1560 Repositories
Python latent-semantic-analysis Libraries
Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt
Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt. This is done by
Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars
Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars
code for Multi-scale Matching Networks for Semantic Correspondence, ICCV
MMNet This repo is the official implementation of ICCV 2021 paper "Multi-scale Matching Networks for Semantic Correspondence.". Pre-requisite conda cr
[ICCV 2021] Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain
Amplitude-Phase Recombination (ICCV'21) Official PyTorch implementation of "Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neur
Functional Data Analysis, or FDA, is the field of Statistics that analyses data that depend on a continuous parameter.
Functional Data Analysis Python package
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications.
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications.
Bot for Telegram data Analysis
Bot Scraper for telegram This bot use an AI to Work powered by BOG Team you must do the following steps to make the bot functional: Install the requir
PIZZA - a task-oriented semantic parsing dataset
The PIZZA dataset continues the exploration of task-oriented parsing by introducing a new dataset for parsing pizza and drink orders, whose semantics cannot be captured by flat slots and intents.
A Python multilingual toolkit for Sentiment Analysis and Social NLP tasks
pysentimiento: A Python toolkit for Sentiment Analysis and Social NLP tasks A Transformer-based library for SocialNLP classification tasks. Currently
ICCV2021 - Mining Contextual Information Beyond Image for Semantic Segmentation
Introduction The official repository for "Mining Contextual Information Beyond Image for Semantic Segmentation". Our full code has been merged into ss
A scalable implementation of WobblyStitcher for 3D microscopy images
WobblyStitcher Introduction A scalable implementation of WobblyStitcher Dependencies $ python -m pip install numpy scikit-image Visualization ImageJ
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019)
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019) Introduction Official implementation of Adaptive Pyramid Context Network
TorchIO is a Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
Django API that scrapes and provides the last news of the city of Carlos Casares by semantic way (RDF format).
"Casares News" API Api that scrapes and provides the last news of the city of Carlos Casares by semantic way (RDF format). Usage Consume the articles
Lite-HRNet: A Lightweight High-Resolution Network
LiteHRNet Benchmark 🔥 🔥 Based on MMsegmentation 🔥 🔥 Cityscapes FCN resize concat config mIoU last mAcc last eval last mIoU best mAcc best eval bes
skimpy is a light weight tool that provides summary statistics about variables in data frames within the console.
skimpy Welcome Welcome to skimpy! skimpy is a light weight tool that provides summary statistics about variables in data frames within the console. Th
pysentimiento: A Python toolkit for Sentiment Analysis and Social NLP tasks
A Python multilingual toolkit for Sentiment Analysis and Social NLP tasks
OpenCVのGrabCut()を利用したセマンティックセグメンテーション向けアノテーションツール(Annotation tool using GrabCut() of OpenCV. It can be used to create datasets for semantic segmentation.)
[Japanese/English] GrabCut-Annotation-Tool GrabCut-Annotation-Tool.mp4 OpenCVのGrabCut()を利用したアノテーションツールです。 セマンティックセグメンテーション向けのデータセット作成にご使用いただけます。 ※Grab
This repository contains the official implementation code of the paper Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis, accepted at EMNLP 2021.
MultiModal-InfoMax This repository contains the official implementation code of the paper Improving Multimodal Fusion with Hierarchical Mutual Informa
Collection of NLP model explanations and accompanying analysis tools
Thermostat is a large collection of NLP model explanations and accompanying analysis tools. Combines explainability methods from the captum library wi
This repository contains various models targetting multimodal representation learning, multimodal fusion for downstream tasks such as multimodal sentiment analysis.
Multimodal Deep Learning 🎆 🎆 🎆 Announcing the multimodal deep learning repository that contains implementation of various deep learning-based model
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks
SSTNet Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks(ICCV2021) by Zhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan, Kui J
TAPEX: Table Pre-training via Learning a Neural SQL Executor
TAPEX: Table Pre-training via Learning a Neural SQL Executor The official repository which contains the code and pre-trained models for our paper TAPE
Semantic Segmentation with Pytorch-Lightning
This is a simple demo for performing semantic segmentation on the Kitti dataset using Pytorch-Lightning and optimizing the neural network by monitoring and comparing runs with Weights & Biases.
Deep Learning for 3D Point Clouds: A Survey (IEEE TPAMI, 2020)
🔥Deep Learning for 3D Point Clouds (IEEE TPAMI, 2020)
PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
PaddlePaddle Vision Transformers State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 🤖 PaddlePaddle Visual Transformers (PaddleViT or
sssegmentation is a general framework for our research on strongly supervised semantic segmentation.
sssegmentation is a general framework for our research on strongly supervised semantic segmentation.
