Search Results for "python pip" - Page 7
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Showing 196 open source projects for "python pip"
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arxiv-collector
Little Python script to collect LaTeX sources for upload to the arXiv
A little Python script to collect LaTeX sources for upload to the arXiv. Install with pip install arxiv-collector or conda install -c conda-forge arxiv-collector, or just download arxiv_collector.py, it's a stand-alone script with no dependencies. Works with any reasonable version of Python 3, or 2.7 if you really must. -
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AWS IoT Greengrass Core SDK
SDK to use with functions running on Greengrass Core using Python
The AWS IoT Greengrass Core SDK is meant to be used by AWS Lambda functions running on an AWS IoT Greengrass Core. It will enable Lambda functions to invoke other Lambda functions deployed to the Greengrass Core, publish messages to the Greengrass Core and work with the local Shadow service. To use the AWS IoT Greengrass Core SDK, you must first import the AWS IoT Greengrass Core SDK in your Lambda function as you would with any other external libraries. You then need to create a client for... -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
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0x Monorepo
0x protocol monorepo - includes our smart contracts
...Visit our developer portal for a comprehensive list of core & community-maintained packages. All packages maintained with this monorepo are listed. You will also need to have Python 3 installed, in order to build and run the tests of abi-gen's command-line interface, which is integrated with the yarn build, yarn test, and yarn lint commands described below. More specifically, your local pip should resolve to the Python 3 version of pip, not a Python 2.x version. -
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TubeCatcher
Its an application which can download youtube videos.
Its an application which can download youtube videos and videos of the given playlist. Also download videos from playlist given range number. It has been developed by using youtube_dl library. Linux : python >=3.6 and python3-pip. -
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cv2_plt_imshow
Using matplotlib_imshow for images read by cv2
...This package provides two of the main function, converting the image to a format more suitable in matplotlib, and plotting the image using matplotlib in the notebooks. ## Table of contents * [Setup](#setup) * [Dependencies](#dependencies) * [Contact](#contact) ## Setup ```pip install cv2_plt_imshow``` ## Dependencies * [matplotlib](https://pypi.org/project/matplotlib/) * [cv2](https://pypi.org/project/opencv-python/) ## Contact * [Author](https://rupesh.info/) * [Github](https://github.com/rs9899/cv2_plt_imshow) -
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unrpa
A program to extract files from the RPA archive format
unrpa is a tool to extract files from the RPA archive format (from the Ren'Py Visual Novel Engine). It can also be used as a library. The best way to install unrpa is through your package manager, if a package is available for your operating system. I maintain an AUR package for Arch Linux users. -
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jieba
Stuttering Chinese word segmentation
...The paddle mode uses the PaddlePaddle deep learning framework to train the sequence labeling (bidirectional GRU) network model to achieve word segmentation. Also supports part-of-speech tagging. To use paddle mode, you need to install paddlepaddle-tiny, pip install paddlepaddle-tiny==1.6.1. Currently paddle mode supports jieba v0.40 and above. For versions below jieba v0.40, please upgrade jieba, pip install jieba --upgrade. -
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termtosvg
Record terminal sessions as SVG animations
termtosvg is a Unix terminal recorder written in Python that renders your command line sessions as standalone SVG animations. Produce lightweight and clean-looking animations embeddable on a project page. Custom color themes, terminal UI, and animation controls via SVG templates. Compatible with asciinema recording format. termtosvg is compatible with Linux, macOS and BSD OSes, requires Python >= 3.5 and can be installed using pip. -
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Bangla TTS
Bangla text to speech synthesis in python
Bangla text to speech Multilingual (Bangla, English) real-time ([almost] in a GPU) speech synthesis library. Installation -------------------------------------- * Install Anaconda * conda create -n new_virtual_env python==3.6.8 * conda activate new_virtual_env * pip install -r requirements.txt * While running for the first time, keep your internet connection on to download the weights of the speech synthesis models (>500 MB) * For fast inference, you must install tensorflow-gpu and have a NVidia GPU. ... -
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gpt2-client
Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.
