OpenCV vs TensorFlow

OpenCV
OpenCV

277
50
66
TensorFlow
TensorFlow

960
354
58
Add tool

OpenCV vs TensorFlow: What are the differences?

Developers describe OpenCV as "Open Source Computer Vision Library". OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform. On the other hand, TensorFlow is detailed as "Open Source Software Library for Machine Intelligence". TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

OpenCV belongs to "Image Processing and Management" category of the tech stack, while TensorFlow can be primarily classified under "Machine Learning Tools".

"Computer Vision" is the top reason why over 19 developers like OpenCV, while over 16 developers mention "High Performance" as the leading cause for choosing TensorFlow.

OpenCV is an open source tool with 36.3K GitHub stars and 26.6K GitHub forks. Here's a link to OpenCV's open source repository on GitHub.

According to the StackShare community, TensorFlow has a broader approval, being mentioned in 200 company stacks & 135 developers stacks; compared to OpenCV, which is listed in 39 company stacks and 39 developer stacks.

- No public GitHub repository available -

What is OpenCV?

OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform.

What is TensorFlow?

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

Want advice about which of these to choose?Ask the StackShare community!

Why do developers choose OpenCV?
Why do developers choose TensorFlow?
What are the cons of using OpenCV?
What are the cons of using TensorFlow?
    Be the first to leave a con
    What companies use OpenCV?
    What companies use TensorFlow?
    What are some alternatives to OpenCV and TensorFlow?
    Cloudinary
    Cloudinary is a cloud-based service that streamlines websites and mobile applications' entire image and video management needs - uploads, storage, administration, manipulations, and delivery.
    imgix
    imgix is a real-time image processing service and CDN. Resize, crop, and edit images simply by changing their URLs.
    FFMPEG
    The universal multimedia toolkit.
    Aviary
    Aviary's beautiful photo editor is powerful, customizable, and can be plugged into your mobile apps and website in minutes. The best photo editing for your app or website Our 3500+ partners chose Aviary because our editor is powerful, customizable, and integration takes just minutes. Aviary comes preloaded with a ton of intuitive features that your users will love.
    scikit-image
    scikit-image is a collection of algorithms for image processing.
    See all alternatives
    What tools integrate with OpenCV?
    What tools integrate with TensorFlow?
      No integrations found
        No integrations found
        Decisions about OpenCV and TensorFlow
        No stack decisions found
        Interest over time
        Reviews of OpenCV and TensorFlow
        No reviews found
        How developers use OpenCV and TensorFlow
        Avatar of ttandon
        ttandon uses OpenCVOpenCV

        I used both scikit-image and OpenCV for image processing and cell identification on the backend. Trained to identify malaria cells based on image datasets online. When it comes to quick training for image processing, OpenCV and scikit-image are the two best choices in my opinion. The approach I took to cell detection was template-matching and edge detection based. Both are highly tested and very powerful features of the Scikit Image and OpenCV libraries, and also have great Python interfaces.

        Avatar of ssshake
        ssshake uses OpenCVOpenCV

        I use openCV to serve as "motion capture" logic for my home security cameras. Which means that instead of capturing in a dumb way based on motion, it captures video when it recognizes human faces or bodies. This saves a lot of disk, but at the expense of CPU.

        Avatar of Taylor Host
        Taylor Host uses OpenCVOpenCV

        CV glue. Modified libraries for pattern-detection. Some pattern training tasks. HoG matching. Transform

        Avatar of Eliana Abraham
        Eliana Abraham uses TensorFlowTensorFlow

        Machine Learning in EECS 445

        Avatar of Taylor Host
        Taylor Host uses TensorFlowTensorFlow

        Pilot integration for retraining.

        Avatar of Owen Miller
        Owen Miller uses OpenCVOpenCV

        We read people's CAPTCHA images.

        How much does OpenCV cost?
        How much does TensorFlow cost?
        Pricing unavailable
        Pricing unavailable
        News about OpenCV
        More news