📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.
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📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.
Neural Network to colorize grayscale images
Mail hosting made simple
An open source implementation of OpenAI's ChatGPT Code interpreter
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
Unbearably fast near-real-time pure-Python runtime-static type-checker.
Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Collaborative forensic timeline analysis
pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
Insane(ly slow but wicked good) PNG image optimization
Datetimes for Humans™
Accelerated deep learning R&D
Python Toolkit for Causal and Probabilistic Reasoning
Powerful Markdown package for Sublime Text with better syntax understanding and good color schemes.
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
The machine learning toolkit for time series analysis in Python
:sunglasses: A curated list of robotics libraries and software
TensorFlow (Python API) implementation of Neural Style
High performance datastore for time series and tick data
A Simple and Versatile Framework for Object Detection and Instance Recognition
Simplifies writing DocBlock comments in Javascript, PHP, CoffeeScript, Actionscript, C & C++
Automatically mock your HTTP interactions to simplify and speed up testing
NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO