1560 Repositories
Python latent-semantic-analysis Libraries
Using fully convolutional networks for semantic segmentation with caffe for the cityscapes dataset
Using fully convolutional networks for semantic segmentation (Shelhamer et al.) with caffe for the cityscapes dataset How to get started Download the
Fully convolutional networks for semantic segmentation
FCN-semantic-segmentation Simple end-to-end semantic segmentation using fully convolutional networks [1]. Takes a pretrained 34-layer ResNet [2], remo
Pytorch for Segmentation
Pytorch for Semantic Segmentation This repo has been deprecated currently and I will not maintain it. Meanwhile, I strongly recommend you can refer to
Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as
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
FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation
FCN_via_Keras FCN FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This
Keras-tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation(Unfinished)
Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas
Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.
Fully Convolutional Networks for Semantic Segmentation This is the reference implementation of the models and code for the fully convolutional network
PyTorch implementation of DeepLab v2 on COCO-Stuff / PASCAL VOC
DeepLab with PyTorch This is an unofficial PyTorch implementation of DeepLab v2 [1] with a ResNet-101 backbone. COCO-Stuff dataset [2] and PASCAL VOC
PyTorch Implementations for DeeplabV3 and PSPNet
Pytorch-segmentation-toolbox DOC Pytorch code for semantic segmentation. This is a minimal code to run PSPnet and Deeplabv3 on Cityscape dataset. Shor
Train DeepLab for Semantic Image Segmentation
Train DeepLab for Semantic Image Segmentation Martin Kersner, [email protected] This repository contains scripts for training DeepLab for Semantic I
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
DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe.
DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute
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
Implementation of SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling
Caffe SegNet This is a modified version of Caffe which supports the SegNet architecture As described in SegNet: A Deep Convolutional Encoder-Decoder A
Semantic segmentation models, datasets and losses implemented in PyTorch.
Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm
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
A combination of autoregressors and autoencoders using XLNet for sentiment analysis
A combination of autoregressors and autoencoders using XLNet for sentiment analysis Abstract In this paper sentiment analysis has been performed in or
Keyword-BERT: Keyword-Attentive Deep Semantic Matching
project discription An implementation of the Keyword-BERT model mentioned in my paper Keyword-Attentive Deep Semantic Matching (Plz cite this github r
Sentiment analysis on streaming twitter data using Spark Structured Streaming & Python
Sentiment analysis on streaming twitter data using Spark Structured Streaming & Python This project is a good starting point for those who have little
Important dataframe statistics with a single command
quick_eda Receiving dataframe statistics with one command Project description A python package for Data Scientists, Students, ML Engineers and anyone
Data Scientist in Simple Stock Analysis of PT Bukalapak.com Tbk for Long Term Investment
Data Scientist in Simple Stock Analysis of PT Bukalapak.com Tbk for Long Term Investment Brief explanation of PT Bukalapak.com Tbk Bukalapak was found
Numerical Analysis toolkit centred around PDEs, for demonstration and understanding purposes not production
Numerics Numerical Analysis toolkit centred around PDEs, for demonstration and understanding purposes not production Use procedure: Initialise a new i
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
strava-offline is a tool to keep a local mirror of Strava activities for further analysis/processing:
strava-offline Overview strava-offline is a tool to keep a local mirror of Strava activities for further analysis/processing: synchronizes metadata ab
nbsafety adds a layer of protection to computational notebooks by solving the stale dependency problem when executing cells out-of-order
nbsafety adds a layer of protection to computational notebooks by solving the stale dependency problem when executing cells out-of-order
Facial Image Inpainting with Semantic Control
Facial Image Inpainting with Semantic Control In this repo, we provide a model for the controllable facial image inpainting task. This model enables u
Analysis scripts for QG equations
qg-edgeofchaos Analysis scripts for QG equations FIle/Folder Structure eigensolvers.py - Spectral and finite-difference solvers for Rossby wave eigenf
Log processor for nginx or apache that extracts user and user sessions and calculates other types of useful data for bot detection or traffic analysis
Log processor for nginx or apache that extracts user and user sessions and calculates other types of useful data for bot detection or traffic analysis
A Python adaption of Augur to prioritize cell types in perturbation analysis.
A Python adaption of Augur to prioritize cell types in perturbation analysis.
Powerful, efficient particle trajectory analysis in scientific Python.
freud Overview The freud Python library provides a simple, flexible, powerful set of tools for analyzing trajectories obtained from molecular dynamics
Pymwp is a tool for automatically performing static analysis on programs written in C
pymwp: MWP analysis in Python pymwp is a tool for automatically performing static analysis on programs written in C, inspired by "A Flow Calculus of m
Office365 (Microsoft365) audit log analysis tool
Office365 (Microsoft365) audit log analysis tool The header describes it all WHY?? The first line of code was written long time before other colleague
This is an example of how to automate Ridit Analysis for a dataset with large amount of questions and many item attributes
This is an example of how to automate Ridit Analysis for a dataset with large amount of questions and many item attributes
Code & Experiments for "LILA: Language-Informed Latent Actions" to be presented at the Conference on Robot Learning (CoRL) 2021.
LILA LILA: Language-Informed Latent Actions Code and Experiments for Language-Informed Latent Actions (LILA), for using natural language to guide assi
Source code, data, and evaluation details for “Cross-Lingual Citations in English Papers: A Large-Scale Analysis of Prevalence, Formation, and Ramifications”
Analysis of cross-lingual citations in English papers Contents initial_analysis Source code, data, and evaluation details as published at ICADL2020 ci
A package for music online and offline rhythmic information analysis including music Beat, downbeat, tempo and meter tracking.
BeatNet A package for music online and offline rhythmic information analysis including music Beat, downbeat, tempo and meter tracking. This repository
Efficient electromagnetic solver based on rigorous coupled-wave analysis for 3D and 2D multi-layered structures with in-plane periodicity
Efficient electromagnetic solver based on rigorous coupled-wave analysis for 3D and 2D multi-layered structures with in-plane periodicity, such as gratings, photonic-crystal slabs, metasurfaces, surface-emitting lasers, nano-antennas, and more.
Obsei is a low code AI powered automation tool.
Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more .
4CAT: Capture and Analysis Toolkit
4CAT: Capture and Analysis Toolkit 4CAT is a research tool that can be used to analyse and process data from online social platforms. Its goal is to m
Robocop is a tool that performs static code analysis of Robot Framework code.
Robocop Introduction Documentation Values Requirements Installation Usage Example Robotidy FAQ Watch our talk from RoboCon 2021 about Robocop and Robo
The official PyTorch code implementation of "Human Trajectory Prediction via Counterfactual Analysis" in ICCV 2021.
Human Trajectory Prediction via Counterfactual Analysis (CausalHTP) The official PyTorch code implementation of "Human Trajectory Prediction via Count
Multi-View Radar Semantic Segmentation
Multi-View Radar Semantic Segmentation Paper Multi-View Radar Semantic Segmentation, ICCV 2021. Arthur Ouaknine, Alasdair Newson, Patrick Pérez, Flore
Perception-aware multi-sensor fusion for 3D LiDAR semantic segmentation (ICCV 2021)
Perception-Aware Multi-Sensor Fusion for 3D LiDAR Semantic Segmentation (ICCV 2021) [中文|EN] 概述 本工作主要探索一种高效的多传感器(激光雷达和摄像头)融合点云语义分割方法。现有的多传感器融合方法主要将点云投影
This is the code related to "Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation" (ICCV 2021).
Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation This is the code relat
[ICCV 2021 Oral] Mining Latent Classes for Few-shot Segmentation
Mining Latent Classes for Few-shot Segmentation Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao. This codebase contains baseline of our paper Mini
(ICCV 2021 Oral) Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation.
DARS Code release for the paper "Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation", ICCV 2021
Multi-Anchor Active Domain Adaptation for Semantic Segmentation (ICCV 2021 Oral)
Multi-Anchor Active Domain Adaptation for Semantic Segmentation Munan Ning*, Donghuan Lu*, Dong Wei†, Cheng Bian, Chenglang Yuan, Shuang Yu, Kai Ma, Y
Code for the ICCV2021 paper "Personalized Image Semantic Segmentation"
PSS: Personalized Image Semantic Segmentation Paper PSS: Personalized Image Semantic Segmentation Yu Zhang, Chang-Bin Zhang, Peng-Tao Jiang, Ming-Ming
[ICCV 2021] FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
FaPN: Feature-aligned Pyramid Network for Dense Image Prediction [arXiv] [Project Page] @inproceedings{ huang2021fapn, title={{FaPN}: Feature-alig
ICCV2021 Papers with Code
ICCV2021 Papers with Code
Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data based on Pytorch Framework
VFedPCA+VFedAKPCA This is the official source code for the Paper: Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-
A flexible ML framework built to simplify medical image reconstruction and analysis experimentation.
meddlr Getting Started Meddlr is a config-driven ML framework built to simplify medical image reconstruction and analysis problems. Installation To av
Exploratory analysis and data visualization of aircraft accidents and incidents in Brazil.
