1005 Repositories
Python tensorflow-course Libraries
Text to image synthesis using thought vectors
Text To Image Synthesis Using Thought Vectors This is an experimental tensorflow implementation of synthesizing images from captions using Skip Though
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations.
IllustrationGAN A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations. Generated Images
Learning Chinese Character style with conditional GAN
zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(ๅญๅฐๅญ, me
Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"
BEGAN in Tensorflow Tensorflow implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks. Requirements Python 2.7 or 3.x Pillow tq
EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow
EfficientDet This is an implementation of EfficientDet for object detection on Keras and Tensorflow. The project is based on the official implementati
Powerful and efficient Computer Vision Annotation Tool (CVAT)
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
๐ Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
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
Collection of generative models in Tensorflow
tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th
Build Graph Nets in Tensorflow
Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact [email protected] for comments a
Time Series Prediction with tf.contrib.timeseries
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
Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting Note: You can find here the accompanying seq2seq RNN forecas
Human Pose estimation with TensorFlow framework
Human Pose Estimation with TensorFlow Here you can find the implementation of the Human Body Pose Estimation algorithm, presented in the DeeperCut and
This is a tensorflow-based rotation detection benchmark, also called AlphaRotate.
AlphaRotate: A Rotation Detection Benchmark using TensorFlow Abstract AlphaRotate is maintained by Xue Yang with Shanghai Jiao Tong University supervi
sktime companion package for deep learning based on TensorFlow
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
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
NNI Doc | ็ฎไฝไธญๆ NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture
Provide an input CSV and a target field to predict, generate a model + code to run it.
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
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
Alpha Zero General (any game, any framework!) A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play
Open source hardware and software platform to build a small scale self driving car.
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.
BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models.
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.
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 is an easy to use AI solution that allows you to make and train your neural networks without a single line of code.
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
Tensorflow Implementation of Pixel Transposed Convolutional Networks (PixelTCN and PixelTCL)
Pixel Transposed Convolutional Networks Created by Hongyang Gao, Hao Yuan, Zhengyang Wang and Shuiwang Ji at Texas A&M University. Introduction Pixel
A Kitti Road Segmentation model implemented in tensorflow.
KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark
Real-time Joint Semantic Reasoning for Autonomous Driving
MultiNet MultiNet is able to jointly perform road segmentation, car detection and street classification. The model achieves real-time speed and state-
Tensorflow implementation of "Learning Deconvolution Network for Semantic Segmentation"
Tensorflow implementation of Learning Deconvolution Network for Semantic Segmentation. Install Instructions Works with tensorflow 1.11.0 and uses the
Training PSPNet in Tensorflow. Reproduce the performance from the paper.
Training Reproduce of PSPNet. (Updated 2021/04/09. Authors of PSPNet have provided a Pytorch implementation for PSPNet and their new work with support
TensorFlow-based implementation of "Pyramid Scene Parsing Network".
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
TensorFlow implementation of original paper : https://github.com/hszhao/PSPNet
Keras implementation of PSPNet(caffe) Implemented Architecture of Pyramid Scene Parsing Network in Keras. For the best compability please use Python3.
ICNet and PSPNet-50 in Tensorflow for real-time semantic segmentation
Real-Time Semantic Segmentation in TensorFlow Perform pixel-wise semantic segmentation on high-resolution images in real-time with Image Cascade Netwo
TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".
ICNet_tensorflow This repo provides a TensorFlow-based implementation of paper "ICNet for Real-Time Semantic Segmentation on High-Resolution Images,"
Keras implementation of 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
DilatedNet in Keras for image segmentation
Keras implementation of DilatedNet for semantic segmentation A native Keras implementation of semantic segmentation according to Multi-Scale Context A
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
FC-DenseNet-Tensorflow This is a re-implementation of the 100 layer tiramisu, technically a fully convolutional DenseNet, in TensorFlow (Tiramisu). Th
TensorFlow implementation of ENet
TensorFlow-ENet TensorFlow implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. This model was tested on th
TensorFlow implementation of ENet, trained on the Cityscapes dataset.
segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e
A TensorFlow implementation of FCN-8s
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 task for ADE20k & cityscapse dataset, based on several models.
semantic-segmentation-tensorflow This is a Tensorflow implementation of semantic segmentation models on MIT ADE20K scene parsing dataset and Cityscape
fcn by tensorflow
Update An example on how to integrate this code into your own semantic segmentation pipeline can be found in my KittiSeg project repository. tensorflo
A tensorflow implementation of Fully Convolutional Networks For Semantic Segmentation
##A tensorflow implementation of Fully Convolutional Networks For Semantic Segmentation. #USAGE To run the trained classifier on some images: python w
Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation
FCN.tensorflow Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (FCNs). The implementation is largely based on the
Keras-tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation๏ผUnfinished๏ผ
Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas
An Implementation of Fully Convolutional Networks in Tensorflow.