TextDescriptives - A Python library for calculating a large variety of statistics from text
A Python library for calculating a large variety of statistics from text(s) using spaCy v.3 pipeline components and extensions. TextDescriptives can be used to calculate several descriptive statistics, readability metrics, and metrics related to dependency distance.
Official implementation of the MM'21 paper Constrained Graphic Layout Generation via Latent Optimization
[MM'21] Constrained Graphic Layout Generation via Latent Optimization This repository provides the official code for the paper "Constrained Graphic La
Implementation for paper: Self-Regulation for Semantic Segmentation
Self-Regulation for Semantic Segmentation This is the PyTorch implementation for paper Self-Regulation for Semantic Segmentation, ICCV 2021. Citing SR
TorchDistiller - a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.
This project is a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.
PyTorch Code for the paper "VSE++: Improving Visual-Semantic Embeddings with Hard Negatives"
Improving Visual-Semantic Embeddings with Hard Negatives Code for the image-caption retrieval methods from VSE++: Improving Visual-Semantic Embeddings
A PyTorch implementation of the paper "Semantic Image Synthesis via Adversarial Learning" in ICCV 2017
Semantic Image Synthesis via Adversarial Learning This is a PyTorch implementation of the paper Semantic Image Synthesis via Adversarial Learning. Req
Official Python wrapper for the Quantel Finance API
Quantel is a powerful financial data and insights API. It provides easy access to world-class financial information. Quantel goes beyond just financial statements, giving users valuable information like insider transactions, major shareholder transactions, share ownership, peers, and so much more.
Cross-platform MachO/ObjC Static binary analysis tool & library. class-dump + otool + lipo + more
ktool Static Mach-O binary metadata analysis tool / information dumper pip3 install k2l Development is currently taking place on the @python3.10 branc
Public API client for GETTR, a "non-bias [sic] social network," designed for data archival and analysis.
GoGettr GoGettr is an API client for GETTR, a "non-bias [sic] social network." (We will not reward their domain with a hyperlink.) GoGettr is built an
ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation
ST++ This is the official PyTorch implementation of our paper: ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation. Lihe Ya
Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'
Filtration Curves for Graph Representation This repository provides the code from the KDD'21 paper Filtration Curves for Graph Representation. Depende
An official implementation of "Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation" (ICCV 2021) in PyTorch.
Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation This is an official implementation of the paper "Exploiting a Joint
Pytorch Implementation for NeurIPS (oral) paper: Pixel Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation
Pixel-Level Cycle Association This is the Pytorch implementation of our NeurIPS 2020 Oral paper Pixel-Level Cycle Association: A New Perspective for D
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation (ICCV2021)
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation This is a pytorch project for the paper Dynamic Divide-and-Conquer Ad
Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files) and Zeek logs.
Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files) and Zeek logs.
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing da
"Segmenter: Transformer for Semantic Segmentation" reproduced via mmsegmentation
Segmenter-based-on-OpenMMLab "Segmenter: Transformer for Semantic Segmentation, arxiv 2105.05633." reproduced via mmsegmentation. We reproduce Segment
IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020)
This repo is the official implementation of our paper "Instance Adaptive Self-training for Unsupervised Domain Adaptation". The purpose of this repo is to better communicate with you and respond to your questions. This repo is almost the same with Another-Version, and you can also refer to that version.
This is the code for ACL2021 paper A Unified Generative Framework for Aspect-Based Sentiment Analysis
This is the code for ACL2021 paper A Unified Generative Framework for Aspect-Based Sentiment Analysis Install the package in the requirements.txt, the
Official code for "Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021".
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021. Introduction We proposed a novel model training paradi
PyTorch implementation of ShapeConv: Shape-aware Convolutional Layer for RGB-D Indoor Semantic Segmentation.
Shape-aware Convolutional Layer (ShapeConv) PyTorch implementation of ShapeConv: Shape-aware Convolutional Layer for RGB-D Indoor Semantic Segmentatio
Official PyTorch implementation of Segmenter: Transformer for Semantic Segmentation
Segmenter: Transformer for Semantic Segmentation Segmenter: Transformer for Semantic Segmentation by Robin Strudel*, Ricardo Garcia*, Ivan Laptev and
一套完整的微博舆情分析流程代码,包括微博爬虫、LDA主题分析和情感分析。
已经将项目的关键文件上传,包含微博爬虫、LDA主题分析和情感分析三个部分。 1.微博爬虫 实现微博评论爬取和微博用户信息爬取,一天大概十万条。 2.LDA主题分析 实现文档主题抽取,包括数据清洗及分词、主题数的确定(主题一致性和困惑度)和最优主题模型的选择(暴力搜索)。 3.情感分析 实现评论文本的
Yuyu Scanner is a Web Reconnaissance & Web Analysis Scanner to find assets and information about targets.
