write-you-a-haskell - Building a modern functional compiler from first principles

•    Haskell

Building a modern functional compiler from first principles. This is a work in progress.

evo - Python package for the evaluation of odometry and SLAM

•    Python

This package provides executables and a small library for handling, evaluating and comparing the trajectory output of odometry and SLAM algorithms. See here for more infos about the formats.

AB3DMOT - (IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"

•    Python

3D multi-object tracking (MOT) is an essential component technology for many real-time applications such as autonomous driving or assistive robotics. However, recent works for 3D MOT tend to focus more on developing accurate systems giving less regard to computational cost and system complexity. In contrast, this work proposes a simple yet accurate real-time baseline 3D MOT system. We use an off-the-shelf 3D object detector to obtain oriented 3D bounding boxes from the LiDAR point cloud. Then, a combination of 3D Kalman filter and Hungarian algorithm is used for state estimation and data association. Although our baseline system is a straightforward combination of standard methods, we obtain the state-of-the-art results. To evaluate our baseline system, we propose a new 3D MOT extension to the official KITTI 2D MOT evaluation along with two new metrics. Our proposed baseline method for 3D MOT establishes new state-of-the-art performance on 3D MOT for KITTI, improving the 3D MOTA from 72.23 of prior art to 76.47. Surprisingly, by projecting our 3D tracking results to the 2D image plane and compare against published 2D MOT methods, our system places 2nd on the official KITTI leaderboard. Also, our proposed 3D MOT method runs at a rate of 214.7 FPS, 65 times faster than the state-of-the-art 2D MOT system. 1. Clone the github repository.

datasets - 🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

•    Python

🤗Datasets also provides access to +15 evaluation metrics and is designed to let the community easily add and share new datasets and evaluation metrics. 🤗Datasets originated from a fork of the awesome TensorFlow Datasets and the HuggingFace team want to deeply thank the TensorFlow Datasets team for building this amazing library. More details on the differences between 🤗Datasets and tfds can be found in the section Main differences between 🤗Datasets and tfds.

lispy - Short and sweet LISP editing

•    Emacs

This package reimagines Paredit - a popular method to navigate and edit LISP code in Emacs. Most of more than 100 interactive commands that lispy provides are bound to a-z and A-Z in lispy-mode. You can see the full command reference with many examples here.

govaluate - Arbitrary expression evaluation for golang

•    Go

Provides support for evaluating arbitrary C-like artithmetic/string expressions. Sometimes, you can't know ahead-of-time what an expression will look like, or you want those expressions to be configurable. Perhaps you've got a set of data running through your application, and you want to allow your users to specify some validations to run on it before committing it to a database. Or maybe you've written a monitoring framework which is capable of gathering a bunch of metrics, then evaluating a few expressions to see if any metrics should be alerted upon, but the conditions for alerting are different for each monitor.

xai - XAI - An eXplainability toolbox for machine learning

•    Python

XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contains various tools that enable for analysis and evaluation of data and models. The XAI library is maintained by The Institute for Ethical AI & ML, and it was developed based on the 8 principles for Responsible Machine Learning. You can find the documentation at https://ethicalml.github.io/xai/index.html. You can also check out our talk at Tensorflow London where the idea was first conceived - the talk also contains an insight on the definitions and principles in this library.

tcexam - TCExam is a CBA (Computer-Based Assessment) system (e-exam, CBT - Computer Based Testing) for universities, schools and companies, that enables educators and trainers to author, schedule, deliver, and report on surveys, quizzes, tests and exams

•    PHP

FOR ANY USAGE THAT REQUIRES COMMERCIAL LICENSING TERMS, PLEASE CONTACT INFO@TECNICK.COM TO PURCHASE A LICENSE. TCExam includes some third-party software components that are not strictly required but have been included as you convenience, and if used are subject to their respective licenses.

tide - A General Toolbox for Identifying Object Detection Errors

•    Python

An easy-to-use, general toolbox to compute and evaluate the effect of object detection and instance segmentation on overall performance. This is the code for our paper: TIDE: A General Toolbox for Identifying Object Detection Errors (ArXiv) [ECCV2020 Spotlight]. The current version is v1.0.1 (changelog).

