This project is a deep learning system designed for real-time emotion recognition and facial expression analysis. It utilizes a convolutional neural network architecture to process raw visual input, mapping complex facial patterns to seven distinct emotional states through a supervised machine learning pipeline. The system functions as both a training framework and an inference engine. It includes utilities for preparing and standardizing large image datasets to ensure consistent input quality, alongside a real-time processing pipeline that captures and buffers live video frames to perform co
lite.ai.toolkit is a C++ computer vision toolkit designed for edge AI deployment. It enables the execution of pre-trained models for object detection, image classification, and segmentation on resource-constrained devices. The project features a multi-backend inference engine that supports the ONNX model runtime, allowing AI models to run across different hardware targets. It includes a GPU-accelerated pipeline specifically for NVIDIA hardware to reduce latency and increase processing speed. The toolkit covers a broad range of facial analysis capabilities, including emotion detection, gender
Deepface is a comprehensive deep learning library for facial recognition and demographic analysis. It provides a modular pipeline that handles the entire lifecycle of facial processing, including detection, geometric alignment, and the transformation of facial images into high-dimensional numerical vector embeddings for identity verification and similarity comparison. The library distinguishes itself through a model ensemble approach, which combines predictions from multiple pre-trained neural networks to improve classification accuracy and reduce bias. It also integrates advanced security fe
Faceai is a computer vision toolkit designed for facial analysis, identity recognition, and image processing. It provides integrated engines for detecting human faces in static images and live video streams, matching facial encodings against identity databases, and mapping facial landmarks to understand geometric structure and alignment. The project enables real-time augmented reality applications, such as applying virtual makeup and digital accessories by scaling assets to detected facial coordinates. It also includes a suite for digital image restoration capable of removing noise, erasing w
هذا المشروع عبارة عن نظام للتعلم العميق لتصنيف الوجوه يكتشف الوجوه البشرية ويصنف الجنس والعاطفة. يستخدم الشبكات العصبية التلافيفية وأدوات الرؤية الحاسوبية لتحليل سمات الوجه في كل من الصور الثابتة ومقاطع الفيديو الحية.
الميزات الرئيسية لـ oarriaga/face_classification هي: Emotion Classifiers, Face Detection, Custom Model Training, Attribute Classifiers, Facial Emotion Classifiers, Facial Expression Recognition, Gender Predictions, CNN Architectures.
تشمل البدائل مفتوحة المصدر لـ oarriaga/face_classification: atulapra/emotion-detection — This project is a deep learning system designed for real-time emotion recognition and facial expression analysis. It… xlite-dev/lite.ai.toolkit — lite.ai.toolkit is a C++ computer vision toolkit designed for edge AI deployment. It enables the execution of… serengil/deepface — Deepface is a comprehensive deep learning library for facial recognition and demographic analysis. It provides a… vipstone/faceai — Faceai is a computer vision toolkit designed for facial analysis, identity recognition, and image processing. It… mjrovai/opencv-face-recognition — OpenCV-Face-Recognition is a computer vision system designed to detect human faces and verify identities within live… esimov/pigo — Pigo is a computer vision library written in Go for locating human faces in images and video streams. It provides…