BMP180 sensor driver for Home Assistant used in Raspberry Pi

Custom component BMP180 sensor for Home Assistant. Copy the content of this directory to your homeassistant config directory: example: ./config/custom_components/dev_747_BMP180/ ##Requirements:Enable I2C communication in Raspberry via raspi-config and install dependencies for handeling I2C communication in Python sudo apt-get update sudo apt-get install python3-smbus python3-dev i2c-tools ##Parameters: i2c_address: I2C address of BMP180 (typical 0x77) i2c_bus_num: I2C bus number (default raspberry = 1) name: custom name of the sensor mode: 0 – Ultra low power, 1 – standard, 2 – high resolution, […]

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Message Encrypt and decrypt software, allows you to encrypt the secrete message and decrypt Another Encryption Message

Message Encrypt and decrypt software // allows you to encrypt the secrete message and decrypt Another Encryption Message. | Requirements Install Base64 for Encryption and Decrpytion To Install This Module Follow This Step pip install base64 If You Don’t Have Last version Pip Upgrade First And InstallTo Upgrade Pip Write This Command On The Command Prompt python -m pip install –upgrade pip Encrpytion Mode Decryption Mode GitHub View Github    

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Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning

Trevor Ablett*, Bryan Chan*, Jonathan Kelly (*equal contribution) Poster at Neurips 2021 Deep Reinforcement Learning Workshop Adversarial Imitation Learning (AIL) is a technique for learning from demonstrations that helps remedy the distribution shift problem that occurs with Behavioural Cloning. Empirically, we found that for manipulation tasks, off-policy AIL can suffer from inefficient or stagnated learning. In this work, we resolve this by enforcing exploration of a set of easy-to-define auxiliary tasks, in addition to a main task. This repository contains […]

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POC for detecting the Log4Shell (Log4J RCE) vulnerability

POC for detecting the Log4Shell (Log4J RCE) vulnerability. Run on a system with python3python3 log4shell-poc.py pathToTargetFile – containing a list of targets (targets are seperated by newlines) InteractionURL – the endpoint used to monitor out of band data extraction or interactions, e.g: https://github.com/projectdiscovery/interactsh Example Output

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A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch

Basic unsupervised implementation of Layer-wise Relevance Propagation (Bach et al.,Montavon et al.) in PyTorch for VGG networks from PyTorch’s Model Zoo.This tutorial served as a starting point.In this implementation, I tried to make sure that the code is easy to understand and easy to extend to othernetwork architectures. I also added a novel relevance propagation filter to this implementation resulting in much crisper heatmaps(see my blog for more information).If you want to use it, please don’t forget to cite this […]

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Kivy program for identification & rotation sensing of objects on multi-touch tables

ObjectViz is a multitouch object detection solution, enabling you to createphysical markers out of any reliable multitouch solution. It’s easily configurable and pluggable, using TUIO as a communication protocolwith client applications. Documentation To build the documentation (on ubuntu) you need texlive-base texlive-fonts-extra go to the docs directory and run make latexpdf Build & Package A makefile in packaging is used for the various operations: to install the dependencies, ensure python3.6 or newer is installed then: make -f packaging/Makefile Deps To […]

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Manipulation OpenAI Gym environments to simulate robots at the STARS lab

This repository contains a set of manipulation environments that are compatible with OpenAI Gym and simulated in pybullet. In particular, we have a set of environments with a simulated version of our lab’s mobile manipulator, the Thing, containing a UR10 mounted on a Ridgeback base, as well as a set of environments using a table-mounted Franka Emika Panda. The package currently contains variations of the following tasks: Reach Lift Stack Pick and Place Sort Insert Pick and Insert Door Open […]

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Log4jake works by spidering a web application for GET/POST requests

Log4jake works by spidering a web application for GET/POST requests. It will then automatically execute the GET/POST requests, filling any discovered parameters with the ${jndi:ldap://:389} Log4j payload. Note that this tool is designed to work simultaneously with a NetCat listener. If you want to test behind authentication, use the commented ‘#req.add_header(‘Authorization’, “token_goes_here”)’ line to add the proper token. If you are experiencing SSL errors, use the commented ‘#context = ssl._create_unverified_context()’ line in addition to ‘resp = urllib.request.urlopen(req, context=context)’ Syntax:

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