Yuyu Scanner Yuyu Scanner is a Web Reconnaissance & Web Analysis Scanner to find assets and information about targets. installation ! run as root
A Data Annotation Tool for Semantic Segmentation, Object Detection and Lane Line Detection.(In Development Stage)
Data-Annotation-Tool How to Run this Tool? To run this software, follow the steps: git clone https://github.com/Autonomous-Car-Project/Data-Annotation
Scraping and analysis of leetcode-compensations page.
Leetcode compensations report Scraping and analysis of leetcode-compensations page.
[CVPR 2021] Forecasting the panoptic segmentation of future video frames
Panoptic Segmentation Forecasting Colin Graber, Grace Tsai, Michael Firman, Gabriel Brostow, Alexander Schwing - CVPR 2021 [Link to paper] We propose
Open-World Entity Segmentation
Open-World Entity Segmentation Project Website Lu Qi*, Jason Kuen*, Yi Wang, Jiuxiang Gu, Hengshuang Zhao, Zhe Lin, Philip Torr, Jiaya Jia This projec
Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP
Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP Abstract: We introduce a method that allows to automatically se
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
Update (20 Jan 2020): MODALS on text data is avialable MODALS MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space Table of Conte
Recall Loss for Semantic Segmentation (This repo implements the paper: Recall Loss for Semantic Segmentation)
Recall Loss for Semantic Segmentation (This repo implements the paper: Recall Loss for Semantic Segmentation) Download Synthia dataset The model uses
Implementation of ICCV2021(Oral) paper - VMNet: Voxel-Mesh Network for Geodesic-aware 3D Semantic Segmentation
VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation Created by Zeyu HU Introduction This work is based on our paper VMNet: Voxel-Mes
The code for our paper CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention.
CrossFormer This repository is the code for our paper CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention. Introduction Existin
Minimal PyTorch implementation of Generative Latent Optimization from the paper "Optimizing the Latent Space of Generative Networks"
Minimal PyTorch implementation of Generative Latent Optimization This is a reimplementation of the paper Piotr Bojanowski, Armand Joulin, David Lopez-
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch (https://arxiv.org/abs/1707.09405) This is a Pytorch implementation of cascaded
PyTorch implementation of the wavelet analysis from Torrence & Compo
Continuous Wavelet Transforms in PyTorch This is a PyTorch implementation for the wavelet analysis outlined in Torrence and Compo (BAMS, 1998). The co
LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.
LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.
This is an online course where you can learn and master the skill of low-level performance analysis and tuning.
Performance Ninja Class This is an online course where you can learn to find and fix low-level performance issues, for example CPU cache misses and br
Anomaly detection on SQL data warehouses and databases
With CueObserve, you can run anomaly detection on data in your SQL data warehouses and databases. Getting Started Install via Docker docker run -p 300
Official Implementation of LARGE: Latent-Based Regression through GAN Semantics
LARGE: Latent-Based Regression through GAN Semantics [Project Website] [Google Colab] [Paper] LARGE: Latent-Based Regression through GAN Semantics Yot
A Strong Baseline for Image Semantic Segmentation
A Strong Baseline for Image Semantic Segmentation Introduction This project is an open source semantic segmentation toolbox based on PyTorch. It is ba
Implementation of CVPR 2020 Dual Super-Resolution Learning for Semantic Segmentation
Dual super-resolution learning for semantic segmentation 2021-01-02 Subpixel Update Happy new year! The 2020-12-29 update of SISR with subpixel conv p
Official implementation of "DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation"
DSP Official implementation of "DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation". Accepted by ACM Multimedia 2021. Authors
TLA - Twitter Linguistic Analysis
TLA - Twitter Linguistic Analysis Tool for linguistic analysis of communities TLA is built using PyTorch, Transformers and several other State-of-the-
Greppin' Logs: Leveling Up Log Analysis
This repo contains sample code and example datasets from Jon Stewart and Noah Rubin's presentation at the 2021 SANS DFIR Summit titled Greppin' Logs. The talk was centered around the idea that Forensics is Data Engineering and Data Science, and should be approached as such. Jon and Noah focused on the core (Unix) command line tools useful to anyone analyzing datasets from a terminal, purpose-built tools for handling structured tabular and JSON data, Stroz Friedberg's open source multipattern search tool Lightgrep, and scaling with AWS.
