Based on our record, TinyPNG seems to be a lot more popular than Scikit Image. While we know about 155 links to TinyPNG, we've tracked only 7 mentions of Scikit Image. 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.
You also have things like https://tinypng.com which do (basically) lossy PNG for you. Works pretty well. - Source: Hacker News / about 2 months ago
Compressing images: This technique reduces image size without compromising quality. You can achieve this using various image compression tools like TinyPNG or ImageOptim. These tools are specifically designed to manage multiple image formats and compression methods. They help reduce image files, resulting in less data transfer from the server to the user's device. It is advisable to compress images before... - Source: dev.to / 2 months ago
Tinypng.com — API to compress and resize PNG and JPEG images, offers 500 compressions for free each month. - Source: dev.to / 3 months ago
TinyPNG Smart WebP, PNG and JPEG Compression. When utilised with the Raycast extension by Ryo Kawamata image compression becomes a simple task. - Source: dev.to / 4 months ago
ImageOptim - For lossless image compression. TinyPNG - Compress PNG and JPEG images without losing quality. - Source: dev.to / 4 months ago
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 14 hours 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 / 4 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: almost 2 years ago
ImageOptim - Faster web pages and apps.
OpenCV - OpenCV is the world's biggest computer vision library
TinyJPG - Compress JPEG images with perfect quality and file size
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
Caesium Image Compressor - Compress your pictures up to 90% without visible quality loss.
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.