Python Keras-classify Resources

torchinfo (formerly torch-summary) Torchinfo provides information complementary to what is provided by print(your_model) in PyTorch, similar to Tensor

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear

ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme

Learning to Classify Images without Labels This repo contains the Pytorch implementation of our paper: SCAN: Learning to Classify Images without Label

Monopol Indonesian Car License Plate (Indonesia Mobil Nomor Polisi) Character Recognition using Tensorflow, Keras and OpenCV. Background This applicat

DeepJ: A model for style-specific music generation https://arxiv.org/abs/1801.00887 Abstract Recent advances in deep neural networks have enabled algo

(intron I nterrogator and C lassifier) intronIC is a program that can be used to classify intron sequences as minor (U12-type) or major (U2-type), usi

Memefly You can find the project at MemeflyAI. Contributors Nick Buukhalter Harsh Desai Han Lee Project Overview Trello Board Product Canvas Automatic

Make Sure the dataset file "spamData.mat" is in the folder spam\src Environment: Python --version = 3.7 Third Party: numpy, matplotlib, math, scipy

Yolact-keras实例分割模型在keras当中的实现 目录 性能情况 Performance 所需环境 Environment 文件下载 Download 训练步骤 How2train 预测步骤 How2predict 评估步骤 How2eval 参考资料 Reference 性能情况 训练数

Rest API Written In Python To Classify NSFW Images.

Simple GAN This is my attempt to make a wrapper class for a GAN in keras which can be used to abstract the whole architecture process. Simple GAN Over

AdaptationSeg This is the Python reference implementation of AdaptionSeg proposed in "Curriculum Domain Adaptation for Semantic Segmentation of Urban

PersonLab This is a Keras implementation of PersonLab for Multi-Person Pose Estimation and Instance Segmentation. The model predicts heatmaps and vari

PyTASER PyTASER is a Python (3.9+) library and set of command-line tools for classifying spectral features in bulk materials, post-DFT. The goal of th

frugally-deep Use Keras models in C++ with ease Table of contents Introduction Usage Performance Requirements and Installation FAQ Introduction Would

SE-MSCNN: A Lightweight Multi-scaled Fusion Network for Sleep Apnea Detection Using Single-Lead ECG Signals Abstract Sleep apnea (SA) is a common slee

TokenLearner: What Can 8 Learned Tokens Do for Images and Videos? Source: Improving Vision Transformer Efficiency and Accuracy by Learning to Tokenize

Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend

Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml

Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend

Chinese named entity recognization (Bilstm with Keras) Project Structure ./ ├── README.md ├── data │   ├── README.md │   ├── data 数据集 │   │   ├─

Chinese named entity recognization (bert/roberta/macbert/bert_wwm with Keras)

Chinese NLP (albert/electra with Keras) Named Entity Recognization Project Structure ./ ├── NER │   ├── __init__.py │   ├── log

PokeGAN A tensorflow/keras implementation of StyleGAN to generate images of new Pokemon. Dataset The model has been trained on dataset that includes 8

Zero-DCE and Zero-DCE++(Lite architechture for Mobile and edge Devices) Papers Abstract The paper presents a novel method, Zero-Reference Deep Curve E

You can watch the details of the project on my youtube channel Project Interface Project Second Interface Goal= Correctly guessing the classification

emoji2vec This is my attempt to train, visualize and evaluate emoji embeddings as presented by Ben Eisner, Tim Rocktäschel, Isabelle Augenstein, Matko

PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear

Lobe This is a Home Assistant custom component for Lobe. Lobe is an AI tool that can classify images. This component lets you easily use an exported m

Weights_Keras_2_Pytorch 最近想在Pytorch项目里使用一下谷歌的NIMA，但是发现没有预训练好的pytorch权重，于是整理了一下将Keras预训练权重转为Pytorch的代码，目前是支持Keras的Conv2D, Dense, DepthwiseConv2D, Batch

NOTE This implementation is fork of https://github.com/XifengGuo/CapsNet-Keras , applied to IMDB texts reviews dataset. CapsNet-Keras A Keras implemen

H2G-Net This repository contains the code relevant for the proposed design H2G-Net, which was introduced in the manuscript "Hybrid guiding: A multi-re

deepface Deepface is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid

rapidnlp-datasets Data pipelines for both TensorFlow and PyTorch ! If you want to load public datasets, try: tensorflow/datasets huggingface/datasets

MusicGenreClassification Academic research in the field of Deep Learning (Deep Neural Networks) and Sound Processing, Tel Aviv University. Featured in

Semi-Supervised Learning with Ladder Networks in Keras This is an implementation of Ladder Network in Keras. Ladder network is a model for semi-superv

TF-Unet General purpose U-Network implemented in Keras for image segmentation Getting started • Training • Evaluation Getting started Looking for Jupy

Sarus published models Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are

**This project is no longer active. Please check out TensorFlow.js.** The Keras.js demos still work but is no longer updated. Run Keras models in the

DeepBay This project was created with the objective of compile Machine Learning Architectures created using Tensorflow or Keras. The architectures mus

Convert ONNX model graph to Keras model format.

