A Pancakeswap v2 trading client with limit orders and much more

Pancakeswap v2 trading client A Pancakeswap trading client (and bot) with limit orders, stop-loss, custom gas strategies, a GUI and much more. If you have any questions or inquiries, you can contact me via telegram: aviddot Check out the demo of my Pancakeswap sniping bot: https://github.com/aviddot/Pancakeswap-sniping-bot-demo Prerequisites An ethereum/bsc address A Windows machine Not sure whether needed anymore: Visual C++ build tools (www.visualstudio.microsoft.com/visual-cpp-build-tools/) Getting started Read prerequisites Download the latest release or download “configfile.py” and “pancakeswap_bot.exe” from the repository. Open […]

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An unofficial PyTorch implementation of a federated learning algorithm

Federated Averaging (FedAvg) in PyTorch An unofficial implementation of FederatedAveraging (or FedAvg) algorithm proposed in the paper Communication-Efficient Learning of Deep Networks from Decentralized Data in PyTorch. (implemented in Python 3.9.2.) Implementation points Exactly implement the models (‘2NN’ and ‘CNN’ mentioned in the paper) to have the same number of parameters written in the paper. 2NN: TwoNN class in models.py; 199,210 parameters CNN: CNN class in models.py; 1,663,370 parameters Exactly implement the non-IID data split. Each client has at least […]

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Connecting Language and Vision for Natural Language-Based Vehicle Retrieval

AI City 2021 The 1st Place Submission to AICity Challenge 2021 Natural Language-Based Vehicle Retrieval Track (Alibaba-UTS submission) We have two codebases. For the final submission, we conduct the feature ensemble, where features are from two codebases. Part One is at here: https://github.com/ShuaiBai623/AIC2021-T5-CLV Part Two is at here: https://github.com/layumi/NLP-AICity2021 Prepare Preprocess the dataset to prepare frames, motion maps, NLP augmentation scripts/extract_vdo_frms.py is a Python script that is used to extract frames. scripts/get_motion_maps.py is a Python script that is used to […]

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Unsupervised technique to Glossary and Definition Extraction

Automatic-Glossary-Generation The projects lets you extract glossary words and their definitions from a given piece of text automatically using NLP techniques Code Files GPT2-DefinitionModel.ipynb – GPT-2 model for definition generation. Data_Generator.ipynb – Data Scraper from GoodReads and GradeSaver Definition_Extraction.ipynb – WordNet model for definition generation. Glossary_Extraction.ipynb – Chinking strategy pipeline for selection of glossary terms. GitHub https://github.com/prakhar21/Automatic-Glossary-Generation    

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Stacks and Queues: Selecting the Ideal Data Structure

There are a variety of ways for storing and managing data in your program and the choice of the right data structure has an effect on the readability of your code, ease of writing, and performance. Python has a wide selection of built-in mechanisms that meet most of your data structure needs. This course introduces you to three types of data structures: stacks, queues, and priority queues. There are multiple types and classes for all of these data structures and […]

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Implementation of GGB color space with python

GGB Color Space This script is implementation of GGB color space from Development of a Robust Algorithm for Detection of Nuclei and Classification of White Blood Cells in Peripheral Blood Smear Image Dependencies $ sudo pip install -r requirements.txt How to Use $ python ggb.py –input Result Leukocytes Fundus Car GitHub https://github.com/reshalfahsi/ggb    

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Create videos quickly and easily by simply typing out the video’s script with python

Text2Video Text2Video’s purpose is to help people create videos quickly and easily by simply typing out the video’s script and a description of images to include in the video. Usage Just upload a script and an optional audio file of you saying the script To start the server run this in the terminal docker start gentle python app.py To stop the server open the same terminal and press CTRL-C. After that run docker stop gentle For instructions on how to […]

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A High-Performance Video Processing Python Library

VidGear VidGear is a High-Performance Video Processing Python Library that provides an easy-to-use, highly extensible, thoroughly optimised Multi-Threaded + Asyncio Framework on top of many state-of-the-art specialized libraries like OpenCV, FFmpeg, ZeroMQ, picamera, starlette, streamlink, pafy, pyscreenshot, aiortc and python-mss serving at its backend, and enable us to flexibly exploit their internal parameters and methods, while silently delivering robust error-handling and real-time performance fire VidGear primarily focuses on simplicity, and thereby lets programmers and software developers to easily integrate and […]

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Formulas for mixed-effects models in Python

formulae formulae is a Python library that implements Wilkinson’s formulas for mixed-effects models. The main difference with other implementations like Patsy or formulaic is that formulae can work with formulas describing a model with both common and group specific effects (a.k.a. fixed and random effects, respectively). This package has been written to make it easier to specify models with group effects in Bambi, a package that makes it easy to work with Bayesian GLMMs in Python, but it could be […]

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