4011 Repositories
Python deep-neural-networks Libraries
A small C++ implementation of LSTM networks, focused on OCR.
clstm CLSTM is an implementation of the LSTM recurrent neural network model in C++, using the Eigen library for numerical computations. Status and sco
This is the implementation of the paper "Gated Recurrent Convolution Neural Network for OCR"
Gated Recurrent Convolution Neural Network for OCR This project is an implementation of the GRCNN for OCR. For details, please refer to the paper: htt
Tensorflow-based CNN+LSTM trained with CTC-loss for OCR
Overview This collection demonstrates how to construct and train a deep, bidirectional stacked LSTM using CNN features as input with CTC loss to perfo
Textboxes : Image Text Detection Model : python package (tensorflow)
shinTB Abstract A python package for use Textboxes : Image Text Detection Model implemented by tensorflow, cv2 Textboxes Paper Review in Korean (My Bl
TextBoxes: A Fast Text Detector with a Single Deep Neural Network https://github.com/MhLiao/TextBoxes 基于SSD改进的文本检测算法,textBoxes_note记录了之前整理的笔记。
TextBoxes: A Fast Text Detector with a Single Deep Neural Network Introduction This paper presents an end-to-end trainable fast scene text detector, n
Packaged, Pytorch-based, easy to use, cross-platform version of the CRAFT text detector
CRAFT: Character-Region Awareness For Text detection Packaged, Pytorch-based, easy to use, cross-platform version of the CRAFT text detector | Paper |
Tool which allow you to detect and translate text.
Text detection and recognition This repository contains tool which allow to detect region with text and translate it one by one. Description Two pretr
AdvancedEAST is an algorithm used for Scene image text detect, which is primarily based on EAST, and the significant improvement was also made, which make long text predictions more accurate.https://github.com/huoyijie/raspberrypi-car
AdvancedEAST AdvancedEAST is an algorithm used for Scene image text detect, which is primarily based on EAST:An Efficient and Accurate Scene Text Dete
A tensorflow implementation of EAST text detector
EAST: An Efficient and Accurate Scene Text Detector Introduction This is a tensorflow re-implementation of EAST: An Efficient and Accurate Scene Text
keras复现场景文本检测网络CPTN: 《Detecting Text in Natural Image with Connectionist Text Proposal Network》;欢迎试用,关注,并反馈问题...
keras-ctpn [TOC] 说明 预测 训练 例子 4.1 ICDAR2015 4.1.1 带侧边细化 4.1.2 不带带侧边细化 4.1.3 做数据增广-水平翻转 4.2 ICDAR2017 4.3 其它数据集 toDoList 总结 说明 本工程是keras实现的CPTN: Detecti
TensorFlow Implementation of FOTS, Fast Oriented Text Spotting with a Unified Network.
FOTS: Fast Oriented Text Spotting with a Unified Network I am still working on this repo. updates and detailed instructions are coming soon! Table of
TextField: Learning A Deep Direction Field for Irregular Scene Text Detection (TIP 2019)
TextField: Learning A Deep Direction Field for Irregular Scene Text Detection Introduction The code and trained models of: TextField: Learning A Deep
This repository provides train&test code, dataset, det.&rec. annotation, evaluation script, annotation tool, and ranking.
SCUT-CTW1500 Datasets We have updated annotations for both train and test set. Train: 1000 images [images][annos] Additional point annotation for each
Code for the paper STN-OCR: A single Neural Network for Text Detection and Text Recognition
STN-OCR: A single Neural Network for Text Detection and Text Recognition This repository contains the code for the paper: STN-OCR: A single Neural Net
Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text Recognition"
SEE: Towards Semi-Supervised End-to-End Scene Text Recognition Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text
This is a c++ project deploying a deep scene text reading pipeline with tensorflow. It reads text from natural scene images. It uses frozen tensorflow graphs. The detector detect scene text locations. The recognizer reads word from each detected bounding box.
DeepSceneTextReader This is a c++ project deploying a deep scene text reading pipeline. It reads text from natural scene images. Prerequsites The proj
This project modify tensorflow object detection api code to predict oriented bounding boxes. It can be used for scene text detection.
