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https://github.com/thecooldrop/awesome-autonomous

A curated list of repositories, libraries and topics which are related to furthering the autonomous robotics technologies
https://github.com/thecooldrop/awesome-autonomous

List: awesome-autonomous

Last synced: 3 months ago
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A curated list of repositories, libraries and topics which are related to furthering the autonomous robotics technologies

Host: GitHub
URL: https://github.com/thecooldrop/awesome-autonomous
Owner: thecooldrop
License: mit
Created: 2021-03-09T21:04:21.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2021-03-10T22:43:25.000Z (over 3 years ago)
Last Synced: 2024-05-21T02:24:01.552Z (6 months ago)
Size: 5.86 KB
Stars: 0
Watchers: 0
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: readme.md
- Contributing: contributing.md
- License: LICENSE
- Code of conduct: code-of-conduct.md

Awesome Lists containing this project

ultimate-awesome - awesome-autonomous - A curated list of repositories, libraries and topics which are related to furthering the autonomous robotics technologies. (Other Lists / PowerShell Lists)

README

        # Awesome Autonomous [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

> A curated list of repositories, resources and methodologies which lead to advancement of autonomous technologies

## Topics overview

- [Target Tracking](#Tracking)

- [Simultanoues Localization and Mapping](#Simultaneous-localization-and-mapping)

- [Robotics Platforms](#Robotics-platforms)

- [Utility libraries](#Utility-libraries)

## Contribute

Contributions welcome! Read the [contribution guidelines](contributing.md) first.

## Tracking

### Datasets

- [PETS 2009 Benchmark data](http://www.cvg.reading.ac.uk/PETS2009/a.html)

- [MOT Challenge](https://motchallenge.net/)

- [The WILDTRACK Seven-Camera HD Dataset](https://www.epfl.ch/labs/cvlab/data/data-wildtrack/)

- [Nvidia AI City Challenge](https://www.aicitychallenge.org/2020-data-and-evaluation/)

- [VisDrone Dataset](https://github.com/VisDrone/VisDrone-Dataset)

- [Joined Track Auto Dataset](https://github.com/fabbrimatteo/JTA-Dataset)

- [Pathtrack dataset](https://www.trace.ethz.ch/publications/2017/pathtrack/index.html)

- [TAO: A Large-Scale Benchmark for Tracking Any Object](https://github.com/TAO-Dataset/tao)

- [KITTI Datasets] - http://www.cvlibs.net/datasets/kitti/eval_tracking.php

- [3D Lidar Object Detection and Tracking](http://apolloscape.auto/tracking.html)

- [UA-DETRAC](http://www.cs.albany.edu/cvml/cvml_downloads.html)

- [BDD100K Tracking Challenge](https://bdd-data.berkeley.edu/)

### Papers

About this section. Optional. Keep this short and focus on the list.

- [List item](http://example.com)

- [List item](http://example.com)

## Hand detection and pose estimation

### Datasets

- [EgoHands: A Dataset for Hands in Complex Egocentric Interactions](http://vision.soic.indiana.edu/projects/egohands/)

- [Oxford hand dataset](https://www.robots.ox.ac.uk/~vgg/research/hands/index.html)

### Repositories

- [handtracking by Victor Dibia](https://github.com/victordibia/handtracking)

- [Detecting hands in images tutorial](https://github.com/jkjung-avt/hand-detection-tutorial)

- [Hand Detection and Distance Estimation](https://github.com/pablovela5620/Hand-Detection-and-Distance-Estimation)

- [Handpose - A program to recognize hand pose fom RGB camera](https://github.com/MrEliptik/HandPose)

- [Gesture recognition from egocentric view](https://github.com/zzeitt/Gesture-Recognition)

### Resource collections

- [Awesome hand pose estimation](https://github.com/xinghaochen/awesome-hand-pose-estimation)

- []

### Articles

- [How to build a real time hand detector using neural networks](https://medium.com/@victor.dibia/how-to-build-a-real-time-hand-detector-using-neural-networks-ssd-on-tensorflow-d6bac0e4b2ce)

- 

## Simultaneous localization and mapping

## Robotics platforms

## Eye tracking

### Articles

- [Eye Tracking in Python with OpenCV](https://medium.com/@stepanfilonov/tracking-your-eyes-with-python-3952e66194a6)

### Libraries

- [Pupil](https://github.com/pupil-labs/pupil/)

- [Webgazer.js](https://github.com/brownhci/WebGazer)

### Tools and vendors

- [Pupil Labs](https://docs.pupil-labs.com/developer/core/network-api/)

## Utility-libraries

### Rust

- [Ndarray](https://github.com/rust-ndarray/ndarray) - Numpy equivalent in Rust

- [Nalgebra](https://nalgebra.org/) - Matrices library with type-safe dimensions

  

### Python

- [Numpy](https://numpy.org/)

- [Scipy](https://www.scipy.org/)

- [Matplotlib](https://matplotlib.org/)

## Machine learning support systems:

- [Keepsake - Version control for machine learning](https://github.com/replicate/keepsake)

- [Drifter_ml - Testing for Scikit models](https://github.com/EricSchles/drifter_ml)

- [Aim - Easy way to record and compare ML training runs](https://github.com/aimhubio/aim)

- [Clearml - ML experiment tracking tool](https://github.com/allegroai/clearml)

- [Hopsworks - Feature store](https://github.com/logicalclocks/hopsworks)

- [Polyaxon](https://github.com/polyaxon/polyaxon)

- [Sacred](https://github.com/IDSIA/sacred)

- [Guild AI - Optimize and automate ML experiments](https://github.com/guildai/guildai)

- [DVC - Data version control](https://github.com/iterative/dvc)

- [ML-Logger - Logging utility for ML](https://github.com/geyang/ml_logger)

- [MLflow: A Machine Learning Lifecycle Platform](https://github.com/mlflow/mlflow/)

- [labml.ai - mobile experimet and training tracking](https://github.com/lab-ml/labml)