Python Neural-networks-and-deep-learning Resources

EZ-Graph EZ Graph is a GUI that allows users to make and train neural networks without writing a single line of code. Requirements python 3 pandas num

Fast and customizable vulnerability scanner For JIRA. 🤔 What is this? Jira-Lens 🔍 is a Python Based vulnerability Scanner for JIRA. Jira is a propri

GSCNN This is the official code for: Gated-SCNN: Gated Shape CNNs for Semantic Segmentation Towaki Takikawa, David Acuna, Varun Jampani, Sanja Fidler

UNet++: A Nested U-Net Architecture for Medical Image Segmentation UNet++ is a new general purpose image segmentation architecture for more accurate i

PyTorch-Encoding created by Hang Zhang Documentation Please visit the Docs for detail instructions of installation and usage. Please visit the link to

DFANet This repo is an unofficial pytorch implementation of DFANet:Deep Feature Aggregation for Real-Time Semantic Segmentation log 2019.4.16 After 48

Medical Image Segmentation with Guided Attention This repository contains the code of our paper: "'Multi-scale self-guided attention for medical image

UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te

High-resolution networks and Segmentation Transformer for Semantic Segmentation Branches This is the implementation for HRNet + OCR. The PyTroch 1.1 v

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation This repository contains the source code of our paper, ESPNet (acc

TorchSeg This project aims at providing a fast, modular reference implementation for semantic segmentation models using PyTorch. Highlights Modular De

Implementation for paper LadderNet: Multi-path networks based on U-Net for medical image segmentation This implementation is based on orobix implement

Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor

TuSimple-DUC by Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, and Garrison Cottrell. Introduction This repository is for Under

Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s

Pixel Transposed Convolutional Networks Created by Hongyang Gao, Hao Yuan, Zhengyang Wang and Shuiwang Ji at Texas A&M University. Introduction Pixel

Semantic Segmentation using Adversarial Networks Requirements Chainer (1.23.0) Differences Use of FCN-VGG16 instead of Dilated8 as Segmentor. Caution

Segmentation-Aware Convolutional Networks Using Local Attention Masks [Project Page] [Paper] Segmentation-aware convolution filters are invariant to b

MultiNet MultiNet is able to jointly perform road segmentation, car detection and street classification. The model achieves real-time speed and state-

Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation This repository contains code and models for the method described in: Golnaz

Full-Resolution Residual Networks (FRRN) This repository contains code to train and qualitatively evaluate Full-Resolution Residual Networks (FRRNs) a

Tensorflow implementation of Learning Deconvolution Network for Semantic Segmentation. Install Instructions Works with tensorflow 1.11.0 and uses the

DeconvNet: Learning Deconvolution Network for Semantic Segmentation Created by Hyeonwoo Noh, Seunghoon Hong and Bohyung Han at POSTECH Acknowledgement

PSPNet This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in Chainer. Training Requirement Python 3.4.4+ Chainer 3.0.0b1+

Multipath RefineNet A MATLAB based framework for semantic image segmentation and general dense prediction tasks on images. This is the source code for

ERFNet This code is a toolbox that uses Torch library for training and evaluating the ERFNet architecture for semantic segmentation. NEW!! New PyTorch

Real-Time Semantic Segmentation in TensorFlow Perform pixel-wise semantic segmentation on high-resolution images in real-time with Image Cascade Netwo

Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K

PixelNet: Representation of the pixels, by the pixels, and for the pixels. We explore design principles for general pixel-level prediction problems, f

FC-DenseNet-Tensorflow This is a re-implementation of the 100 layer tiramisu, technically a fully convolutional DenseNet, in TensorFlow (Tiramisu). Th

TensorFlow-ENet TensorFlow implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. This model was tested on th

segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e

ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too

ENet in Caffe Execution times and hardware requirements Network 1024x512 1280x720 Parameters Model size (fp32) ENet 20.4 ms 32.9 ms 0.36 M 1.5 MB SegN

keras-fcn A re-implementation of Fully Convolutional Networks with Keras Installation Dependencies keras tensorflow Install with pip $ pip install git

Keras-FCN This repository contains my implementation of Fully Convolutional Networks in Keras (Tensorflow backend). Currently, semantic segmentation c

Using fully convolutional networks for semantic segmentation (Shelhamer et al.) with caffe for the cityscapes dataset How to get started Download the

FCN-semantic-segmentation Simple end-to-end semantic segmentation using fully convolutional networks [1]. Takes a pretrained 34-layer ResNet [2], remo

Pytorch for Semantic Segmentation This repo has been deprecated currently and I will not maintain it. Meanwhile, I strongly recommend you can refer to

fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as

##A tensorflow implementation of Fully Convolutional Networks For Semantic Segmentation. #USAGE To run the trained classifier on some images: python w

FCN.tensorflow Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (FCNs). The implementation is largely based on the

FCN_via_Keras FCN FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This

Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas

Update An example on how to integrate this code into your own semantic segmentation pipeline can be found in my KittiSeg project repository. tensorflo

Fully Convolutional Networks for Semantic Segmentation This is the reference implementation of the models and code for the fully convolutional network

MatConvNet implementation of the FCN models for semantic segmentation This package contains an implementation of the FCN models (training and evaluati

TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a

Pytorch-segmentation-toolbox DOC Pytorch code for semantic segmentation. This is a minimal code to run PSPnet and Deeplabv3 on Cityscape dataset. Shor

DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute

SegNet SegNet is a model of semantic segmentation based on Fully Comvolutional Network. This repository contains the implementation of learning and te

Torch implementation of SegNet and deconvolutional network

SegNet SegNet is a TensorFlow implementation of the segmentation network proposed by Kendall et al., with cool features like strided deconvolution, a

Segnet is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This is implementation of http://arxiv.org/pdf/15

Caffe SegNet This is a modified version of Caffe which supports the SegNet architecture As described in SegNet: A Deep Convolutional Encoder-Decoder A

Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm

pytorch Implementation of U-Net, R2U-Net, Attention U-Net, Attention R2U-Net U-Net: Convolutional Networks for Biomedical Image Segmentation https://a

Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. The main features of this library are: High level API (just

Retina blood vessel segmentation with a convolution neural network (U-net) This repository contains the implementation of a convolutional neural netwo

Real-Time Semantic Segmentation in Mobile device This project is an example project of semantic segmentation for mobile real-time app. The architectur

Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras. Implementation of various Deep Image Segmentation mo

Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu

Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne

ZF_UNET_224 Pretrained Model Modification of convolutional neural net "UNET" for image segmentation in Keras framework Requirements Python 3.*, Keras

Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne

A combination of autoregressors and autoencoders using XLNet for sentiment analysis Abstract In this paper sentiment analysis has been performed in or

Federated Learning with Non-IID Data This is an implementation of the following paper: Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vik

DubbingAssistants This app gets your sutitle.srt and proccess it to extract sentences, and also find Start time and End time of them. Step 1: install

SSQAuto (Splunk Search Query Automation) Example Of Splunk Search Query With Python And Splunk Python SDK installation: ➜ ~ git clone https://github.c

GATER This repository contains the code for our EMNLP 2021 paper “Heterogeneous Graph Neural Networks for Keyphrase Generation”. Our implementation is

anonymity Lets you remove all friends, leave GCs, and leave servers, in an instant! You can also do each of them by themselves. First, you need to get

minecraft-hack-installer You want to uto-update your private minecraft client? Give this to developer and enjoy! Steps to do: Install libraries: pip i

Identifies the faulty wafer before it can be used for the fabrication of integrated circuits and, in photovoltaics, to manufacture solar cells. The project retrains itself after every prediction, making it more robust and generalized over time.

CNN Based Meta-Learning for Noisy Image Classification and Template Matching Introduction This master thesis used a few-shot meta learning approach to

Bavera is an extensive and extendable Python 3.x library for the Discord API. Bavera boasts the following major features: Expressive, functiona

Desktop background on Windows 10, based on current weather and time A python script that changes our background based on current weather and time of t

Fusion-360-Add-In-PuzzleSpline Fusion 360 Add-in that creates a pair of toothed curves that can be used to split a body and create two pieces that sli

CookieClicker Usage: Let's check your chrome navigator version : Consequently, you have to : download the right chromedriver in the follow link : http

PyTorch-LIT PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices. With

GraphWar: Arms Race in Graph Adversarial Learning NOTE: GraphWar is still in the early stages and the API will likely continue to change. 🚀 Installat

G2S This is the official code for ICRA 2021 Paper: Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation by Hemang

Welcome This is a minimal project using graphene with django and user authentication to expose a graphql endpoint. Definitely checkout how I have mana

Weather Bot Besac Weather_besac is a French twitter bot that tweet the weather of the city of Besançon in Franche-Comté in France every day at 8am and

AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed

Python dataset creator to construct datasets composed of OpenFace extracted features and Shimmer3 GSR+ Sensor datas

RestApi-With-Django-3.2-And-Django-Rest-Framework Description This repository is a Software of Development with Python. Virtual Using pipenv, virtuale

Transformers: from NLP to CV This is a practical introduction to Transformers from Natural Language Processing (NLP) to Computer Vision (CV) Introduct

Einshape: DSL-based reshaping library for JAX and other frameworks. The jnp.einsum op provides a DSL-based unified interface to matmul and tensordot o

FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.

Date Time Expression dte is a WIP date-time processing language with focus on broad interpretation. If you don't think it's intuitive, it's most likel

Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.

The-Emergence-of-Objectness This is the official released code for our paper, The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos

Anime Face Detector This is an anime face detector using mmdetection and mmpose. (To avoid copyright issues, I use generated images by the TADNE model

A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.

TTSR Official PyTorch implementation of the paper Learning Texture Transformer Network for Image Super-Resolution accepted in CVPR 2020. Contents Intr

SusPedal-Gen This is the official repository of Learning to Generate Piano Music With Sustain Pedals Demo Page Dataset The dataset used in this projec

PVDNet: Recurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes This repository contains the official PyTorch implementatio

History Aware Multimodal Transformer for Vision-and-Language Navigation This repository is the official implementation of History Aware Multimodal Tra

httprobe Take a list of domains and probe for working http and https servers. Install ▶ go get -u github.com/tomnomnom/httprobe Basic Usage httprobe

MassDNS A high-performance DNS stub resolver MassDNS is a simple high-performance DNS stub resolver targeting those who seek to resolve a massive amou