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Scikit Image
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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 / over 2 years 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 / over 2 years 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 3 years 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: almost 4 years ago
There's probably something in scikit-image to do what you want, or close enough to build on. Source: about 4 years ago
OpenCV - OpenCV is the world's biggest computer vision library
Apigility - Apigility is an API Builder, designed to simplify creating and maintaining useful, easy to consume, and well structured APIs.ย
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
API Platform - REST and GraphQL framework to build modern API-driven projects
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.
Microsoft Video API - Automatically extract metadata from video and audio files using Video Indexer. Improve the performance of your media content with Azure.