Author: Deep Learner

Command-line Tools

The premiere CLI jockey replacement full stack web/app/database network automation application

Network Engineer’s Unified Realtime Automation Library © NEURAL Page (Overview, features, extensibility, etc.) https://www.automate-the-network.com/neural NEURAL is the premiere CLI jockey replacement full stack web/app/database network automation application, providing a “no-code” web app for network engineers developed by a network engineer! It’s built using the Django Web framework I’ll be updating this README in the future with more info, but for now, here’s the intial setup instructions, after you’ve got your Server running, e.g. after you’veimported the OVA into VM Workstation […]

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PyTorch

Pytorch Pedestrian Attribute Recognition: A strong PyTorch baseline for pedestrian attribute recognition and multi-label classification

Rethinking of Pedestrian Attribute Recognition: A Reliable Evaluation under Zero-Shot Pedestrian Identity Setting (official Pytorch implementation) This paper submitted to TIP is the extension of the previous Arxiv paper. This project aims to provide a strong baseline for Pedestrian Attribute Recognition and Multi-Label Classification. provide two new datasets RAPzs and PETAzs following zero-shot pedestrian identity setting. provide a general training pipeline for pedestrian attribute recognition and multi-label classification task. This project provide DDP training, which is mainly used for multi-label […]

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Tool

DALLE-tools provided useful dataset utilities to improve you workflow with WebDatasets

DALLE-tools is a github repository with useful tools to categorize, annotate or check the sanity of your datasets. Installation Just clone this repository to your folder and use one of the following commands in the section underneath. WebDataset Annotator Press to switch to the next page, to change the annotation category or click on the image to add it to the current cateogry and save it in annotations.json. Please upload your annotations.json by creating a push request into community_annotations folder […]

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Python

Advent of Code: Solving Your Puzzles With Python

Advent of Code is an online Advent calendar where you’ll find new programming puzzles offered each day from December 1st to the 25th. While you can solve the puzzles at any time, the excitement when new puzzles unlock is really something special. You can participate in Advent of Code in any programming language—including Python! This tutorial will help you get started with solving puzzles and earning your first golden stars. Advent of Code puzzles are designed to be approachable by […]

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Games

Small game for you to run on your terminal

Pequeno joguinho pra você rodar no seu terminal Olá! Joguinho legal pra vc rodar no seu terminal!! (rode no terminal, pra melhor experiencia) Instalação, Clonagem e Acesso $ pkg upgrade $ pkg update $ pkg install git $ pkg install python $ git clone https://github.com/yScottLuck/JokenPython $ cd JokenPython $ python3 main.py GitHub View Github    

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Error

Prevent `CUDA error: out of memory` in just 1 line of code

Koila solves CUDA error: out of memory error painlessly.Fix it with just one line of code, and forget it. 🚀 Features 🙅 Prevents CUDA error: out of memory error with one single line of code. 🦥 Lazily evaluates pytorch code to save computing power. ✂️ Automatically splits along the batch dimension to more GPU friendly numbers (2’s powers) to speed up the execution. 🤏    

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Converter

Simple converter for deploying Stable-Baselines3 model to TFLite and/or Coral

Introduction I’ve been using Stable-Baselines3to train agents against some custom Gyms, some of which require fairlylarge NNs in order to be effective. I want those agents to eventually be run on a pi or similar, so I needto export all the way to TFLiteand ideally a Coral. How to use Setup You will need to have configured the Coral system-wide stuff. Build a venv: python3 -m venv venv source venv/bin/activate python3 -m pip install -r requirements.txt Running This comes with […]

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