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Based on our record, OpenCV should be more popular than FuzzyWuzzy. It has been mentiond 59 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.
Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / 8 days ago
Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / 4 months ago
OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision. - Source: dev.to / 6 months ago
This library is used for image and video processing, offering functions for tasks like object detection, filtering, and transformations in computer vision. - Source: dev.to / 7 months ago
First of all, OpenCV, an open-source computer vision library, was used as the main editing tool. This is how NuloApp is able to get the correct aspect ratio for smartphone content, and do other cool things like centering the video on the speaker so that they aren't out of frame when the aspect ratio is changed. - Source: dev.to / 8 months ago
Do fuzzy matching (something like fuzzywuzzy maybe) to see if the the words line up (allowing for wrong words). You'll need to work out how to use scoring to work out how well aligned the two lists are. Source: over 2 years ago
Convert the original lines to full furigana and do a fuzzy match. (For reference, the original line is 貴方がこれまでに得てきた力、存分に発揮してくださいね。) You can do a regional search using the initial scene data (E60) first, and if the confidence is low, go for a slower full search. Source: over 2 years ago
It's now known as "thefuzz", see https://github.com/seatgeek/fuzzywuzzy. Source: almost 3 years ago
You can have a look at this library to use fuzzy search instead of looking for plaintext muck: https://github.com/seatgeek/fuzzywuzzy. Source: over 3 years ago
To deal with comparing the string, I found FuzzyWuzzy ratio function that is returning a score of how much the strings are similar from 0-100. Source: almost 4 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Amazon Comprehend - Discover insights and relationships in text
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
spaCy - spaCy is a library for advanced natural language processing in Python and Cython.
NumPy - NumPy is the fundamental package for scientific computing with Python
Microsoft Bing Spell Check API - Enhance your apps with the Bing Spell Check API from Microsoft Azure. The spell check API corrects spelling mistakes as users are typing.