Exploring aircraft accidents in Brazil Occurrencies with aircraft in Brazil are investigated by the Center for Investigation and Prevention of Aircraf
Unsub is a collection analysis tool that assists libraries in analyzing their journal subscriptions.
About Unsub is a collection analysis tool that assists libraries in analyzing their journal subscriptions. The tool provides rich data and a summary g
cLoops2: full stack analysis tool for chromatin interactions
cLoops2: full stack analysis tool for chromatin interactions Introduction cLoops2 is an extension of our previous work, cLoops. From loop-calling base
Tool for automatically reordering python imports. Similar to isort but uses static analysis more.
reorder_python_imports Tool for automatically reordering python imports. Similar to isort but uses static analysis more. Installation pip install reor
Multifunctional Analysis of Regions through Input-Output
MARIO Multifunctional Analysis of Regions through Input-Output. (Documents) What is it MARIO is a python package for handling input-output tables and
LSTM Neural Networks for Spectroscopic Studies of Type Ia Supernovae
Package Description The difficulties in acquiring spectroscopic data have been a major challenge for supernova surveys. snlstm is developed to provide
A real data analysis and modeling project - restaurant inspections
A real data analysis and modeling project - restaurant inspections Jafar Pourbemany 9/27/2021 This project represents data analysis and modeling of re
Python implementation of Principal Component Analysis
Principal Component Analysis Principal Component Analysis (PCA) is a dimension-reduction algorithm. The idea is to use the singular value decompositio
Exploratory data analysis
Exploratory data analysis An Exploratory data analysis APP TAPIWA CHAMBOKO 🚀 About Me I'm a full stack developer experienced in deploying artificial
edaSQL is a library to link SQL to Exploratory Data Analysis and further more in the Data Engineering.
edaSQL is a python library to bridge the SQL with Exploratory Data Analysis where you can connect to the Database and insert the queries. The query results can be passed to the EDA tool which can give greater insights to the user.
Stock Analysis dashboard Using Streamlit and Python
StDashApp Stock Analysis Dashboard Using Streamlit and Python If you found the content useful and want to support my work, you can buy me a coffee! Th
Perform sentiment analysis and keyword extraction on Craigslist listings
craiglist-helper synopsis Perform sentiment analysis and keyword extraction on Craigslist listings Background I love Craigslist. I've found most of my
Python-based tools for document analysis and OCR
ocropy OCRopus is a collection of document analysis programs, not a turn-key OCR system. In order to apply it to your documents, you may need to do so
This tool parses log data and allows to define analysis pipelines for anomaly detection.
logdata-anomaly-miner This tool parses log data and allows to define analysis pipelines for anomaly detection. It was designed to run the analysis wit
A collection of tools for biomedical research assay analysis in Python.
waltlabtools A collection of tools for biomedical research assay analysis in Python. Key Features Analysis for assays such as digital ELISA, including
A pytorch-based real-time segmentation model for autonomous driving
CFPNet: Channel-Wise Feature Pyramid for Real-Time Semantic Segmentation This project contains the Pytorch implementation for the proposed CFPNet: pap
For the paper entitled ''A Case Study and Qualitative Analysis of Simple Cross-Lingual Opinion Mining''
Summary This is the source code for the paper "A Case Study and Qualitative Analysis of Simple Cross-Lingual Opinion Mining", which was accepted as fu
Caboto, the Kubernetes semantic analysis tool
Caboto Caboto, the Kubernetes semantic analysis toolkit. It contains a lightweight Python library for semantic analysis of plain Kubernetes manifests
This repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here
uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain
A simple pytorch pipeline for semantic segmentation.
SegmentationPipeline -- Pytorch A simple pytorch pipeline for semantic segmentation. Requirements : torch=1.9.0 tqdm albumentations=1.0.3 opencv-pyt
I created My own Virtual Artificial Intelligence named genesis, He can assist with my Tasks and also perform some analysis,,
Virtual-Artificial-Intelligence-genesis- I created My own Virtual Artificial Intelligence named genesis, He can assist with my Tasks and also perform
A python module for scientific analysis of 3D objects based on VTK and Numpy
A lightweight and powerful python module for scientific analysis and visualization of 3d objects.
