AWS

Scans Amazon Route53 across an AWS Organization for domain records vulnerable to takeover

domain-protect scans Amazon Route53 across an AWS Organization for domain records vulnerable to takeover deploy to security audit account deploy to security audit account scan your entire AWS Organization receive alerts by Slack or email or manually scan from your laptop subdomain detection functionality scans Amazon Route53 Alias records to identify CloudFront distributions with missing S3 origin scans Amazon Route53 CNAME records to identify CloudFront distributions with missing S3 origin scans Amazon Route53 for ElasticBeanstalk Alias records vulnerable to takeover […]

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Games

Dragon Quest IV English + Party Chat Script Patcher for Japan ROM

dqiv-nds-en-script-patcher Patches English script files from the US version of Dragon Quest IV for Nintendo DS and Android so they are rendered nicely when used with the Japan ROM. Addresses various issues caused by the Japan game code being not fully compatible with English script files. Why? The US version of Dragon Quest IV for the Nintendo DS did not have party chat (https://dragon-quest.org/wiki/Party_Chat) and seems to completely disable party chat in the game code, so it is not normally […]

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Framework

A Framework meant for the exploitation of iOS devices

iPwn A Framework meant for the exploitation of iOS devices. iPwn is a framework meant for exploiting and and gaining access to iOS devices. It also has an extension that is a mini-framework called ‘iSteal’ that is meant for post-exploitation (after you get access to the device). This description will walk you through the different ways and steps to get access to an iOS device and harvest information from it. The first way of getting access to an iOS device. […]

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Machine Learning

Oriented RepPoints for Aerial Object Detection

OrientedRepPoints Oriented RepPoints employs a set of adaptive points to capture the geometric and spatial information of the arbitrary-oriented objects, which is able to automatically arrange themselves over the object in a spatial and semantic scenario. To facilitate the supervised learning, the oriented conversion function is proposed to explicitly map the adaptive point set into an oriented bounding box. Moreover, we introduce an effective quality assessment measure to select the point set samples for training, which can choose the representative […]

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Computer Vision

Global Filter Networks for Image Classification

GFNet Created by Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for GFNet. Global Filter Networks is a transformer-style architecture that learns long-term spatial dependencies in the frequency domain with log-linear complexity. Our architecture replaces the self-attention layer in vision transformers with three key operations: a 2D discrete Fourier transform, an element-wise multiplication between frequency-domain features and learnable global filters, and a 2D inverse Fourier transform. Global Filter Layer GFNet is a conceptually […]

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Machine Learning

Drone detection using YOLOv5 in python

Detect_Drone Drone detection using YOLOv5 in python. Install Python >= 3.6.0 required with all requirements.txt dependencies installed: $ git clone https://github.com/tusharsarkar3/Detect_Drone.git $ pip install -r requirements.txt Training The structure of the file system is of great importance here so these images will show you the correct way of organizing it. The main folder named datasets should be on the same level as this repository. The next steps are elaborated in the images: The two folders with images and labels respectively […]

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API

A collection of metrics for evaluating timbre dissimilarity using the TorchMetrics API

A collection of metrics for evaluating timbre dissimilarity using the TorchMetrics API Installation pip install -e . Usage import timbremetrics datasets = timbremetrics.list_datasets() dataset = datasets[0] # get the first timbre dataset # MAE between target dataset and pred embedding distances metric = timbremetrics.TimbreMAE( margin=0.0, dataset=dataset, distance=timbremetrics.l1 ) # get numpy audio for the timbre dataset audio = timbremetrics.get_audio(dataset) # get arbitrary embeddings for the timbre dataset’s audio embeddings = net(audio) # compute the metric metric(embeddings) Metrics The following metrics […]

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PyTorch

Look before you leap: learning landmark features for one-stage visual grounding

LBYL-Net This repo implements paper Look Before You Leap: Learning Landmark Features For One-Stage Visual Grounding CVPR 2021. Getting Started Prerequisites python 3.7 pytorch 10.0 cuda 10.0 gcc 4.92 or above Installation Then clone the repo and install dependencies. git clone https://github.com/svip-lab/LBYLNet.git cd LBYLNet pip install requirements.txt You also need to install our landmark feature convolution: cd ext git clone https://github.com/hbb1/landmarkconv.git cd landmarkconv/lib/layers python setup.py install –user We follow dataset structure DMS and FAOA. For convience, we have pack them […]

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Machine Learning

A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation

clDice CVPR 2021 Authors: Suprosanna Shit and Johannes C. Paetzold et al. @article{shit2020cldice, title={clDice – a Topology-Preserving Loss Function for Tubular Structure Segmentation}, author={Shit, Suprosanna and Paetzold, Johannes C and Sekuboyina, Anjany and Zhylka, Andrey and Ezhov, Ivan and Unger, Alexander and Pluim, Josien PW and Tetteh, Giles and Menze, Bjoern H}, journal={arXiv preprint arXiv:2003.07311}, year={2020} } Abstract Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research. For such structures, […]

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Machine Learning

StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation

StyleSpace-pytorch Implementation of StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation (https://arxiv.org/pdf/2011.12799.pdf) in PyTorch This implementation is mostly relied on rosinality’s stylegan2-pytorch Requirements I have tested on: Usage For the index and channel, please check the paper (https://arxiv.org/pdf/2011.12799.pdf), e.g., (11_286), channel 286 of generator level 11. FFHQ Firstly, you should download pretrained model from here and place the stylegan2-ffhq-config-f.pkl into pretrained folder. Open the notebook StyleSpace_FFHQ.ipynb Car LSUN GitHub https://github.com/xrenaa/StyleSpace-pytorch    

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