1846 Repositories
Python customer-segmentation-analysis Libraries
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:
Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data
LiDAR-MOS: Moving Object Segmentation in 3D LiDAR Data This repo contains the code for our paper: Moving Object Segmentation in 3D LiDAR Data: A Learn
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
PyTorch implementation of paper: HPNet: Deep Primitive Segmentation Using Hybrid Representations.
HPNet This repository contains the PyTorch implementation of paper: HPNet: Deep Primitive Segmentation Using Hybrid Representations. Installation The
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
A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography
A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography
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
U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI
U-Net for brain segmentation U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI based on a deep learning segmentation alg
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
Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).
Adaptive Segmentation Mask Attack This repository contains the implementation of the Adaptive Segmentation Mask Attack (ASMA), a targeted adversarial
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
Kaggle | 9th place single model solution for TGS Salt Identification Challenge
UNet for segmenting salt deposits from seismic images with PyTorch. General We, tugstugi and xuyuan, have participated in the Kaggle competition TGS S
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
Official PyTorch implementation of UACANet: Uncertainty Aware Context Attention for Polyp Segmentation
UACANet: Uncertainty Aware Context Attention for Polyp Segmentation Official pytorch implementation of UACANet: Uncertainty Aware Context Attention fo
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.
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
2021-MICCAI-Progressively Normalized Self-Attention Network for Video Polyp Segmentation
2021-MICCAI-Progressively Normalized Self-Attention Network for Video Polyp Segmentation Authors: Ge-Peng Ji*, Yu-Cheng Chou*, Deng-Ping Fan, Geng Che
Code for 'Self-Guided and Cross-Guided Learning for Few-shot segmentation. (CVPR' 2021)'
SCL Introduction Code for 'Self-Guided and Cross-Guided Learning for Few-shot segmentation. (CVPR' 2021)' We evaluated our approach using two baseline
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
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.
Pose Detection and Machine Learning for real-time body posture analysis during exercise to provide audiovisual feedback on improvement of form.
Posture: Pose Tracking and Machine Learning for prescribing corrective suggestions to improve posture and form while exercising. This repository conta
Visual Python is a GUI-based Python code generator, developed on the Jupyter Notebook environment as an extension.
Visual Python is a GUI-based Python code generator, developed on the Jupyter Notebook environment as an extension.
Code implementation of Data Efficient Stagewise Knowledge Distillation paper.
Data Efficient Stagewise Knowledge Distillation Table of Contents Data Efficient Stagewise Knowledge Distillation Table of Contents Requirements Image
clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
README clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation CVPR 2021 Authors: Suprosanna Shit and Johannes C. Paetzo
Point Cloud Denoising input segmentation output raw point-cloud valid/clear fog rain de-noised Abstract Lidar sensors are frequently used in environme
Point Cloud Denoising input segmentation output raw point-cloud valid/clear fog rain de-noised Abstract Lidar sensors are frequently used in environme
[CVPR 2021] Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach
Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach This is the repo to host the dataset TextSeg and code for TexRNe
Implementation of StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation in PyTorch
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation Implementation of StyleSpace Analysis: Disentangled Controls for StyleGAN Ima
Generic Event Boundary Detection: A Benchmark for Event Segmentation
Generic Event Boundary Detection: A Benchmark for Event Segmentation We release our data annotation & baseline codes for detecting generic event bound
PyTorch implementation of ARM-Net: Adaptive Relation Modeling Network for Structured Data.
A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.
Complete U-net Implementation with keras
U Net Lowered with Keras Complete U-net Implementation with keras Original Paper Link : https://arxiv.org/abs/1505.04597 Special Implementations : The
The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"
Swin-Unet The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"(https://arxiv.org/abs/2105.05537). A validatio
This repo is a PyTorch implementation for Paper "Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds"
Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds This repository is a PyTorch implementation for paper: Uns
(CVPR2021) DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation CVPR2021(oral) [arxiv] Requirements python3.7 pytorch==
A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!
Stox ⚡ A Python Module For The Stock Market ⚡ A Module to predict the "close price" for the next day and give "technical analysis". It uses a Neural N
Gamestonk Terminal is an awesome stock and crypto market terminal
Gamestonk Terminal is an awesome stock and crypto market terminal. A FOSS alternative to Bloomberg Terminal.
30 Days Of Machine Learning Using Pytorch
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
BRepNet: A topological message passing system for solid models
BRepNet: A topological message passing system for solid models This repository contains the an implementation of BRepNet: A topological message passin
Robust Instance Segmentation through Reasoning about Multi-Object Occlusion [CVPR 2021]
Robust Instance Segmentation through Reasoning about Multi-Object Occlusion [CVPR 2021] Abstract Analyzing complex scenes with DNN is a challenging ta
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering Jang Hyun Cho1, Utkarsh Mall2, Kavita Bala2, Bharath Harihar
Code for the paper One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation, CVPR 2021.