FinEAS: Financial Embedding Analysis of Sentiment 📈
FinEAS: Financial Embedding Analysis of Sentiment 📈 (SentenceBERT for Financial News Sentiment Regression) This repository contains the code for gene
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces
This repository contains source code for the paper Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces a
This repository contains the source code of an efficient 1D probabilistic model for music time analysis proposed in ICASSP2022 venue.
Jump Reward Inference for 1D Music Rhythmic State Spaces An implementation of the probablistic jump reward inference model for music rhythmic informat
PyTorch implementation for "Mining Latent Structures with Contrastive Modality Fusion for Multimedia Recommendation"
MIRCO PyTorch implementation for paper: Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation Dependencies Python 3.
Analysis code and Latex source of the manuscript describing the conditional permutation test of confounding bias in predictive modelling.
Git repositoty of the manuscript entitled Statistical quantification of confounding bias in predictive modelling by Tamas Spisak The manuscript descri
Survival analysis (SA) is a well-known statistical technique for the study of temporal events.
DAGSurv Survival analysis (SA) is a well-known statistical technique for the study of temporal events. In SA, time-to-an-event data is modeled using a
K-FACE Analysis Project on Pytorch
Installation Setup with Conda # create a new environment conda create --name insightKface python=3.7 # or over conda activate insightKface #install t
Repository for the semantic WMI loss
Installation: pip install -e . Installing DL2: First clone DL2 in a separate directory and install it using the following commands: git clone https:/
[NeurIPS2021] Code Release of K-Net: Towards Unified Image Segmentation
K-Net: Towards Unified Image Segmentation Introduction This is an official release of the paper K-Net:Towards Unified Image Segmentation. K-Net will a
This is an auto-ML tool specialized in detecting of outliers
Auto-ML tool specialized in detecting of outliers Description This tool will allows you, with a Dash visualization, to compare 10 models of machine le
Code for "SRHEN: Stepwise-Refining Homography Estimation Network via Parsing Geometric Correspondences in Deep Latent Space"
SRHEN This is a better and simpler implementation for "SRHEN: Stepwise-Refining Homography Estimation Network via Parsing Geometric Correspondences in
Malware Analysis Neural Network project.
MalanaNeuralNetwork Description Malware Analysis Neural Network project. Table of Contents Getting Started Requirements Installation Clone Set-Up VENV
Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*
Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*. The algorithm was extremely optimal running in ~15s to ~30s for search spaces as big as 10000000 nodes where a set of 18 actions could be performed at each node in the 3D Maze.
this repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here
uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain
Data cleaning tools for Business analysis
Datacleaning datacleaning tools for Business analysis This program is made for Vicky's work. You can use it, too. 数据清洗 该数据清洗工具是为了商业分析 这个程序是为了Vicky的工作而
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
deeptime Releases: Installation via conda recommended. conda install -c conda-forge deeptime pip install deeptime Documentation: deeptime-ml.github.io
ELFXtract is an automated analysis tool used for enumerating ELF binaries
ELFXtract ELFXtract is an automated analysis tool used for enumerating ELF binaries Powered by Radare2 and r2ghidra This is specially developed for PW
py-image-dedup is a tool to sort out or remove duplicates within a photo library
py-image-dedup is a tool to sort out or remove duplicates within a photo library. Unlike most other solutions, py-image-dedup intentionally uses an approximate image comparison to also detect duplicates of images that slightly differ in resolution, color or other minor details.
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Requirements This repository needs mmsegmentation Training To train
Pseudo-mask Matters in Weakly-supervised Semantic Segmentation
Pseudo-mask Matters in Weakly-supervised Semantic Segmentation By Yi Li, Zhanghui Kuang, Liyang Liu, Yimin Chen, Wayne Zhang SenseTime, Tsinghua Unive
MsfMania is a command line tool developed in Python that is designed to bypass antivirus software on Windows and Linux/Mac in the future
MsfMania MsfMania is a command line tool developed in Python that is designed to bypass antivirus software on Windows and Linux/Mac in the future. Sum
A CLI Application to detect plagiarism in Source Code Files.
Plag Description A CLI Application to detect plagiarism in Source Code Files. Features Compare source code files for plagiarism. Extract code features
A simple tool to extract python code from a Jupyter notebook, and then run pylint on it for static analysis.
Jupyter Pylinter A simple tool to extract python code from a Jupyter notebook, and then run pylint on it for static analysis. If you find this tool us