Displaying 1 to 13 from 13 results

imglab - To speedup and simplify image labeling/ annotation process with multiple supported formats.

  •    HTML

A web based tool to label images for objects that can be used to train dlib or other object detectors. With most users switching over to the new version of imglab, the legacy version of imglab has been removed.

amoc-project - Moodify: Recognizes emotion from face, generates a suitable playlist in the music player

  •    Python

A WebApp which uses a snapshot taken of the user to detect emotion and using this, generate a suitable music playlist. This project was built for ACM Month Of Code, actual coding done in about 3 weeks. The Cam, Music Player, scripts for emotion recognition and Database were wired and wrapped up into a WebApp using Flask, using routes to use the Backend like an API while the frontend handles the user.

ofxDlib - An openFrameworks wrapper for dlib. http://dlib.net/

  •    C++

This is under development currently so, your please post questions to the issues for now. For more, see docs/GETTING_STARTED.md.

go-face - :mag: Face recognition with Go

  •    Go

go-face implements face recognition for Go using dlib, a popular machine learning toolkit. Read Face recognition with Go article for some background details if you're new to FaceNet concept. To compile go-face you need to have dlib (>= 19.10) and libjpeg development packages installed.

transito-cv - Traffic sign detector and classifier that uses dlib and its implementation of the Felzenszwalb's version of the Histogram of Oriented Gradients (HoG) detector

  •    C++

Note: this repository was created for the final project of an undergraduate course and won't receive any major updates. There are methods with better results than HoG for traffic sign detector, such as Deep Learning architectures. Still, you can use this repository as a study reference or for some practical purposes. This is a traffic sign detector and classifier that uses dlib and its implementation of the Felzenszwalb's version of the Histogram of Oriented Gradients (HoG) detector.

image - Computer Vision and Image Recognition algorithms for R users

  •    C

This repository contains a suite of R packages which perform image algorithms currently not available in other R packages like magick, imager or EBImage. More packages and extensions are under development.

drishti - Real time eye tracking for embedded and mobile devices.

  •    C++

Native iOS, Android, and "desktop" variants of the real-time facefilter application have been added here: src/examples/facefilter. These applications link against the installed public drishti::drishti package interface, which is designed without external types in the API definition. The facefilter demos are enabled by the DRISHTI_BUILD_EXAMPLES CMake option, and the entire src/examples tree is designed to be relocatable, you can cp -r src/examples ${HOME}/drishti_examples, customize, and build, by simply updating the drishti package details. The iOS facefilter target requires Xcode 9 (beta 4) or above (Swift language requirements) and will be generated directly as a standard CMake add_executable() target as part of the usual top level project build -- if you are using an appropriate CMake iOS toolchain for cross compilation from your macOS + Xcode host for your iOS device. Please see Polly Based Build and iOS Build below for more details.

dockerface - An easy to use docker solution for deep learning face detection.


Dockerface is a deep learning replacement for dlib and OpenCV non-deep face detection. It deploys a trained Faster R-CNN network on Caffe through an easy to use docker image. Bring your videos and images, run dockerface and obtain videos and images with bounding boxes of face detections and an easy to use face detection annotation text file. The docker image is large for now because OpenCV has to be compiled and stored in the image to be able to use video and it takes up a lot of space.