image-similarity-measures
PyTorch-NLP
| image-similarity-measures | PyTorch-NLP | |
|---|---|---|
| 3 | 1 | |
| 518 | 2,180 | |
| 2.1% | - | |
| 4.4 | 0.0 | |
| 20 days ago | 10 months ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
image-similarity-measures
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Using VAE for image compression
Speaking of math, using this library -- https://github.com/up42/image-similarity-measures -- I computed the following for these images vs the original image:
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I matched 400+ images to create illusion of motion [epilepsy]
The easiest place to start is using the classical approaches such as implemented here. For the kind of qualitative assessments you're performing, you'd probably need to use some deep learning techniques but these generally require significant technical background to implement.
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I made a website that tracks Forsen's Jump King progress and can notify you above chosen percentage.
I use https://github.com/up42/image-similarity-measures for image similarity.
PyTorch-NLP
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Introduction to PyTorch
PyTorch-NLP
What are some alternatives?
ignite - High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
piqa - PyTorch Image Quality Assessement package
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
OCTIS - OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)
NLTK - NLTK Source
generative-evaluation-prdc - Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.
pytext - A natural language modeling framework based on PyTorch
COMET - A Neural Framework for MT Evaluation
Jieba - 结巴中文分词
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.