This is an oriented object detector based on tensorflow object detection API. Most of the code is not changed except for those related to the need of
caffe re-implementation of R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection
R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection Abstract This is a caffe re-implementation of R2CNN: Rotational Region CNN fo
The code of "Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes"
Mask TextSpotter A Pytorch implementation of Mask TextSpotter along with its extension can be find here Introduction This is the official implementati
Pytorch implementation of PSEnet with Pyramid Attention Network as feature extractor
Scene Text-Spotting based on PSEnet+CRNN Pytorch implementation of an end to end Text-Spotter with a PSEnet text detector and CRNN text recognizer. We
CUTIE (TensorFlow implementation of Convolutional Universal Text Information Extractor)
CUTIE TensorFlow implementation of the paper "CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractor." Xiaohu
Table recognition inside douments using neural networks
TableTrainNet A simple project for training and testing table recognition in documents. This project was developed to make a neural network which reco
Unofficial implementation of "TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images"
TableNet Unofficial implementation of ICDAR 2019 paper : TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from
Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.
Handwritten Line Text Recognition using Deep Learning with Tensorflow Description Use Convolutional Recurrent Neural Network to recognize the Handwrit
Handwritten_Text_Recognition
Deep Learning framework for Line-level Handwritten Text Recognition Short presentation of our project Introduction Installation 2.a Install conda envi
Handwritten Text Recognition (HTR) system implemented with TensorFlow.
Handwritten Text Recognition with TensorFlow Update 2021: more robust model, faster dataloader, word beam search decoder also available for Windows Up
Handwritten Number Recognition using CNN and Character Segmentation
Handwritten-Number-Recognition-With-Image-Segmentation Info About this repository This Repository is aimed at reading handwritten images of numbers an
Handwriting Recognition System based on a deep Convolutional Recurrent Neural Network architecture
Handwriting Recognition System This repository is the Tensorflow implementation of the Handwriting Recognition System described in Handwriting Recogni
This repository lets you train neural networks models for performing end-to-end full-page handwriting recognition using the Apache MXNet deep learning frameworks on the IAM Dataset.
Handwritten Text Recognition (OCR) with MXNet Gluon These notebooks have been created by Jonathan Chung, as part of his internship as Applied Scientis
a deep learning model for page layout analysis / segmentation.
OCR Segmentation a deep learning model for page layout analysis / segmentation. dependencies tensorflow1.8 python3 dataset: uw3-framed-lines-degraded-
ocroseg - This is a deep learning model for page layout analysis / segmentation.
ocroseg This is a deep learning model for page layout analysis / segmentation. There are many different ways in which you can train and run it, but by
Page to PAGE Layout Analysis Tool
P2PaLA Page to PAGE Layout Analysis (P2PaLA) is a toolkit for Document Layout Analysis based on Neural Networks. 💥 Try our new DEMO for online baseli
Deep learning based page layout analysis
Deep Learning Based Page Layout Analyze This is a Python implementaion of page layout analyze tool. The goal of page layout analyze is to segment page
Deep Learning Chinese Word Segment
引用 本项目模型BiLSTM+CRF参考论文:http://www.aclweb.org/anthology/N16-1030 ,IDCNN+CRF参考论文:https://arxiv.org/abs/1702.02098 构建 安装好bazel代码构建工具,安装好tensorflow(目前本项目需
ARU-Net - Deep Learning Chinese Word Segment
ARU-Net: A Neural Pixel Labeler for Layout Analysis of Historical Documents Contents Introduction Installation Demo Training Introduction This is the
Code for the paper "DewarpNet: Single-Image Document Unwarping With Stacked 3D and 2D Regression Networks" (ICCV '19)
DewarpNet This repository contains the codes for DewarpNet training. Recent Updates [May, 2020] Added evaluation images and an important note about Ma
Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561
Meta-Solver for Neural Ordinary Differential Equations Towards robust neural ODEs using parametrized solvers. Main idea Each Runge-Kutta (RK) solver w
