TUI

A simple yet powerful TUI framework for your Python (3.7+) applications

A simple yet powerful TUI framework for your Python (3.7+) applications Usecases PyTermGUI can be used for a variety of things. You are ought to find something useful, whether you are after a TUI library with a mature widget API, a way to easily color and style your program’s output or even just get syntax highlighting in the REPL. Interfacing with the terminal At its core, PyTermGUI is based on the ANSI interface module to provide pretty much all of […]

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WebAssembly

Experimental WebAssembly build of GNU Radio

what Experimental WebAssembly build of GNU Radio that runs in a browser tab why For some reason I thought it would be easy narrator: it was not, in fact, easy but I eventually got a proof-of-concept ~working, so I thought I’d share 🙂 status: experimental proof-of-concept This is a proof-of-concept WebAssembly build of GNU Radio Companion which can generate and run basic flowgraphs. It includes gr-qtgui and supports visualization using the QT GUI sink-blocks. The GNU Radio Companion UI is […]

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Word

Word Finder written with python

Tool Information Gathering Write With Python. ██╗ ██╗ ██████╗ ██████╗ ██████╗ ██║ ██║██╔═══██╗██╔══██╗██╔══██╗ ██║ █╗ ██║██║ ██║██████╔╝██║ ██║ ██║███╗██║██║ ██║██╔══██╗██║ ██║ ╚███╔███╔╝╚██████╔╝██║ ██║██████╔╝ ╚══╝╚══╝ ╚═════╝ ╚═╝ ╚═╝╚════╝ [#] Choose one of the options below [1] Word List [2] Add yes character [3] Add no character [4] Add character location [5] Remove yes character [6] Remove no    

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Camera

CamLiFlow: Bidirectional Camera-LiDAR Fusion for Joint Optical Flow and Scene Flow Estimation

This is the official PyTorch implementation for paper “CamLiFlow: Bidirectional Camera-LiDAR Fusion for Joint Optical Flow and Scene Flow Estimation”. (CVPR 2022) News 2022-03-07: We release the code and the pretrained weights. 2022-03-03: Our paper is accepted by CVPR 2022. 2021-11-20: Our paper is available at https://arxiv.org/abs/2111.10502 2021-11-04: Our method ranked #1 on the leaderboard of KITTI Scene Flow. Pretrained Weights Precomputed Results Here, we provide precomputed results for the submission to the online benchmark of KITTI Scene Flow. Environment […]

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Scripts

Quick script for mixing wordlists in a way that maintains order

quick script for mixing wordlists in a way that maintains order. ([1,2],[3,4],[5,6] -> [1,3,5,2,4,6]) edit config.list to your set of preferred wordlists, then run the script and fetch the output on output.txt example of the default config.list file /usr/share/seclists/Discovery/Web-Content/raft-large-files.txt /usr/share/seclists/Discovery/Web-Content/raft-large-directories.txt /usr/share/seclists/Discovery/Web-Content/raft-large-words.txt /usr/share/seclists/Fuzzing/fuzz-Bo0oM.txt GitHub View Github    

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Tool

HaxUnit combines multiple active and passive subdomain enumeration tools

Intro •Installation •Usage •Running HaxUnit •Functions HaxUnit combines multiple active and passive subdomain enumeration tools and port scanning tools with vulnerability discovery tools. For each subdomain enumeration tool you’ll be prompted to add the new discovered subdomains to the list.If you see unrelated subdomains you can decline and you’ll be asked again with only subdomains of the same domain as the input. If you don’t want to be asked to add the domains you can use the -y parameter. Add […]

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Attack

Adversarial Robustness, White-box, Adversarial Attack

“Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack”Ye Liu, Yaya Cheng, Lianli Gao, Xianglong Liu, Qilong Zhang, Jingkuan SongCVPR 2022 Code, model weights, and datasets have been released. We will continue to optimize the code.paper will be released soon. A practical evaluation method should be convenient (i.e., parameter-free), efficient (i.e., fewer iterations) and reliable (i.e., approaching the lower bound of robustness). Towards this target, we propose a parameter-free Adaptive Auto Attack (A3) evaluation method. We apply A3 to over […]

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Machine Learning

Quality Assurance for AI

Backend Requirements Frontend Requirements Backend local development Start the stack with Docker Compose: Now you can open your browser and interact with these URLs: Frontend, built with Docker, with routes handled based on the path: http://localhost Backend, JSON based web API based on OpenAPI: http://localhost/api/ Automatic interactive documentation with Swagger UI (from the OpenAPI backend): http://localhost/docs Alternative automatic documentation with ReDoc (from the OpenAPI backend): http://localhost/redoc PGAdmin, PostgreSQL web administration: http://localhost:5050 Note: you can disable (comment) this component in the […]

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Transformer

MetaFormer : A Unified Meta Framework for Fine-Grained Recognition

A repository for the code used to create and train the model defined in “MetaFormer : A Unified Meta Framework for Fine-Grained Recognition” arxiv:2203.02751 Model zoo Usage python module install Pytorch and torchvision pip install torch==1.5.1 torchvision==0.6.1 git clone https://github.com/NVIDIA/apex cd apex pip install -v –disable-pip-version-check –no-cache-dir –global-option=”–cpp_ext” –global-option=”–cuda_ext” ./ install other requirements pip install opencv-python==4.5.1.48 yacs==0.1.8 data preparation Download inat21,18,17,CUB,NABirds,stanfordcars, andaircraft, put them in respective folders (/datasets/) and    

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PyTorch

MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets

Introduction MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets. Currently, we implmented 7 multi-task recommendation models to enable fair comparison and boost the development of multi-task recommendation algorithms. The currently supported algorithms include: Datasets For the processed dataset, you should directly put the dataset in ‘./data/’ and unpack it. For the original dataset, you should put it in ‘./data/’ and run ‘python preprocess.py –dataset_name NL’. Requirements Python 3.6 PyTorch > 1.10 pandas numpy tqdm Run Parameter […]

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