GPT-2 is a Natural Language Processing model developed by OpenAI for text generation. It is the successor to the GPT (Generative Pre-trained Transformer) model trained on 40GB of text from the internet. It features a Transformer model that was brought to light by the Attention Is All You Need paper in 2017. The model has 4 versions - 124M, 345M, 774M, and 1558M - that differ in terms of the amount of training data fed to it and the number of parameters they contain. Finally, gpt2-client is a... -
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GPT-2 FR
GPT-2 French demo | Démo française de GPT-2
OpenAI GPT-2 model trained on four different datasets in French. Books in French, French film scripts, reports of parliamentary debates, Tweet by Emmanuel Macron, allowing to generate text. Tensorflow and gpt-2-simple are required in order to fine-tune GPT-2. Create an environment then install the two packages pip install tensorflow==1.14 gpt-2-simple. A script and a notebook are available in the src folder to fine-tune GPT-2 on your own datasets. The output of each workout, i.e. the folder... -
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nonechucks
Deal with bad samples in your dataset dynamically
nonechucks is a library that provides wrappers for PyTorch's datasets, samplers and transforms to allow for dropping unwanted or invalid samples dynamically. What if you have a dataset of 1000s of images, out of which a few dozen images are unreadable because the image files are corrupted? Or what if your dataset is a folder full of scanned PDFs that you have to OCRize, and then run a language detector on the resulting text, because you want only the ones that are in English? Or maybe you... -
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pipupgrade
Like yarn outdated/upgrade, but for pip
pipupgrade is a command-line utility designed to streamline the management of Python package dependencies. It automates the process of identifying and upgrading outdated packages across various Python environments, including system-wide installations, virtual environments, and project-specific setups. By analyzing semantic versioning, pipupgrade categorizes updates into major, minor, and patch changes, allowing developers to make informed decisions about which packages to upgrade.... -
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ChainerCV
ChainerCV: a Library for Deep Learning in Computer Vision
ChainerCV is a collection of tools to train and run neural networks for computer vision tasks using Chainer. In ChainerCV, we define the object detection task as a problem of, given an image, bounding box-based localization and categorization of objects. Bounding boxes in an image are represented as a two-dimensional array of shape (R,4), where R is the number of bounding boxes and the second axis corresponds to the coordinates of bounding boxes. ChainerCV supports dataset loaders, which can... -
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NeuralCoref
Fast Coreference Resolution in spaCy with Neural Networks
NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolves coreference clusters using a neural network. NeuralCoref is production-ready, integrated in spaCy's NLP pipeline and extensible to new training datasets. For a brief introduction to coreference resolution and NeuralCoref, please refer to our blog post. NeuralCoref is written in Python/Cython and comes with a pre-trained statistical model for English only. NeuralCoref is accompanied by a visualization client... -
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PyTorch pretrained BigGAN
PyTorch implementation of BigGAN with pretrained weights
An op-for-op PyTorch reimplementation of DeepMind's BigGAN model with the pre-trained weights from DeepMind. This repository contains an op-for-op PyTorch reimplementation of DeepMind's BigGAN that was released with the paper Large Scale GAN Training for High Fidelity Natural Image Synthesis. This PyTorch implementation of BigGAN is provided with the pretrained 128x128, 256x256 and 512x512 models by DeepMind. We also provide the scripts used to download and convert these models from the... -
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Cloud Filer
S3 file management tool with encryption
Cloud Filer is a graphical cloud file management tool and S3 client. Cloud Filer allows you to upload and download files to cloud storage and can be used as part of your backup strategy. Cloud Filer includes pre-internet encryption and file name obfuscation making access to your cloud data useless without the right password. Download and install using pip install cloudfiler - see also https://pypi.org/project/cloudfiler/ -
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virtualgo
Virtualgo: Easy and powerful workspace based development
...Virtualgo doesn't do dependency resolution or version pinning itself, because this is a hard problem that's already being solved by other tools. Its approach is to build on top of these tools, such as dep, to provide the features features listed above. For people coming from Python, vg is very similar to virtualenv, with dep being respective to pip. The main difference is that vg is much easier to use than virtualenv, because there's almost no mental overhead in using vg. You can pin versions of executable dependencies, such as linting and code generation tools. You can easily use a dependency from your global GOPATH inside your workspace, without running into confusing import errors. ... -
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BeakerX
Beaker Extensions for Jupyter Notebook
...BeakerX is available via conda, pip, and docker. Or try it live online with Binder. All of BeakerX’s JVM languages plus Python and JavaScript have APIs for interactive time-series, scatter plots, histograms, heatmaps, and treemaps. -
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Jupyter Themes
Custom Jupyter Notebook Themes
jupyter-themes brings theme management to classic Jupyter Notebooks with a command-line tool that can restyle the interface, code cells, and UI chrome in seconds. It ships a catalog of popular dark and light themes and lets you customize fonts, font sizes, cell widths, and toolbar visibility so the notebook matches your preferred reading and coding ergonomics. The theming system adjusts CodeMirror syntax highlighting to keep code legible against chosen backgrounds and provides options to... -
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The Hershey Font Explorer
Review, Manage, and Export Vector-Based Fonts
...If you're into Python, you can `pip install PyHershey_9000` as well. Enjoy. Randall Nagy Soft9000.com -
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PipBlender
Pip installer in Blender+[Sverchok|Animation Nodes]+BlendBridge
A Blender addon to install Python packages using Pip and the BlendBridge library. The BlendBridge library is distributed as a perk in the TWINGSISTER's internal crowdfunding campaign. The PipBlender addon can be used either in Blender or in Blender+[Sverchok or Animation Nodes]. License: material contained here (brought to you by TWINGSISTER) is for TWINGSISTER personal use only. -
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pivottablejs
Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook
PivotTable.js is a Javascript Pivot Table and Pivot Chart library with drag-drop interactivity, and it can now be used with Jupyter/IPython Notebook via the pivottablejs module. I first built PivotTable.js with a plan to build an in-browser data analysis tool, and got as far as one where you could load up a CSV file in the browser for display. Since then, however, the Jupyter project has gathered steam and now provides a browser-based interface to some of the most powerful data processing... -
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Tangent
Source-to-source debuggable derivatives in pure Python
Existing libraries implement automatic differentiation by tracing a program's execution (at runtime, like PyTorch) or by staging out a dynamic data-flow graph and then differentiating the graph (ahead-of-time, like TensorFlow). In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools. As a result, you can finally read your automatic derivative...
