Search Results for "facial emotion detection in real time"

Showing 11 open source projects for "facial emotion detection in real time"

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  • 1
    MediaPipe Face Detection

    MediaPipe Face Detection

    Detect faces in an image

    The MediaPipe Face Detection model is a high-performance, real-time face detection solution that uses machine learning to identify faces in images and video streams. It is optimized for mobile and embedded platforms, offering fast and accurate face detection while maintaining a small memory footprint. This model supports multiple face detections and is highly efficient, making it suitable for a variety of applications such as augmented reality, user authentication, and facial expression analysis.
    Downloads: 3 This Week
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  • 2
    OpenCV

    OpenCV

    Open Source Computer Vision Library

    OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations.
    Downloads: 31 This Week
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  • 3
    Blazeface

    Blazeface

    Blazeface is a lightweight model that detects faces in images

    Blazeface is a lightweight, high-performance face detection model designed for mobile and embedded devices, developed by TensorFlow. It is optimized for real-time face detection tasks and runs efficiently on mobile CPUs, ensuring minimal latency and power consumption. Blazeface is based on a fast architecture and uses deep learning techniques to detect faces with high accuracy, even in challenging conditions. It supports multiple face detection in varying lighting and poses, and is designed...
    Downloads: 1 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: 8 This Week
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  • 5
    Amica

    Amica

    Amica is an open source interface for interactive communication

    Amica is an open source interface for interacting with fully animated 3D characters that combine voice chat, vision, and an emotion engine into a single experience. It lets you hold natural conversations with AI characters that can see, listen, and speak, while expressing emotional states through facial expressions and body language. Users can import VRM character models, adjust their appearance, tune the voice to match the character, and define behavior using different large language models...
    Downloads: 1 This Week
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  • 6

    Liveliness and Face Identification

    Leading free and open-source liveliness check &face recognition system

    This is a free and open-source liveliness check and face recognition project. Essentially, it is an application that can be used as a standalone server or deployed in the cloud. You don’t need prior machine learning skills to set up and use. The application is customizable react based mobile friendly UI and Python based backend. The program is a real-time face detection application. It allows you to detect faces using your webcam and displays the video feed with oval drawn around the...
    Downloads: 3 This Week
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  • 7
    Facetrak Facial recognition
    This program broken The program is a real-time face detection application built using OpenCV and Tkinter. It allows you to detect faces using your webcam and displays the video feed with rectangles drawn around the detected faces. When you run the program, a GUI window will appear. The window has a title "Real-time Face Detection" and a description below it. The description guides you to adjust the settings and click the "Start" button to begin face detection. The settings section...
    Downloads: 0 This Week
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  • 8
    OpenPose

    OpenPose

    Real-time multi-person keypoint detection library for body, face, etc.

    OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images. It is authored by Ginés Hidalgo, Zhe Cao, Tomas Simon, Shih-En Wei, Yaadhav Raaj, Hanbyul Joo, and Yaser Sheikh. It is maintained by Ginés Hidalgo and Yaadhav Raaj. OpenPose would not be possible without the CMU Panoptic Studio dataset. We would also like to thank all the people who has helped OpenPose in any way. 15, 18 or...
    Downloads: 27 This Week
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  • 9
    opencv4nodejs

    opencv4nodejs

    Nodejs bindings to OpenCV 3 and OpenCV 4

    OpenCV4NodeJS is a Node.js binding for OpenCV, allowing developers to integrate computer vision capabilities directly into JavaScript applications for image processing, object detection, and facial recognition.
    Downloads: 0 This Week
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  • 10

    OpenFace

    A state-of-the-art facial behavior analysis toolkit

    OpenFace is an advanced facial behavior analysis toolkit intended for computer vision and machine learning researchers, those in the affective computing community, and those who are simply interested in creating interactive applications based on facial behavior analysis. The OpenFace toolkit is capable of performing several complex facial analysis tasks, including facial landmark detection, eye-gaze estimation, head pose estimation and facial action unit recognition. ...
    Downloads: 20 This Week
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  • 11

    Facial Expression Recognition

    Facial Expression Recognition System - Matlab source code

    ...The extracted feature vectors in the reduced space are used to train the supervised Neural Network classifier. This approach results extremely powerful because it does not require the detection of any reference point or node grid. The proposed method is fast and can be used for real-time applications.
    Downloads: 0 This Week
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