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Pytorch-Adaptive-Instance-Normalization
A Pytorch implementation of the 2017 Huang et. al. paper "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization"subsurface
A domain recon tool capable of finding subdomains and subnets and then harvesting HTTP screen shots and whois data about them.50-Million-Primes
The first 50 million prime numbers in a .csv file. What more can one ask for?Facehugger
A versatile and modular post-exploitation framework. Enumerate, Escalate and pivot while keeping your scripts in ram and off disk.Pytorch-ZFNet
A pytorch implementation of the ZFNet Architecture described in the paper "Visualizing and Understanding Convolutional Networks" by Matthew D Zeiler, Rob FergusAlexNet
This is a Pytorch implementation of "ImageNet Classification with Deep Convolutional Neural Networks" by Alex Krizhevsky, Ilya Sutskever and Geoffrey E. HintonPytorchResNet
A Pytorch Implementation of the 2015 paper "Deep Residual Learning for Image Recognition" by He et al.PytorchXceptionNet
A Pytorch Implementation of the Xception image recognition architecture described in 2017 paper "Xception: Deep Learning with Depthwise Separable Convolutions" by Francois CholletCustom-Text-To-Speech
A handcrafted text to speech engine that reads words in (at least in a creepy cybernetic aproximation of) my voice!Scikit-CLI
A command line utility for rapidly training scikit-Learn ML models without having to bother to write a single line of codeEZsuid
A python script to automatically enumerate and exploit all common suid vulnerabilities.PytorchUnet
A Pytorch implementation of the Unet Image Segmentation architecture as described in the paper "U-Net: Convolutional Networks for Biomedical Image Segmentation" by Olaf Ronneberger, Philipp Fischer, and Thomas BroxPytorchSegNet
A Pytorch Implementation of the SegNet Image Segmentation architecture described in the 2016 paper "SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation" by Badrinarayanan et al.PytorchMobileNet-v1
A Pytorch Implementation of the MobileNet v1 architecture as described in the 2017 paper "MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications" from GooglePytorchFCN
A Pytorch Implementation of the 2015 paper "Fully Convolutional Networks for Semantic Segmentation" by Jonathan Long, Evan Shelhamer and Trevor DarrellLove Open Source and this site? Check out how you can help us