Implementation of "Deep Implicit Templates for 3D Shape Representation"
Deep Implicit Templates for 3D Shape Representation Zerong Zheng, Tao Yu, Qionghai Dai, Yebin Liu. arXiv 2020. This repository is an implementation fo
TensorFlow code for the neural network presented in the paper: "Structural Language Models of Code" (ICML'2020)
SLM: Structural Language Models of Code This is an official implementation of the model described in: "Structural Language Models of Code" [PDF] To ap
Code and model benchmarks for "SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology"
NeurIPS 2020 SEVIR Code for paper: SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology Requirement
[ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks, ICLR 2021 (Spotlight) Demo | Paper [NEW!] Time to play with our interac
Code for "Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks", CVPR 2021
Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks This repository contains the code that accompanies our CVPR 20
中文语音识别系列,读者可以借助它快速训练属于自己的中文语音识别模型,或直接使用预训练模型测试效果。
MASR中文语音识别(pytorch版) 开箱即用 自行训练 使用与训练分离(增量训练) 识别率高 说明:因为每个人电脑机器不同,而且有些安装包安装起来比较麻烦,强烈建议直接用我编译好的docker环境跑 目前docker基础环境为ubuntu-cuda10.1-cudnn7-pytorch1.6.
CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"
Diverse Structure Inpainting ArXiv | Papar | Supplementary Material | BibTex This repository is for the CVPR 2021 paper, "Generating Diverse Structure
Official PyTorch implementation of Spatial Dependency Networks.
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling Đorđe Miladinović Aleksandar Stanić Stefan Bauer Jürgen Schmid
[CIKM 2019] Code and dataset for "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction"
FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti
DECAF: Deep Extreme Classification with Label Features
DECAF DECAF: Deep Extreme Classification with Label Features @InProceedings{Mittal21, author = "Mittal, A. and Dahiya, K. and Agrawal, S. and Sain
A spherical CNN for weather forecasting
DeepSphere-Weather - Deep Learning on the sphere for weather/climate applications. The code in this repository provides a scalable and flexible framew
A deep learning-based translation library built on Huggingface transformers
DL Translate A deep learning-based translation library built on Huggingface transformers and Facebook's mBART-Large 💻 GitHub Repository 📚 Documentat
Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)
Training GANs with Stronger Augmentations via Contrastive Discriminator (ICLR 2021) This repository contains the code for reproducing the paper: Train
Deep Dual Consecutive Network for Human Pose Estimation (CVPR2021)
Deep Dual Consecutive Network for Human Pose Estimation (CVPR2021) Introduction This is the official code of Deep Dual Consecutive Network for Human P
code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling This repository contains PyTorch evaluation code, training code and pretrain
[CVPR 2021] Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion
[CVPR 2021] Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion
Implicit Graph Neural Networks
Implicit Graph Neural Networks This repository is the official PyTorch implementation of "Implicit Graph Neural Networks". Fangda Gu*, Heng Chang*, We
[ICLR 2021] HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark
HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark Accepted as a spotlight paper at ICLR 2021. Table of content File structure Prerequi
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
A curated list of neural network pruning resources.
A curated list of neural network pruning and related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awesome-deep-learning-papers and Awesome-NAS.
Implementation of "Slow-Fast Auditory Streams for Audio Recognition, ICASSP, 2021" in PyTorch
Auditory Slow-Fast This repository implements the model proposed in the paper: Evangelos Kazakos, Arsha Nagrani, Andrew Zisserman, Dima Damen, Slow-Fa
Learning Intents behind Interactions with Knowledge Graph for Recommendation, WWW2021
Learning Intents behind Interactions with Knowledge Graph for Recommendation This is our PyTorch implementation for the paper: Xiang Wang, Tinglin Hua
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.
Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations
TorchMetrics is a collection of 25+ PyTorch metrics implementations and an easy-to-use API to create custom metrics.
Machine learning metrics for distributed, scalable PyTorch applications.
FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction
FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction. It uses a customized encoder decoder architecture with spatio-temporal convolutions and channel gating to capture and interpolate complex motion trajectories between frames to generate realistic high frame rate videos. This repository contains original source code for the paper accepted to CVPR 2021.
Dogs classification with Deep Metric Learning using some popular losses
Tsinghua Dogs classification with Deep Metric Learning 1. Introduction Tsinghua Dogs dataset Tsinghua Dogs is a fine-grained classification dataset fo
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
Infinitely Deep Bayesian Neural Networks with SDEs This library contains JAX and Pytorch implementations of neural ODEs and Bayesian layers for stocha
This project is the official implementation of our accepted ICLR 2021 paper BiPointNet: Binary Neural Network for Point Clouds.
BiPointNet: Binary Neural Network for Point Clouds Created by Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Li
Official implementation of Self-supervised Graph Attention Networks (SuperGAT), ICLR 2021.
SuperGAT Official implementation of Self-supervised Graph Attention Networks (SuperGAT). This model is presented at How to Find Your Friendly Neighbor
Very deep VAEs in JAX/Flax
Very Deep VAEs in JAX/Flax Implementation of the experiments in the paper Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on I
Open world survival environment for reinforcement learning
Crafter Open world survival environment for reinforcement learning. Highlights Crafter is a procedurally generated 2D world, where the agent finds foo
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)
Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
involution Official implementation of a neural operator as described in Involution: Inverting the Inherence of Convolution for Visual Recognition (CVP
[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
Anycost GAN video | paper | website Anycost GANs for Interactive Image Synthesis and Editing Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zh
Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch
Perceiver - Pytorch Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch Install $ pip install perceiver-pytorch Usage
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain
(CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
ClassSR (CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic Paper Authors: Xiangtao Kong, Hengyuan
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage
Open standard for machine learning interoperability
Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis
Create HTML profiling reports from pandas DataFrame objects
Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great
Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about library: https://www.mdpi.com/2078-2489/11/2/125
Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc
Image augmentation library in Python for machine learning.
Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independe
Image augmentation for machine learning experiments.
imgaug This python library helps you with augmenting images for your machine learning projects. It converts a set of input images into a new, much lar
Open Source Computer Vision Library
OpenCV: Open Source Computer Vision Library Resources Homepage: https://opencv.org Courses: https://opencv.org/courses Docs: https://docs.opencv.org/m
Hyperparameter Optimization for TensorFlow, Keras and PyTorch
Hyperparameter Optimization for Keras Talos • Key Features • Examples • Install • Support • Docs • Issues • License • Download Talos radically changes
Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
PyVarInf PyVarInf provides facilities to easily train your PyTorch neural network models using variational inference. Bayesian Deep Learning with Vari
A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation
Aboleth A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation [1] with stochastic gradient variational Bayes
Bayesian dessert for Lasagne
Gelato Bayesian dessert for Lasagne Recent results in Bayesian statistics for constructing robust neural networks have proved that it is one of the be
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
InferPy: Deep Probabilistic Modeling Made Easy InferPy is a high-level API for probabilistic modeling written in Python and capable of running on top
Deep universal probabilistic programming with Python and PyTorch
Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab
ChainerRL is a deep reinforcement learning library built on top of Chainer.
ChainerRL ChainerRL is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Ch
Deep Reinforcement Learning for Keras.
Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml
Tensorforce: a TensorFlow library for applied reinforcement learning
Tensorforce: a TensorFlow library for applied reinforcement learning Introduction Tensorforce is an open-source deep reinforcement learning framework,
Create HTML profiling reports from pandas DataFrame objects
Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens
A collection of infrastructure and tools for research in neural network interpretability.
Lucid Lucid is a collection of infrastructure and tools for research in neural network interpretability. We're not currently supporting tensorflow 2!
Interpretability and explainability of data and machine learning models
AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase
Python Library for Model Interpretation/Explanations
Skater Skater is a unified framework to enable Model Interpretation for all forms of model to help one build an Interpretable machine learning system
A game theoretic approach to explain the output of any machine learning model.
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.
Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The