Scikit Image
OpenCV
Microsoft Computer Vision API
Amazon Rekognition
SimpleCV
Microsoft Video API
Google Vision AI
Cloudinary
Clarifai
Amazon Rekognition
Google Vision AI
OpenCV
Kairos
Keras
Trueface Visionbox
Microsoft Computer Vision API
Clarifai is a leading deep learning AI platform for computer vision, natural language processing and automatic speech recognition. We help enterprises and public sector organizations transform unstructured images, video, text and audio data into structured data, significantly faster and more accurately than humans would be able to do on their own. Our technology is used across many industries including E-commerce, Defense, Retail, Manufacturing, and more.
Our platform is powered by state-of-the-art machine learning and comes with the broadest repository of pre-trained out-of-the-box AI models to search, sort, and organize visual, textual, and audio data and help companies build turnkey AI solutions. Our pre-trained models can detect explicit content, faces, embedded objects and text within images and video as well as predict various attributes such as celebrities, food items, textures, colors, and more. An intuitive, feature-rich user interface makes it easy to use for all skill levels. We offer a free API to researchers and developers to get started building their own models in the efforts of using AI to help the greater good.
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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 / 1 day 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 / 5 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
OpenCV - OpenCV is the world's biggest computer vision library
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.
SimpleCV - SimpleCV is an open source framework for building computer vision applications.
Kairos - Facial recognition & mood detection API
