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It is a library for constructing graphs of media-handling components. The applications it supports range from simple Ogg/Vorbis playback, audio/video streaming to complex audio (mixing) and video (non-linear editing) processing. | Instantly transform any static image into a dynamic, engaging video with our AI image animator. Create stunning animations, moving photos, and captivating visual stories in seconds. No editing skills required. |
Multiplatform;
Comprehensive Core Library;
Intelligent Plugin Architecture;
Broad Coverage of Multimedia Technologies;
Extensive Development Tools
| AI Image-to-Video Generation, Photo Animation, AI Video Generator, Image Animator, Motion Control, Static to Motion |
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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 is the leading platform for end-to-end visual media processing. With robust APIs, SDKs, and integrations, imgix empowers developers to optimize, transform, manage, and deliver images and videos at scale through simple URL parameters.

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.

ImageKit offers a real-time URL-based API for image & video optimization, streaming, and 50+ transformations to deliver perfect visual experiences on websites and apps. It also comes integrated with a Digital Asset Management solution.

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

Effortless image resizing, optimization and CDN delivery. Make your site fully responsive and really fast.

scikit-image is a collection of algorithms for image processing.

Zencoder downloads the video and converts it to as many formats as you need. Every output is encoded concurrently, with virtually no waiting—whether you do one or one hundred. Zencoder then uploads the resulting videos to a server, CDN, an S3 bucket, or wherever you dictate in your API call.

It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

It supports JPEG, PNG and GIF files. You can optimize your images in two ways - by providing an URL of the image you want to optimize or by uploading an image file directly to its API.