OpenQuestions

OpenQuestions is the leading open source source for exam simulators. Main features: * All type of questions supported (single choice, multiple choice, open answers, matching, fill the gaps, etc) * Customisable appearance (look and feel) with themes. * Multi-lingual support.

DukeMTMC-reID_evaluation - ICCV2017 The Person re-ID Evaluation Code for DukeMTMC-reID Dataset (Including Dataset Download)

•    Matlab

What's new: Following the license on the DukeMTMC website, we added a few modifications to the license terms. You may check the license in this repo. The dataset is released only for academic research. DukeMTMC-reID [1] is a subset of the DukeMTMC dataset [2] for image-based re-identification, in the format of the Market-1501 dataset. The original dataset contains 85-minute high-resolution videos from 8 different cameras. Hand-drawn pedestrain bounding boxes are available.

semantic-kitti-api - SemanticKITTI API for visualizing dataset, processing data, and evaluating results

•    Python

This repository contains helper scripts to open, visualize, process, and evaluate results for point clouds and labels from the SemanticKITTI dataset. ALL OF THE SCRIPTS CAN BE INVOKED WITH THE --help (-h) FLAG, FOR EXTRA INFORMATION AND OPTIONS.

mendel - Build toolchain for experimentation on isomorphic web applications with tree-inheritance and multivariate support

•    Javascript

Mendel is a framework for building and serving client side JavaScript bundles for A/B testing experiments in web applications.It is meant to be simple and easy to use on a daily basis. It works very well for small applications and small teams, but also scale for complex use cases that large applications or larger teams might need.

Eval-Expression

•    CSharp

From simple C# math expression...To complex code to parse.

Eval-SQL

•    CSharp

Provide to your SQL Server all missing pieces like regular expression and dynamic arithmetic string evaluation.Performance tuning is one of the most important task for a DBA. Don’t miss the chance to dramatically improve query performance by 300% for simple expression and by more than 2000% for complex code over User-Defined Function (UDF) and Table-Valued Function (TVF).

extended-berkeley-segmentation-benchmark - Extended version of the Berkeley Segmentation Benchmark [1] used for evaluation in [2]

•    C++

A more comprehensive benchmark can now be found at davidstutz/superpixel-benchmark.This is an extended version of the Berkeley Segmentation Benchmark, available here and introduced in [1], used to assess superpixel algorithms.

superpixel-benchmark - An extensive evaluation and comparison of 28 state-of-the-art superpixel algorithms on 5 datasets

•    C++

This repository contains the source code used for evaluation in [1], a large-scale comparison of state-of-the-art superpixel algorithms.This repository subsumes earlier work on comparing superpixel algorithms: davidstutz/gcpr2015-superpixels, davidstutz/superpixels-revisited.

scriptor - (DEFUNCT) Scriptor is the ultimate library for dynamically loading, reloading and running scripts

•    Javascript

Scriptor is the ultimate library for dynamically loading, reloading and running scripts, with built-in support for file watching to automatically reload when necessary.A script is defined as a file which can be 'required' via CommonJS require function in node and io.js. It can be a .js, .json, and even .node or any other installed extension. For the asynchronous build of Scriptor, custom extensions can even be defined that take advantage of Promises and Coroutines.

lazy-value - Create a lazily evaluated value

•    Javascript

Useful when a value is expensive to generate, so you want to delay the computation until the value is needed. For example, improving startup performance by deferring nonessential operations.Expected to return a value.

define-lazy-prop - Define a lazily evaluated property on an object

•    Javascript

Useful when the value of a property is expensive to generate, so you want to delay the computation until the property is needed. For example, improving startup performance by deferring nonessential operations.Object to add property to.