Update An example on how to integrate this code into your own semantic segmentation pipeline can be found in my KittiSeg project repository. tensorflo
Tensorflow implementation of DeepLabv2
TF-deeplab This is a Tensorflow implementation of DeepLab, compatible with Tensorflow 1.2.1. Currently it supports both training and testing the ResNe
This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset.
DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Up
DeepLab-ResNet rebuilt in TensorFlow
DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Fr
SegNet including indices pooling for Semantic Segmentation with tensorflow and keras
SegNet SegNet is a model of semantic segmentation based on Fully Comvolutional Network. This repository contains the implementation of learning and te
Implement slightly different caffe-segnet in tensorflow
Tensorflow-SegNet Implement slightly different (see below for detail) SegNet in tensorflow, successfully trained segnet-basic in CamVid dataset. Due t
SegNet-like Autoencoders in TensorFlow
SegNet SegNet is a TensorFlow implementation of the segmentation network proposed by Kendall et al., with cool features like strided deconvolution, a
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. The main features of this library are: High level API (just
Real-Time Semantic Segmentation in Mobile device
Real-Time Semantic Segmentation in Mobile device This project is an example project of semantic segmentation for mobile real-time app. The architectur
Generic U-Net Tensorflow implementation for image segmentation
Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu
The main aim of this project is to avoid the accidents in shredding ( Waste Recycling Industry )
shredder-Machine-Hand-Safety The main aim of this project is to avoid the accidents in shredding ( Waste Recycling Industry ) . The Basic function of
Models Supported: AlbUNet [18, 34, 50, 101, 152] (1D and 2D versions for Single and Multiclass Segmentation, Feature Extraction with supports for Deep Supervision and Guided Attention)
AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed
TensorLight - A high-level framework for TensorFlow
TensorLight is a high-level framework for TensorFlow-based machine intelligence applications. It reduces boilerplate code and enables advanced feature
Material for dataviz course at university of Bordeaux
Material for dataviz course at university of Bordeaux
Doom oโclock is a website/project that features a countdown of โwhen will the earth endโ and a greenhouse gas effect emission prediction thatโs predicted
Doom oโclock is a website/project that features a countdown of โwhen will the earth endโ and a greenhouse gas effect emission prediction thatโs predicted
ML for NLP and Computer Vision.
Sparrow is our open-source ML product. It runs on Skipper MLOps infrastructure.
Predict the latency time of the deep learning models
Deep Neural Network Prediction Step 1. Genernate random parameters and Run them sequentially : $ python3 collect_data.py -gp -ep -pp -pl pooling -num
We have built a Voice based Personal Assistant for people to access files hands free in their device using natural language processing.
Voice Based Personal Assistant We have built a Voice based Personal Assistant for people to access files hands free in their device using natural lang
Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE
SMU A Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/abs/211
Course: Information Security with Python
Curso: Seguranรงa da Informaรงรฃo com Python Curso realizado atravรจs da Plataforma da Digital Innovation One Prof: Bruno Dias Conteรบdo: Introduรงรฃo aos co
An Advanced Local Network IP Scanner, made in python of course!
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An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)
An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)
Kalidokit is a blendshape and kinematics solver for Mediapipe/Tensorflow.js face, eyes, pose, and hand tracking models
Blendshape and kinematics solver for Mediapipe/Tensorflow.js face, eyes, pose, and hand tracking models.
TensorFlow 2 implementation of the Yahoo Open-NSFW model
TensorFlow 2 implementation of the Yahoo Open-NSFW model
A tensorflow=1.13 implementation of Deconvolutional Networks on Graph Data (NeurIPS 2021)
GDN A tensorflow=1.13 implementation of Deconvolutional Networks on Graph Data (NeurIPS 2021) Abstract In this paper, we consider an inverse problem i
Apollo optimizer in tensorflow
Apollo Optimizer in Tensorflow 2.x Notes: Warmup is important with Apollo optimizer, so be sure to pass in a learning rate schedule vs. a constant lea
Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js
Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js
Sample code for Harry's Airflow online trainng course
Sample code for Harry's Airflow online trainng course You can find the videos on youtube or bilibili. I am working on adding below things: the slide p
Members: Thomas Longuevergne Program: Network Security Course: 1DV501 Date of submission: 2021-11-02
Mini-project report Members: Thomas Longuevergne Program: Network Security Course: 1DV501 Date of submission: 2021-11-02 Introduction This project was
A simple project on Data Visualization for CSCI-40 course.
