from {cv2.file}')"

    OPTIONAL: USING SYSTEM PYTHON If you prefer using the default system Python or an existing environment, export the required paths manually:

    - export LD_LIBRARY_PATH="/opt/cool/cpp_sdk/lib:$LD_LIBRARY_PATH" - export PYTHONPATH="/opt/cool/python_3.12/site-packages/cv2/python-3.12/:$PYTHONPATH"

    Then run your script normally:

    - python3.12 your_script.py

    OPTIONAL: BUILDING CUSTOM C++ APPLICATIONS To compile your own C++ applications against the optimized COOL OpenCV libraries:

    1. Create a build directory in your project workspace.

    2. Create a CMakeLists.txt file with the following content:

      cmake_minimum_required(VERSION 3.10)

      project(MyApp)

      set(CMAKE_CXX_STANDARD 11)

      set(OpenCV_DIR "/opt/cool/cpp_sdk/lib/cmake/opencv4")

      find_package(OpenCV REQUIRED)

      add_executable(my_app main.cpp)

      target_link_libraries(my_app ${OpenCV_LIBS})

    3. Build and run:

      cd build

      cmake ..

      make

      ./my_app

    NOTE: Ensure LD_LIBRARY_PATH includes /opt/cool/cpp_sdk/lib before running C++ binaries.

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