One Thing One Click One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation (CVPR2021) Code for the paper One Thi
Code for our TKDE paper "Understanding WeChat User Preferences and “Wow” Diffusion"
wechat-wow-analysis Understanding WeChat User Preferences and “Wow” Diffusion. Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang,
OrienMask: Real-time Instance Segmentation with Discriminative Orientation Maps
OrienMask This repository implements the framework OrienMask for real-time instance segmentation. It achieves 34.8 mask AP on COCO test-dev at the spe
frida-based ceserver. iOS analysis is possible with Cheat Engine.
frida-ceserver frida-based ceserver. iOS analysis is possible with Cheat Engine. Original by Dark Byte. Usage Install frida on iOS. python main.py Cyd
TunBERT is the first release of a pre-trained BERT model for the Tunisian dialect using a Tunisian Common-Crawl-based dataset.
TunBERT is the first release of a pre-trained BERT model for the Tunisian dialect using a Tunisian Common-Crawl-based dataset. TunBERT was applied to three NLP downstream tasks: Sentiment Analysis (SA), Tunisian Dialect Identification (TDI) and Reading Comprehension Question-Answering (RCQA)
🧪 Panel-Chemistry - exploratory data analysis and build powerful data and viz tools within the domain of Chemistry using Python and HoloViz Panel.
🧪📈 🐍. The purpose of the panel-chemistry project is to make it really easy for you to do DATA ANALYSIS and build powerful DATA AND VIZ APPLICATIONS within the domain of Chemistry using using Python and HoloViz Panel.
spafe: Simplified Python Audio-Features Extraction
spafe aims to simplify features extractions from mono audio files. The library can extract of the following features: BFCC, LFCC, LPC, LPCC, MFCC, IMFCC, MSRCC, NGCC, PNCC, PSRCC, PLP, RPLP, Frequency-stats etc. It also provides various filterbank modules (Mel, Bark and Gammatone filterbanks) and other spectral statistics.
🐸 Identify anything. pyWhat easily lets you identify emails, IP addresses, and more. Feed it a .pcap file or some text and it'll tell you what it is! 🧙♀️
🐸 Identify anything. pyWhat easily lets you identify emails, IP addresses, and more. Feed it a .pcap file or some text and it'll tell you what it is! 🧙♀️
Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis.
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
Segmentation and Identification of Vertebrae in CT Scans using CNN, k-means Clustering and k-NN
Segmentation and Identification of Vertebrae in CT Scans using CNN, k-means Clustering and k-NN If you use this code for your research, please cite ou
MDAnalysis tool to calculate membrane curvature.
The MDAkit for membrane curvature analysis is part of the Google Summer of Code program and it is linked to a Code of Conduct.
This repository contains the code for our fast polygonal building extraction from overhead images pipeline.
Polygonal Building Segmentation by Frame Field Learning We add a frame field output to an image segmentation neural network to improve segmentation qu
NBEATSx: Neural basis expansion analysis with exogenous variables
NBEATSx: Neural basis expansion analysis with exogenous variables We extend the NBEATS model to incorporate exogenous factors. The resulting method, c
Implementation of Uformer, Attention-based Unet, in Pytorch
Uformer - Pytorch Implementation of Uformer, Attention-based Unet, in Pytorch. It will only offer the concat-cross-skip connection. This repository wi
A set of functions and analysis classes for solvation structure analysis
SolvationAnalysis The macroscopic behavior of a liquid is determined by its microscopic structure. For ionic systems, like batteries and many enzymes,
Code for Towards Streaming Perception (ECCV 2020) :car:
sAP — Code for Towards Streaming Perception ECCV Best Paper Honorable Mention Award Feb 2021: Announcing the Streaming Perception Challenge (CVPR 2021
Official implementation of "SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers"
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Figure 1: Performance of SegFormer-B0 to SegFormer-B5. Project page
FANet - Real-time Semantic Segmentation with Fast Attention
FANet Real-time Semantic Segmentation with Fast Attention Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko , Stan Sc
Code for weakly supervised segmentation of a single class
SingleClassRL Implementation of weak single object segmentation from paper "Regularized Loss for Weakly Supervised Single Class Semantic Segmentation"
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation (CVPR 2021)
ASGNet The code is for the paper "Adaptive Prototype Learning and Allocation for Few-Shot Segmentation" (accepted to CVPR 2021) [arxiv] Overview data/
Aerial Imagery dataset for fire detection: classification and segmentation (Unmanned Aerial Vehicle (UAV))
Aerial Imagery dataset for fire detection: classification and segmentation using Unmanned Aerial Vehicle (UAV) Title FLAME (Fire Luminosity Airborne-b
Vent domain information retrieval tool, which is capable of retrieving customer information
Vent domain information retrieval tool, which is capable of retrieving customer information. This tool has been created for the purpose of complete education, Iam not responsible for any illegal activities.
Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch
Segformer - Pytorch Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch. Install $ pip install segformer-pytorch
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
STCN Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [a
Source codes of CenterTrack++ in 2021 ICME Workshop on Big Surveillance Data Processing and Analysis
MOT Tracked object bounding box association (CenterTrack++) New association method based on CenterTrack. Two new branches (Tracked Size and IOU) are a
Code implementation of "Sparsity Probe: Analysis tool for Deep Learning Models"
Sparsity Probe: Analysis tool for Deep Learning Models This repository is a limited implementation of Sparsity Probe: Analysis tool for Deep Learning
InsightFace: 2D and 3D Face Analysis Project on MXNet and PyTorch
InsightFace: 2D and 3D Face Analysis Project on MXNet and PyTorch
"SOLQ: Segmenting Objects by Learning Queries", SOLQ is an end-to-end instance segmentation framework with Transformer.
SOLQ: Segmenting Objects by Learning Queries This repository is an official implementation of the paper SOLQ: Segmenting Objects by Learning Queries.
This is the official Pytorch implementation of "Lung Segmentation from Chest X-rays using Variational Data Imputation", Raghavendra Selvan et al. 2020
README This is the official Pytorch implementation of "Lung Segmentation from Chest X-rays using Variational Data Imputation", Raghavendra Selvan et a
The implementation of PEMP in paper "Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes"
Prior-Enhanced network with Meta-Prototypes (PEMP) This is the PyTorch implementation of PEMP. Overview of PEMP Meta-Prototypes & Adaptive Prototypes
Paddle implementation for "Highly Efficient Knowledge Graph Embedding Learning with Closed-Form Orthogonal Procrustes Analysis" (NAACL 2021)
ProcrustEs-KGE Paddle implementation for Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis 🙈 A more detailed re
Using context-free grammar formalism to parse English sentences to determine their structure to help computer to better understand the meaning of the sentence.
Sentance Parser Executing the Program Make sure Python 3.6+ is installed. Install requirements $ pip install requirements.txt Run the program:
Symbolic Parallel Adaptive Importance Sampling for Probabilistic Program Analysis in JAX
SYMPAIS: Symbolic Parallel Adaptive Importance Sampling for Probabilistic Program Analysis Overview | Installation | Documentation | Examples | Notebo
[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
TorchSemiSeg [CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision by Xiaokang Chen1, Yuhui Yuan2, Gang Zeng1, Jingdong Wang
The toolkit to generate auto labeled datasets
Ozeu Ozeu is the toolkit to autolabal dataset for instance segmentation. You can generate datasets labaled with segmentation mask and bounding box fro
🔬 A curated list of awesome machine learning strategies & tools in financial market.
🔬 A curated list of awesome machine learning strategies & tools in financial market.
PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations This is the official PyTorch implementation
APKLeaks - Scanning APK file for URIs, endpoints & secrets.
APKLeaks - Scanning APK file for URIs, endpoints & secrets.
A PyTorch implementation of EfficientDet.
A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
(AAAI2020)Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing
Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing This repository contains pytorch source code for AAAI2020 oral paper: Grapy-ML
Solve various integral equations using numerical methods in Python
Solve Volterra and Fredholm integral equations This Python package estimates Volterra and Fredholm integral equations using known techniques. Installa
A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!
Stox A Module to predict the "close price" for the next day and give "technical analysis". It uses a Neural Network and the LSTM algorithm to predict
Medical Image Segmentation using Squeeze-and-Expansion Transformers
Medical Image Segmentation using Squeeze-and-Expansion Transformers Introduction This repository contains the code of the IJCAI'2021 paper 'Medical Im
Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving
SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving Abstract In this paper, we introduce SalsaNext f
Pytorch codes for "Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation"
Self-Supervised-MVS This repository is the official PyTorch implementation of our AAAI 2021 paper: "Self-supervised Multi-view Stereo via Effective Co
code for `Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation`
Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation (CVPR 2021) Introduction PBR is a conceptually simple yet effective
pyprobables is a pure-python library for probabilistic data structures
pyprobables is a pure-python library for probabilistic data structures. The goal is to provide the developer with a pure-python implementation of common probabilistic data-structures to use in their work.
leafmap - A Python package for geospatial analysis and interactive mapping in a Jupyter environment.
A Python package for geospatial analysis and interactive mapping with minimal coding in a Jupyter environment
SiamMOT is a region-based Siamese Multi-Object Tracking network that detects and associates object instances simultaneously.
SiamMOT: Siamese Multi-Object Tracking
precise iris segmentation
PI-DECODER Introduction PI-DECODER, a decoder structure designed for Precise Iris Segmentation and Location. The decoder structure is shown below: Ple
Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
Image Crop Analysis This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CAC) Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Li