Semantic segmentation using Tensorflow eager execution Requirement Python 2.7+ Tensorflow-gpu OpenCv H5py Scikit-learn Numpy Imgaug Train with eager e

DenseNet-Keras with ImageNet Pretrained Models This is an Keras implementation of DenseNet with ImageNet pretrained weights. The weights are converted

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

This repository provides the official implementation of "Robust channel-wise illumination estimation." accepted in BMVC (2021).

Artificial Neural Network This repository contain implementation of Artificial Neural Network Algorithm in several programming languanges and framewor

Mask R-CNN for Object Detection and Segmentation This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bound

this is a simple rest api serving a deep learning model that classifies human gender based on their faces. (vgg16 transfare learning)

Steps to run = Download the cora dataset from this link : https://linqs.soe.ucsc.edu/data unzip the files in the folder input/cora cd code python eda

Keras Model Implementation Walkthrough

The repository contains the implementations for Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects. Model

Yogi-Optimizer_Keras This is an implementation of Googles Yogi-Optimizer in Keras (tf.keras) The NeurIPS-Paper can be found here: http://papers.nips.c

keras-yolo4 请使用更完善的版本: https://github.com/miemie2013/Keras-YOLOv4 Please visit here for more complete model: https://github.com/miemie2013/Keras-YOLOv

Si Adek Python Keras Sistem Informasi Deteksi Benda Berbahaya Keras Python. Version 1.0 Developed by Ananda Rauf Maududi. Developed date: 24 November

Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati

MAE-keras Unofficial keras(tensorflow) implementation of MAE model described in 'Masked Autoencoders Are Scalable Vision Learners'. This work has been

Vision Transformer Unofficial Tensorflow 2.x implementation of the Transformer based Image Classification model proposed by the paper AN IMAGE IS WORT

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

tf-transformers: faster and easier state-of-the-art NLP in TensorFlow 2.0 ****************************************************************************

livelossplot Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! (RECENT CHANGES, EXAMPLES IN COLAB, A

CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation This repository contains the implementat

lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo

This is a tool to help you quickly solve classification problems including: data analysis, training, report results and model explanation.

ML2 Takehome Project Reimplementing the paper: Cascaded Pyramid Network for Multi-Person Pose Estimation Dataset The model uses the COCO dataset which

Note: This utility is really old and is no longer maintained. You should use keras.layers.TextVectorization instead of this. Utilities for pre-process

KerasTuner KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily c

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

Official Website: autokeras.com AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras

AdaBound for Keras Keras port of AdaBound Optimizer for PyTorch, from the paper Adaptive Gradient Methods with Dynamic Bound of Learning Rate. Usage A

Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li

HiddenLayer A lightweight library for neural network graphs and training metrics for PyTorch, Tensorflow, and Keras. HiddenLayer is simple, easy to ex

Neural Style Transfer & Neural Doodles Implementation of Neural Style Transfer from the paper A Neural Algorithm of Artistic Style in Keras 2.0+ INetw

Deep NLP Course at ABBYY Deep learning for NLP crash course at ABBYY. Suggested textbook: Neural Network Methods in Natural Language Processing by Yoa

DeepSchool.io Sign up here for Udemy Course on Machine Learning (Use code DEEPSCHOOL-MARCH to get 85% off course). Goals Make Deep Learning easier (mi

What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection Introduction This repository includes codes and models of "Effect of De

AIR: Aerial Inspection RetinaNet for supporting Land Search and Rescue Missions AIR is a deep learning based object detection solution to automate the

flower-classification-inceptionV3 Flower classification model that classifies flowers in 10 classes. Training and validation are done using a pre-anot

Anime-Face-GAN-Keras A DCGAN to generate anime faces using custom dataset in Keras. Dataset The dataset is created by crawling anime database websites

Keras-GAN-Animeface-Character GAN example for Keras. Cuz MNIST is too small and there should an example on something more realistic. Some results Trai

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

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

Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a

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

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.

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.

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

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

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

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

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation: Work In Progress, Results can't be replicated yet with the m

ENet-keras This is an implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation, ported from ENet-training (lua-t

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

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