Python Tensorflow-image-models Resources

Context Encoders: Feature Learning by Inpainting CVPR 2016 [Project Website] [Imagenet Results] Sample results on held-out images: This is the trainin

CycleGAN PyTorch | project page | paper Torch implementation for learning an image-to-image translation (i.e. pix2pix) without input-output pairs, for

pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat

Image De-raining Using a Conditional Generative Adversarial Network [Paper Link] [Project Page] He Zhang, Vishwanath Sindagi, Vishal M. Patel In this

Invertible Conditional GANs This is the implementation of the IcGAN model proposed in our paper: Invertible Conditional GANs for image editing. Novemb

###Generative Adversarial Text-to-Image Synthesis Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee This is the

Text To Image Synthesis Using Thought Vectors This is an experimental tensorflow implementation of synthesizing images from captions using Skip Though

StackGAN Pytorch implementation Inception score evaluation StackGAN-v2-pytorch Tensorflow implementation for reproducing main results in the paper Sta

A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions

iGAN: Interactive Image Generation via Generative Adversarial Networks Project | Youtube | Paper Recent projects: [pix2pix]: Torch implementation for

IllustrationGAN A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations. Generated Images

AGIS-Net Introduction This is the official PyTorch implementation of the Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning. paper | suppl

zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(字到字, me

BEGAN in Tensorflow Tensorflow implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks. Requirements Python 2.7 or 3.x Pillow tq

This piece of code is a User Welcomer with Image Manipulation using Python and Pillow (PIL).

Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.

EfficientDet This is an implementation of EfficientDet for object detection on Keras and Tensorflow. The project is based on the official implementati

Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our

Semantic Image Synthesis with SPADE New implementation available at imaginaire repository We have a reimplementation of the SPADE method that is more

Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl

Ladder Variational Autoencoders (LVAE) PyTorch implementation of Ladder Variational Autoencoders (LVAE) [1]: where the variational distributions q at

tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th

Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact [email protected] for comments a

Hummingbird Introduction Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to se

LowRankModels.jl LowRankModels.jl is a Julia package for modeling and fitting generalized low rank models (GLRMs). GLRMs model a data array by a low r

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

TensorFlow-Time-Series-Examples Additional examples for TensorFlow Time Series(TFTS). Read a Time Series with TFTS From a Numpy Array: See "test_input

Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting Note: You can find here the accompanying seq2seq RNN forecas

DOS Punk Text Inspired by MAX CAPACITY's DOS Punks & the amazing DOS Punk community. DOS Punk Text is a Python 3 script that renders a DOS Punk image

health-lesion-stovol healthy and lesion models for learning based on the joint estimation of stochasticity and volatility Reference please cite this p

Fast Image Retrieval (FIRe) is an open source image retrieval project release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This project implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.

CSF Code of Classification Saliency-Based Rule for Visible and Infrared Image Fusion Tips: For testing: CUDA_VISIBLE_DEVICES=0 python main.py For trai

Image Quality Assessment using Contrastive Learning Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli and Alan C. Bovik This is the offi

Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving This is the source code for our paper Frequency Domain Image Tran

High performance distributed framework for training deep learning recommendation models based on PyTorch.

Human Pose Estimation with TensorFlow Here you can find the implementation of the Human Body Pose Estimation algorithm, presented in the DeeperCut and

SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks

Fast Image Retrieval (FIRe) is an open source image retrieval project release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This project implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.

CenterPose Overview This repository is the official implementation of the paper "Single-stage Keypoint-based Category-level Object Pose Estimation fro

vartests is a Python library to perform some statistic tests to evaluate Value at Risk (VaR) Models, such as: T-test: verify if mean of distribution i

Pnuemonia Normal detection by using XRay images. Got image datas from kaggle(link is given in sources.txt file) also normal xray images from other site (also link is given) in order to avoid data disbalancing.

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa

AlphaRotate: A Rotation Detection Benchmark using TensorFlow Abstract AlphaRotate is maintained by Xue Yang with Shanghai Jiao Tong University supervi

ISC-Track2-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 2. Required dependencies To begin with

ISC-Track1-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 1. Required dependencies To begin with

Scalable Intervention Target Estimation in Linear Models Implementation of the paper Scalable Intervention Target Estimation in Linear Models (NeurIPS

Spectral-spatial contrastive clustering (SSCC) Yaoming Cai, Yan Liu, Zijia Zhang, Zhihua Cai, and Xiaobo Liu, Large-scale Hyperspectral Image Clusteri

RobustBioNLP Improving the robustness and performance of biomedical NLP models through adversarial training In this repository you can find suppliment

diffusion-channels Source code for paper "Deep Diffusion Models for Robust Channel Estimation". Generic flow: Use 'matlab/main.mat' to generate traini

Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?

AfriBERTa: Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages This repository contains the code for the pa

PythonImage2PDF A simple Python script to convert multiple images into a single PDF-document. Created basically for only my own needs for converting m

imgAnalyser - Un script pour obtenir la liste des pixels d'une image correspondant à plusieurs couleurs Ce script à pour but, à partir d'une image, de

Image processing using OpenCv Write a program that opens the webcam, and the user selects one of the following on the video: ✅ If the user presses the

Fast Image Retrieval is an open source image retrieval framework release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This framework implements most of the major binary hashing methods, together with both popular backbone networks and public datasets.

liquid_scikit_learn Scikit learn library models to account for data and concept drift. This python library focuses on solving data drift and concept d

gtk-image-selector This is an attempt to restore Gtk Image Chooser "lost functionality": displaying an image preview when selecting images... This is

The code in this toolbox implements the "Spectralformer: Rethinking hyperspectral image classification with transformers". More specifically, it is detailed as follow.

NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and

survivalstan: Survival Models in Stan author: Jacki Novik Overview Library of Stan Models for Survival Analysis Features: Variety of standard survival

Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo

Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI

DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc

Responsible Machine Learning With Great Power Comes Great Responsibility. Voltaire (well, maybe) How to develop machine learning models in a responsib

InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig

AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn

Alpha Zero General (any game, any framework!) A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play

Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions.

m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code

Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

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

PyTorch implementation of UNet++ (Nested U-Net) This repository contains code for a image segmentation model based on UNet++: A Nested U-Net Architect

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

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

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

KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark

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

Training Reproduce of PSPNet. (Updated 2021/04/09. Authors of PSPNet have provided a Pytorch implementation for PSPNet and their new work with support

PSPNet_tensorflow Important Code is fine for inference. However, the training code is just for reference and might be only used for fine-tuning. If yo

Keras implementation of PSPNet(caffe) Implemented Architecture of Pyramid Scene Parsing Network in Keras. For the best compability please use Python3.

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

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

ICNet_tensorflow This repo provides a TensorFlow-based implementation of paper "ICNet for Real-Time Semantic Segmentation on High-Resolution Images,"

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

Multi-Scale Context Aggregation by Dilated Convolutions Introduction Properties of dilated convolution are discussed in our ICLR 2016 conference paper

Keras implementation of DilatedNet for semantic segmentation A native Keras implementation of semantic segmentation according to Multi-Scale Context A

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

FCN-8s implementation in TensorFlow Contents Overview Examples and demo video Dependencies How to use it Download pre-trained VGG-16 Overview This is

semantic-segmentation-tensorflow This is a Tensorflow implementation of semantic segmentation models on MIT ADE20K scene parsing dataset and Cityscape