Another pytorch implementation of FCN (Fully Convolutional Networks)
FCN-pytorch-easiest Trying to be the easiest FCN pytorch implementation and just in a get and use fashion Here I use a handbag semantic segmentation f
FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery (TGRS)
FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery by Ailong Ma, Junjue Wang*, Yanfei Zhon
Newsemble is an API that provides easy access to the current news for programmatic analysis
Newsemble is an API that provides easy access to the current news for programmatic analysis. It has been built using Python, BeautifulSoup and MongoDB.
Nvidia Semantic Segmentation monorepo
Paper | YouTube | Cityscapes Score Pytorch implementation of our paper Hierarchical Multi-Scale Attention for Semantic Segmentation. Please refer to t
DRIFT is a tool for Diachronic Analysis of Scientific Literature.
About DRIFT is a tool for Diachronic Analysis of Scientific Literature. The application offers user-friendly and customizable utilities for two modes:
Implementation of "Bidirectional Projection Network for Cross Dimension Scene Understanding" CVPR 2021 (Oral)
Bidirectional Projection Network for Cross Dimension Scene Understanding CVPR 2021 (Oral) [ Project Webpage ] [ arXiv ] [ Video ] Existing segmentatio
Per-Pixel Classification is Not All You Need for Semantic Segmentation
MaskFormer: Per-Pixel Classification is Not All You Need for Semantic Segmentation Bowen Cheng, Alexander G. Schwing, Alexander Kirillov [arXiv] [Proj
PERIN is Permutation-Invariant Semantic Parser developed for MRP 2020
PERIN: Permutation-invariant Semantic Parsing David Samuel & Milan Straka Charles University Faculty of Mathematics and Physics Institute of Formal an
Semantic Segmentation of images using PixelLib with help of Pascalvoc dataset trained with Deeplabv3+ framework.
CARscan- Approach 1 - Segmentation of images by detecting contours. It failed because in images with elements along with cars were also getting detect
Squidpy is a tool for the analysis and visualization of spatial molecular data.
Squidpy is a tool for the analysis and visualization of spatial molecular data. It builds on top of scanpy and anndata, from which it inherits modularity and scalability. It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available.
1st place solution to the Satellite Image Change Detection Challenge hosted by SenseTime
1st place solution to the Satellite Image Change Detection Challenge hosted by SenseTime
STEAL - Learning Semantic Boundaries from Noisy Annotations (CVPR 2019)
STEAL This is the official inference code for: Devil Is in the Edges: Learning Semantic Boundaries from Noisy Annotations David Acuna, Amlan Kar, Sanj
Code and dataset for ACL2018 paper "Exploiting Document Knowledge for Aspect-level Sentiment Classification"
Aspect-level Sentiment Classification Code and dataset for ACL2018 [paper] ‘‘Exploiting Document Knowledge for Aspect-level Sentiment Classification’’
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Introduction This is an implementation of the model used for breast
IJCAI2020 & IJCV 2020 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo
Seg_Uncertainty In this repo, we provide the code for the two papers, i.e., MRNet:Unsupervised Scene Adaptation with Memory Regularization in vivo, IJ
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models Code accompanying CVPR'20 paper of the same title. Paper lin
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
🛠 All-in-one web-based IDE specialized for machine learning and data science.
All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu
Manage your exceptions in Python like a PRO
A linter to manage all your python exceptions and try/except blocks (limited only for those who like dinosaurs).
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
Semantic Scholar's Author Disambiguation Algorithm & Evaluation Suite
S2AND This repository provides access to the S2AND dataset and S2AND reference model described in the paper S2AND: A Benchmark and Evaluation System f
This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re
Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion (CVPR 2021)
Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion (CVPR 2021) This repository is for BAAF-Net introduce
Codes for TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization.
TS-CAM: Token Semantic Coupled Attention Map for Weakly SupervisedObject Localization This is the official implementaion of paper TS-CAM: Token Semant
A linter to manage all your python exceptions and try/except blocks (limited only for those who like dinosaurs).
Manage your exceptions in Python like a PRO Currently in BETA. Inspired by this blog post. I shared the building process of this tool here. “For those
joint detection and semantic segmentation, based on ultralytics/yolov5,
Multi YOLO V5——Detection and Semantic Segmentation Overeview This is my undergraduate graduation project which based on ultralytics YOLO V5 tag v5.0.