OpenCV Development

Technology We Use


OpenCV is the most popular computer vision library. It’s open-source, offering built-in functions for common image processing that save time and effort. It’s equipped with a wide range of capabilities, from simple image processing to machine learning for image interpretation. OpenCV’s performance is fast, optimized, and often even GPU accelerated, with compatibility to run on a variety of hardware, from desktop to mobile to Raspberry Pi.

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Why we use it

Technique Matters.

Powering Robot Perception

OpenCV supports large parts of the robot perception we build. OpenCV powers the software that our robots use to estimate their motion and visually localize themselves in their environment using onboard cameras.

Facial and Object Recognition

Fresh employs OpenCV throughout our offline facial recognition pipeline — right from image capture to face detection, to building the machine learning algorithms that recognize them.

Full Compatibility

OpenCV has compatibility with a variety of platforms and languages, including C++, Python, Tensorflow, ROS (Robot Operating System), and JavaScript. It also runs on Windows, Linux, iOS, and Android, and works with LabVIEW.

Thought Leadership

Relevant Resources

Autonomous Vehicle Development Process Timeline


understanding robot factors white paper

Understanding Robot Factors


Who Builds it

We Code With OpenCV

Li Ding

Li Ding

AI/ML Engineer
Dean Fortier

Dean Fortier

Electrical Engineer
Paul Reynolds

Paul Reynolds

Technical Director

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