Simple-Data-Visualization A simple project on Data Visualization for CSCI-40 course - the instructions can be found here SAT results in New York in 20
Traingenerator ๐ง A web app to generate template code for machine learning โจ
Traingenerator ๐ง A web app to generate template code for machine learning โจ ๐ Traingenerator is now live! ๐
Using a Seq2Seq RNN architecture via TensorFlow to predict future Bitcoin prices
Recurrent Bitcoin Network A Data Science Thesis Project About This repository contains the source code for implementing Bitcoin price prediciton using
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation
DistMIS Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation. DistriMIS Distributing Deep Learning Hyperparameter Tuning
Planning Algorithms in AI and Robotics. MSc course at Skoltech Data Science program
Planning Algorithms in AI and Robotics course T2 2021-22 The Planning Algorithms in AI and Robotics course at Skoltech, MS in Data Science, during T2,
Algorithms covered in the Bioinformatics Course part of the Cambridge Computer Science Tripos
Bioinformatics This is a repository of all the algorithms covered in the Bioinformatics Course part of the Cambridge Computer Science Tripos Algorithm
Unofficial implementation of the paper: PonderNet: Learning to Ponder in TensorFlow
PonderNet-TensorFlow This is an Unofficial Implementation of the paper: PonderNet: Learning to Ponder in TensorFlow. Official PyTorch Implementation:
Use Google's BERT for named entity recognition ๏ผCoNLL-2003 as the dataset๏ผ.
For better performance, you can try NLPGNN, see NLPGNN for more details. BERT-NER Version 2 Use Google's BERT for named entity recognition ๏ผCoNLL-2003
Tensorflow AffordanceNet and AffContext implementations
AffordanceNet and AffContext This is tensorflow AffordanceNet and AffContext implementations. Both are implemented and tested with tensorflow 2.3. The
Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation
tf-imle Tensorflow 2 and PyTorch implementation and Jupyter notebooks for Implicit Maximum Likelihood Estimation (I-MLE) proposed in the NeurIPS 2021
This repo represents all we learned and are learning in Data Structure course.
DataStructure Journey This repo represents all we learned and are learning in Data Structure course which is based on CLRS book and is being taught by
An Automated udemy coupons scraper which scrapes coupons and autopost the result in blogspot post
Autoscraper-n-blogger An Automated udemy coupons scraper which scrapes coupons and autopost the result in blogspot post and notifies via Telegram bot
๐ฅ Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization ๐ฅ
๐ฅ Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization ๐ฅ
Official implementation of DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations in TensorFlow 2
DreamerPro Official implementation of DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations in TensorFl
Django Course Project - TextCorrector
Django-TextUtils Django Course Project A tool for analyzing text data in Django backend. It is a project where you can do some of the things with you
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:
Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)
Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati
A tensorflow model that predicts if the image is of a cat or of a dog.
Quick intro Hello and thank you for your interest in my project! This is the backend part of a two-repo application. The other part can be found here
Face Mask Detection System built with OpenCV, TensorFlow using Computer Vision concepts
Face mask detection Face Mask Detection System built with OpenCV, TensorFlow using Computer Vision concepts in order to detect face masks in static im
A lightweight python AUTOmatic-arRAY library.
A lightweight python AUTOmatic-arRAY library. Write numeric code that works for: numpy cupy dask autograd jax mars tensorflow pytorch ... and indeed a
TensorFlow Metal Backend on Apple Silicon Experiments (just for fun)
tf-metal-experiments TensorFlow Metal Backend on Apple Silicon Experiments (just for fun) Setup This is tested on M1 series Apple Silicon SOC only. Te
These data visualizations were created for my introductory computer science course using Python
Homework 2: Matplotlib and Data Visualization Overview These data visualizations were created for my introductory computer science course using Python
Hierarchical probabilistic 3D U-Net, with attention mechanisms (โ๐๐ต๐ต๐ฆ๐ฏ๐ต๐ช๐ฐ๐ฏ ๐-๐๐ฆ๐ต, ๐๐๐๐ฆ๐ด๐๐ฆ๐ต) and a nested decoder structure with deep supervision (โ๐๐๐ฆ๐ต++).
Hierarchical probabilistic 3D U-Net, with attention mechanisms (โ๐๐ต๐ต๐ฆ๐ฏ๐ต๐ช๐ฐ๐ฏ ๐-๐๐ฆ๐ต, ๐๐๐๐ฆ๐ด๐๐ฆ๐ต) and a nested decoder structure with deep supervision (โ๐๐๐ฆ๐ต++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
๐ค Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | ็ฎไฝไธญๆ | ็น้ซไธญๆ | ํ๊ตญ์ด State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow ๐ค Transformers provides thousands of pretrai
Solutions to all 6 programming assignments in Dan Boneh's course Cryptography I, in statically typed Python.
Solutions to Cryptography I programming exercises Dan Boneh from Stanford University has an excellent online course on cryptography, hosted on Courser
Implementation of ConvMixer-Patches Are All You Need? in TensorFlow and Keras
Patches Are All You Need? - ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in t