Cloudinary vs OpenCV: What are the differences?
What is Cloudinary? An end-to-end image & video management solution for your web and mobile applications. Cloudinary is a cloud-based service that streamlines websites and mobile applications' entire image and video management needs - uploads, storage, administration, manipulations, and delivery.
What is OpenCV? 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.
Cloudinary and OpenCV can be categorized as "Image Processing and Management" tools.
Some of the features offered by Cloudinary are:
- Upload images to a cloud-based storage
- Upload video to cloud-based storage
- Automatic backup and revision tracking
On the other hand, OpenCV provides the following key features:
- C++, C, Python and Java interfaces and supports Windows, Linux, Mac OS, iOS and Android
- More than 47 thousand people of user community and estimated number of downloads exceeding 7 million
- Usage ranges from interactive art, to mines inspection, stitching maps on the web or through advanced robotics
"Easy setup" is the primary reason why developers consider Cloudinary over the competitors, whereas "Computer Vision" was stated as the key factor in picking OpenCV.
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.
ebay, Myntra, and Movielala are some of the popular companies that use Cloudinary, whereas OpenCV is used by Lensley, Athento, and Suggestic. Cloudinary has a broader approval, being mentioned in 115 company stacks & 39 developers stacks; compared to OpenCV, which is listed in 39 company stacks and 39 developer stacks.
What is Cloudinary?
What is OpenCV?
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My website is https://cyberindia.in and I manage 95% of my images in cloudinary and I am happy slowly I will move all my images to cloudinary and become more happy :D . On a serious note Cloudinary Rocks ...
The art of technologies and delivering power potential with a huge flexibility makes cloudinary stand out in the crowd.
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.
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.
Uploaded files are stored in the cloud and immediately made accessible. To transform, optimize and manage images and videos.The Future of Content Delivery and Management.Optimizing Video with Cloudinary and the HTML5 videoPlayer. https://cloudinary.com
we used this as our image hosting site at talenthouse. helped the cloundinary team with the video integration as we were one of the first users. also helped patch the cloudinary scala library.
CV glue. Modified libraries for pattern-detection. Some pattern training tasks. HoG matching. Transform
4 years of experience with Cloudinary for cloud-based image processing and CDN.