PyTorch

Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking

ArTIST Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking (CVPR 2021) Pytorch implementation of the ArTIST motion model. In this repo, there are Training script for the Moving Agent network Training script for the ArTIST motion model Demo script for Inferring the likelihood of current observations (detections) Demo script for Inpainting the missing observation/detections Demo 1: Likelihood estimation of observation Run: python3 demo_scoring.py This will generate the output in the temp/ar/log_p directory, look like this: This demo gets as […]

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Translation

Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data

BIFI Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data This repo provides the source code & data of our paper: Break-It-Fix-It: Unsupervised Learning for Program Repair (ICML 2021). @InProceedings{yasunaga2021break, author = {Michihiro Yasunaga and Percy Liang}, title = {Break-It-Fix-It: Unsupervised Learning for Program Repair}, year = {2021}, booktitle = {International Conference on Machine Learning (ICML)}, } Problem: Repair Task Our approach: BIFI 0. Dependencies Specifically, run the following commands to create a conda environment (assuming CUDA10.1): conda create -n BIFI […]

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Database

Migrate data from SQL to NoSQL easily with python

sql2nosql Migrate data from SQL to NoSQL easily. Installation 💯 pip install sql2nosql –upgrade Dependencies 📢 For the package to work, it first needs “clients”, which are other packages that are in charge of managing the data in the database. Most of them work very similar, as in the case of ‘mysql-connector’ and ‘pymysql’ for MySQL databases, and ‘PyMongo’ for MongoDB databases. For example, the parameter ‘sql_client’ of the Migrator() class, receives by parameter a string where it is indicated […]

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Text

Saliency-based Span Mixup for Text Classification

SSMix Saliency-based Span Mixup for Text Classification (Findings of ACL 2021) Abstract Data augmentation with mixup has shown to be effective on various computer vision tasks. Despite its great success, there has been a hurdle to apply mixup to NLP tasks since text consists of discrete tokens with variable length. In this work, we propose SSMix, a novel mixup method where the operation is performed on input text rather than on hidden vectors like previous approaches. SSMix synthesizes a sentence […]

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Framework

Framework that uses artificial intelligence applied to mathematical models to make predictions

LiconIA Framework that uses artificial intelligence applied to mathematical models to make predictions Requirements Python 3.6 or superior (sudo apt-get install python3.6 under Linux)Python virtual environment (sudo apt-get install python3.6-venv under Linux) Development and Tests Installing the package Start by creating a new virtual environment for your project. Next, update the packages pip and setuptools to the latest version. Then install the package itself. $ sudo apt-get install python3-tk $ /usr/bin/python3.6 -m venv –prompt=”LiconIA” venv $ source venv/bin/activate (LiconIA) $ […]

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Command-line Tools

A simple tool to query the awesome ippsec.rocks website from terminal

ippsec-cli This a simple tool to query the awesome ippsec.rocks website from your terminal Installation and usage cd /opt git clone https://github.com/stark0de/ippsec-cli cd ippsec-cli pip3 install -r requirements.txt chmod +x ippsec-cli.py python3 -W ignore ippsec-cli.py Note: optionally you can go to /home/$USER/.bashrc and add this line so u can just launch it putting ippsec-cli in your terminal: vim /home/$USER/.bashrc alias ippsec-cli=”python3 -W ignore /opt/ippsec-cli/ippsec-cli.py” source /home/$USER/.bashrc Credits to @HexF_me, @Shell_ock and of course to the awesome Ippsec 😉 Note: I’ve […]

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Machine Learning

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 passing system for solid models. About BRepNet BRepNet is a neural network specifically designed to operate on solid models. It uses additional topological information present in the boundary representation (B-Rep) data structure to perform convolutions in a way which is not possible for arbitrary graphs. As B-Reps describe manifolds, they contain additional topological information which includes the ordering of edges […]

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Network

A Network Shredder IDS for python

Network-Shredder Network-Shredder is a python based NIDS. Installation git clone https://github.com/v0lck3r/Network-Shredder.git cd Network-Shredder pip3 install -r requirements.txt Example usage python3 Network-Shredder.py -h Live mode python3 Network-Shredder.py rules.txt –interface tun0 Start web application python3 Network-Shredder.py rules.txt –interface tun0 –web Console quiet mode python3 Network-Shredder.py rules.txt –interface tun0 –web –quiet Specify log directory python3 Network-Shredder.py rules.txt –logdir /tmp/ –interface tun0 –web Pcap based detection python3 Network-Shredder.py rules.txt –pcap pcap_file.pcap GitHub https://github.com/v0lck3r/Network-Shredder    

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Text

Print text color and text format on Term with Python

term-printer Print ‘text color’ and ‘text format’ on Term with Python ※ It may not work depending on the OS and shell used. PIP $ pip install term-printer import from term_printer import Color, Color256, ColorRGB, StdText, cprint If you want to override bultin print function from term_printer import Color, Color256, ColorRGB, StdText, cprint as print Usage 1. Attrs print Applies to all characters. You can specify Format, Color, Color256, and ColorRGB. Able to specify more than one. source from term_printer […]

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Machine Learning

Dependency Cluster Attention for Aspect-level sentiment classification

DLCF-DCA codes for paper Combining Dynamic Local Context Focus and Dependency Cluster Attention for Aspect-level sentiment classification. submitted to 《Neurocomputing》. Requirement Python >= 3.6 PyTorch >= 1.0 pytorch-transformers == 1.2.0 SpaCy >= 2.2 To use our models, you need download en_core_web_sm by python -m spacy download en_core_web_sm Training python train.py –model dlcf_dca Model Architecture Note Some important scripts to note: datasets/semeval14/*.seg: Preprocessed training and testing sentences in SemEval2014. datasets/semeval15/*.seg: Preprocessed training and testing sentences in SemEval2015. datasets/semeval16/*.seg: Preprocessed training and […]

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