Telegram

Telegram Voice Chat Music Player UserBot Written with Pyrogram Smart Plugin and tgcalls

A Telegram UserBot to Play Audio in Voice Chats. This is also the source code of the userbot which is being used for playing DJ/Live Sets music in VC DJ/Live Sets group. Made with tgcalls and Pyrogram Smart Plugin vc.player vc.recorder ping Description Voice Chat Audio Player Voice Chat Audio Recorder ping and uptime Dependencies ffmpeg ffmpeg, opus-tools, bpm-tools Conflict vc.recorder vc.player Requirements Python 3.6 or higher A Telegram API key and a Telegram account Choose plugins you need, install […]

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Natural Language Processing

DaCy: The State of the Art Danish NLP pipeline using SpaCy

DaCy is a Danish preprocessing pipeline trained in SpaCy. At the time of writing it has achieved State-of-the-Art performance on all Benchmark tasks for Danish. This repository contains code for reproducing DaCy. To download the models use the DaNLP package (request pending), SpaCy (request pending) or downloading the project directly here. Reproduction the folder DaCy contains a SpaCy project which will allow for a reproduction of the results. This folder also includes the evaluation metrics on DaNE. Usage To   […]

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JAX

Turning SymPy expressions into JAX functions

Turn SymPy expressions into parametrized, differentiable, vectorizable, JAX functions. All SymPy floats become trainable input parameters. SymPy symbols become columns of a passed matrix. Installation pip install git+https://github.com/MilesCranmer/sympy2jax.git Example import sympy from sympy import symbols import jax import jax.numpy as jnp from jax import random from sympy2jax import sympy2jax Let’s create an expression in SymPy: x, y = symbols(‘x y’) expression = 1.0 * sympy.cos(x) +

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App

A shopping list and kitchen inventory management app

This is the backend for the Flask React project. Getting started Clone this repository (only this branch) git clone https://github.com/appacademy-starters/python-project-starter.git Install dependencies pipenv install –dev -r dev-requirements.txt && pipenv install -r requirements.txt Create a .env file based on the example with proper settings for your development environment Setup your PostgreSQL user, password and database and make sure it matches your .env file Get into your pipenv, migrate your database, seed your database, and run your flask app To run the […]

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Optimization

Optimization for Oriented Object Detection via Representation Invariance Loss

By Qi Ming, Zhiqiang Zhou, Lingjuan Miao, Xue Yang, and Yunpeng Dong. The repository hosts the codes for our paper Optimization for Oriented Object Detection via Representation Invariance Loss (paper link), based on mmdetection and s2anet. Introduction To be updated. Installation conda create -n ridet python=3.7 -y source activate ridet conda install pytorch=1.3 torchvision cudatoolkit=10.0 -c pytorch pip install -r requirements.txt python setup.py develop cd mmdet/ops/orn python setup.py build_ext –inplace apt-get update apt-get install swig apt-get install zip cd DOTA_devkit […]

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Machine Learning

Pneumonia Detection using machine learning with PyTorch

Pneumonia Detection using machine learning. Training was done in colab: DEMO: Result (Confusion Matrix): Data I uploaded my dataset to kaggle I used a modified version of this dataset from kaggle. Instead of NORMAL and PNEUMONIA I split the PNEUMONIA dataset to BACTERIAL PNUEMONIA and VIRAL PNEUMONIA. This way the data is more evenly distributed and I can distinguish between viral and bacterial pneumonia. I also combined the validation dataset with the test dataset because the validation dataset only had […]

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Python

Rock, Paper, Scissors With Python: A Command Line Game

Game programming is a great way to learn how to program. You use many tools that you’ll see in the real world, plus you get to play a game to test your results! An ideal game to start your Python game programming journey is rock paper scissors. In this course, you’ll learn how to: Code your own rock paper scissors game Take in user input with input() Play several games in a row using a while loop Clean up your […]

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PyTorch

Torch Containers simplified in PyTorch

This repository aims to help former Torchies more seamlessly transition to the “Containerless” world of PyTorch by providing a list of PyTorch implementations of Torch Table Layers. Note: As a result of full integration with autograd, PyTorch requires networks to be defined in the following manner: Define all layers to be used in the __init__ method of your network Combine them however you want in the forward method of your network (avoiding in place Tensor ops) And that’s all there […]

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