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Showing 12 open source projects for "dlib"

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  • 1
    dlib

    dlib

    Toolkit for making machine learning and data analysis applications

    Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge.
    Downloads: 14 This Week
    Last Update:
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  • 2
    dlib C++ Library
    Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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    Downloads: 50 This Week
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  • 3
    deepface

    deepface

    A Lightweight Face Recognition and Facial Attribute Analysis

    DeepFace is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid face recognition framework wrapping state-of-the-art models: VGG-Face, FaceNet, OpenFace, DeepFace, DeepID, ArcFace, Dlib, SFace and GhostFaceNet. Experiments show that human beings have 97.53% accuracy on facial recognition tasks whereas those models already reached and passed that accuracy level.
    Downloads: 27 This Week
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  • 4
    OpenFace Face Recognition

    OpenFace Face Recognition

    Face recognition with deep neural networks

    OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google. Torch allows the network to be executed on a CPU or with CUDA. This research was supported by the National Science Foundation (NSF) under grant number CNS-1518865. Additional support was provided by the Intel Corporation, Google,...
    Downloads: 1 This Week
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  • 5
    Face Alignment

    Face Alignment

    2D and 3D Face alignment library build using pytorch

    ...For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively use dlib, BlazeFace, or pre-existing ground truth bounding boxes. While not required, for optimal performance(especially for the detector) it is highly recommended to run the code using a CUDA-enabled GPU. While here the work is presented as a black box, if you want to know more about the intrisecs of the method please check the original paper either on arxiv or my webpage.
    Downloads: 0 This Week
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  • 6
    Pigo

    Pigo

    Fast face detection, pupil/eyes localization

    ...The reason why Pigo has been developed is because almost all of the currently existing solutions for face detection in the Go ecosystem are purely bindings to some C/C++ libraries like OpenCV or dlib, but calling a C program through cgo introduces huge latencies and implies a significant trade-off in terms of performance. Also, in many cases installing OpenCV on various platforms is cumbersome.
    Downloads: 7 This Week
    Last Update:
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  • 7
    3DDFA

    3DDFA

    Fast, accurate and stable 3D dense face alignment

    ...This repo is the official implementation of 3DDFA_V2. Compared to 3DDFA, 3DDFA_V2 achieves better performance and stability. Besides, 3DDFA_V2 incorporates the fast face detector FaceBoxes instead of Dlib. A simple 3D render written by c++ and cython is also included. This repo supports the onnxruntime, and the latency of regressing 3DMM parameters using the default backbone is about 1.35ms/image on CPU with a single image as input. See requirements.txt, tested on macOS and Linux platforms. The Windows users may refer to FQA for building issues. ...
    Downloads: 3 This Week
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  • 8
    MITIE

    MITIE

    MITIE: library and tools for information extraction

    ...The current release includes tools for performing named entity extraction and binary relation detection as well as tools for training custom extractors and relation detectors. MITIE is built on top of dlib, a high-performance machine-learning library[1], MITIE makes use of several state-of-the-art techniques including the use of distributional word embeddings[2] and Structural Support Vector Machines[3]. MITIE offers several pre-trained models providing varying levels of support for both English, Spanish, and German trained using a variety of linguistic resources (e.g., CoNLL 2003, ACE, Wikipedia, Freebase, and Gigaword). ...
    Downloads: 0 This Week
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  • 9

    dlib

    A selectable and portable c language library

    This library can only compile your needed modules, and it is portable on linux, windows and mac os.
    Downloads: 0 This Week
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  • 10
    ...This project is dead, as haar training proved not to be a good approach. Anyway, there is a replacement which works, at https://bitbucket.org/guenterneust/examinator/wiki/Home based on dlib.
    Downloads: 0 This Week
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  • 11

    drows-detect

    This Program detects drowsiness by a person's face

    ...Running the Code: To run the code on your standard Python 3.6 Installation, you must install the dependencies by following this: pip install cmake pip install scipy numpy matplotlib scikit-learn pip install opencv-contrib-python pip install imutils pip install dlib pip install playsound
    Downloads: 0 This Week
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  • 12
    QJoystickManager

    QJoystickManager

    Simple joystick management system for Qt

    QJoystickManager is a cross platform joystick management system. Its written in C++ and uses SDL and the Qt framework. QJoystickManager strives to be as easy to use as possible, it implements many features that will ease the interaction between your program and the attached joysticks. This project uses Qt extensively, and as such users need to a have working knowledge of C++ and Qt basics (Signals and Slots and Qt data types).
    Downloads: 0 This Week
    Last Update:
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