Search Results for "options"
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Showing 17 open source projects for "options"
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WeasyPrint
The awesome document factory
...Creating high-quality digital documents requires features that you love to use as readers, tables of contents, links, annotations, optimized images, attachments, WeasyPrint provides many features out of the box, and even gives you the possibility to add your own ways to customize your PDF files. Digital fonts are finely tuned pieces of artwork. To give to your documents the subtle touch they deserve, carefully choose the options you want, kerning, ligatures, old-style numbers, tabular figures, ordinals, etc. -
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troposphere
Python library to create AWS CloudFormation descriptions
The troposphere library allows for easier creation of the AWS CloudFormation JSON by writing Python code to describe the AWS resources. troposphere also includes some basic support for OpenStack resources via Heat. To facilitate catching CloudFormation or JSON errors early the library has property and type checking built into the classes. -
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Double Conversion
Efficient binary-decimal & decimal-binary conversion routines for IEEE
...It is optimized for both speed and correctness, making it ideal for numerical computation libraries, serialization systems, and scripting engines. The codebase includes detailed documentation and comprehensive unit tests to validate correctness across various platforms. With flexible build options using SCons, CMake, or Bazel, Double Conversion integrates seamlessly into modern C++ development workflows. -
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Boltons
250+ constructs, recipes, and snippets which extend the Python library
Boltons is a set of pure-Python utilities in the same spirit as, and yet conspicuously missing from, the standard library. Due to the nature of utilities, application developers might want to consider other integration options. Boltons is tested against Python 2.6-2.7, 3.4-3.7, and PyPy. The majority of boltons strive to be “good enough” for a wide range of basic uses, leaving advanced use cases to Python’s myriad specialized 3rd-party libraries. In many cases the respective boltons module will describe 3rd-party alternatives worth investigating when use cases outgrow boltons. ... -
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kubectl-aliases
Programmatically generated handy kubectl aliases
...It ships a prebuilt .kubectl_aliases file for Bash/Zsh, plus variants for Fish and Nushell, which you drop into your home directory and source from your shell config. The aliases are programmatically generated from permutations of common verbs, resources, flags, and options, so you get short forms like kgpo for kubectl get pod and more complex ones that include namespaces, label selectors, and output formats. This dramatically speeds up interactive Kubernetes workflows, especially when you spend a lot of time inspecting pods, services, deployments, and logs. The repository also includes a Python script used to generate the aliases, which advanced users can tweak if they want a custom alias set. ... -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before... -
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pythondialog
Python module to build dialogs for terminal-based applications
This is a Python module for doing terminal-based user interaction. It wraps the dialog/Xdialog program, and provides a nice, object-oriented programming model. -
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Neural Network Intelligence
AutoML toolkit for automate machine learning lifecycle
...The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different training environments like Local Machine, Remote Servers, OpenPAI, Kubeflow, FrameworkController on K8S (AKS etc.) DLWorkspace (aka. DLTS) AML (Azure Machine Learning) and other cloud options. NNI provides CommandLine Tool as well as an user friendly WebUI to manage training experiements. -
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Robin-Stocks API Library
This is a library to use with Robinhood Financial App
This is a library to use with Robinhood Financial App. It currently supports trading crypto-currencies, options, and stocks. In addition, it can be used to get real-time ticker information, assess the performance of your portfolio, and can also get tax documents, total dividends paid, and more. The code is simple to use, easy to understand, and easy to modify. With this library, you can view information on stocks, options, and cryptocurrencies in real-time, create your own robo-investor or trading algorithm, and improve your programming skills. ... -
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10
Name-That-Hash
Identify MD5, SHA256 and 300+ other hashes
Name-That-Hash is a modern hash identification system that tells you what type of hash you are looking at, supporting MD5, SHA-256, and more than 300 other hash types. It is designed as a successor and improvement to older tools like HashID and Hash-Identifier, focusing on up-to-date hash databases and better usability. One of its core ideas is popularity-aware ranking: when you feed in a hash, it prioritizes likely real-world types such as NTLM over obscure ones like Skype hashes, instead... -
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Scripting Language Bindings
A port of WFOPT to the several scripting languages
This project contains bindings for various scripting languages to the Wheefun Options Parsing Library. It is meant to provide parity with the C implementation so .NET languages can take advantage of WFOPT. For more information, please see the main page. -
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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
...It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. The project added multi-GPU training, target count statistics, learning rate scheduling with step and cosine options, and optimizer selection between Adam and SGD. It also includes adaptive learning rate adjustment based on batch size, image cropping, many configurable parameters, and expanded comments for easier study. It is well suited for learners and developers who want a hands-on YOLOv3 codebase in PyTorch. -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
...It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature extractors. The project also includes learning rate scheduling through step and cosine methods, optimizer choices between Adam and SGD, adaptive learning rate behavior based on batch size, image cropping, FPS testing, video prediction, and batch prediction. ... -
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DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
...It provides pretrained weight workflows for MobileNetV2 and Xception backbones and notes that the correct backbone should be selected during training and prediction. The project also supports multi-GPU training, multiple backbones, learning rate schedules with step and cosine options, optimizer selection, and adaptive learning rate behavior based on batch size. It is useful for users who want a stronger semantic segmentation baseline than U-Net for scene-level segmentation tasks. -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
...It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The codebase is organized as modular math and finance primitives so you can combine building blocks or target end-to-end examples. It includes Bazel builds, tests, and example notebooks to accelerate learning and adoption in real workflows. ... -
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Jython Simple Dialogs
Simple UI Dialog boxes much like 'zenity' project for jython
I have wanted very simple dialog box implementation for asking user questions, such as what is intended by the 'zenity' (or previous XDialog) type of interfaces. After looking at options I settled on using swing based UI components and it is based on the information available from: https://wiki.python.org/jython/SwingExamples The specific use of this code is targeted to user inputs for simple activities and it appears as if there isn't any single 'aggregator' and I tried to provide this functionality. Hope you enjoy! -
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ProximityForest
Efficient Approximate Nearest Neighbors for General Metric Spaces
...This source code is provided without warranty and is available under the GPL license. More commercially-friendly licenses may be available. Please contact Stephen O'Hara for license options. Please view the wiki on this site for installation instructions and examples on reproducing the results of the papers.
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