Gumlet Video streamlines the process of uploading, transcoding, optimizing, hosting, and analyzing videos, enabling rapid streaming to vast audiences. Gumlet Image Optimization enhances website speed, responsiveness, user experience (UX), and search engine optimization (SEO).
Gumlet is loved by 8000+ businesses and start-ups and delivers over 1.5 Billion media files daily. With an average optimization rate of 54%, Gumlet offers an exceptional video and media experience for users across websites and applications.
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Image loads fast, im impressed with the speed and ease of installation. I have successfully deployed them on afew of my websites and it improves my overall loading speed.
Gumlet is a wonderful little tool that I use for optimising your images and thus your website loading speeds. We use it for our work (and client projects) and it works very well!
Pros: - Inbuilt CDN - Easy integration with Wordpress - on-the-fly image manipulation is awesome - Supports CNAME now!
Cons: - Missing some smart (AI-like) image manipulation features that Cloudinary has like Smart/Face-cropping for example. Would love to have those!
Gumlet is easy to implement and instantly improves the performance of your site. I compared to other providers and was happy to see that it outperforms the competition
Based on our record, Scikit Image seems to be more popular. It has been mentiond 7 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
We will use the Hugging Face transformers and diffusers libraries for inference, FiftyOne for data management and visualization, and scikit-image for evaluation metrics. - Source: dev.to / about 1 month ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 6 months ago
This is a good cv deep learning book with python examples https://www.manning.com/books/deep-learning-for-vision-systems. If you're pretty comfortable with the concepts of traditional image processing this is a good companion to cv2 (so you don't have to reinvent the wheel) https://scikit-image.org/. Source: over 1 year ago
Also, don't know if you're familiar with Python, but if you need ideas for to implement for future directions : https://scikit-image.org/. Source: over 1 year ago
There's probably something in scikit-image to do what you want, or close enough to build on. Source: about 2 years ago
OpenCV - OpenCV is the world's biggest computer vision library
Cloudimage - Cloudimage.io is the easiest way to resize, store, and deliver your images to your customers through a rocket fast CDN.
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
ImageKit.io - Instant multi-platform image optimization
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.
Cloudinary - Cloudinary is a cloud-based service for hosting videos and images designed specifically with the needs of web and mobile developers in mind.