OpenCV
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, and stitch images together to produce a high-resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery, etc.
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Prophesee Metavision
Metavision is an advanced event-based vision software toolkit developed by Prophesee, designed to facilitate the evaluation, design, and commercialization of event-based vision products. The SDK offers a comprehensive suite of tools, including 64 algorithms, 105 code samples, and 17 tutorials, enabling developers to efficiently build and deploy event-based applications. The open source architecture of Metavision SDK ensures full interoperability between software and hardware devices, fostering a rapidly growing event-based vision community. The platform covers a wide range of computer vision fields, such as machine learning, computer vision, camera calibration, and high-performance applications. Developers have access to extensive documentation, including over 300 pages of content, programming guides, and reference data, providing a solid foundation for product development. Metavision SDK5 PRO includes advanced add-ons like high-speed counting, spatter monitoring, and more.
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Google Cloud Vision AI
Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.
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Wekinator
The Wekinator is free, open source software. Wekinator 1.0 was originally created in 2009 by Rebecca Fiebrink. In 2015, Rebecca released Wekinator 2.0, an entirely new version with redesigned interactions, new algorithms, and ability to connect easily to dozens of other creative coding tools and sensors. Wekinator 2.0 continues to be gently updated with bug fixes and feature requests. It allows anyone to use machine learning to build new musical instruments, gestural game controllers, computer vision or computer listening systems, and more. The Wekinator allows users to build new interactive systems by demonstrating human actions and computer responses, instead of writing programming code. Create mappings between gesture and computer sounds. Control a drum machine using your webcam! Play Ableton using a Kinect! Control interactive visual environments created in Processing, OpenFrameworks, or Quartz Composer, or game engines like Unity, using gestures sensed from webcam, Kinect, etc.
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