Deepfakes Software For All
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
DeepFaceLab is the leading software for creating deepfakes.
Keras implementation of the renowned publication "DeepFace: Closing the Gap to Human-Level Performance in Face Verification" by Taigman et al. Pre-trained weights on VGGFace2 dataset.
Facial Emotion Recognition using OpenCV and Deepface
face detection, verification and recognition using Keras
This project is a comprehensive face recognition-based attendance system for universities. It leverages OpenCV for face detection and recognition, Firebase for data storage, and Flask for the web interface. The system allows for student registration, face capture, and attendance tracking, providing a modern solution for attendance management.
即時人臉辨識(使用OpenCV與FaceNet)
A Streamlit web application for face recognition using a pre-trained YOLO model and the DeepFace library.
This node provides lip-sync capabilities in ComfyUI using ByteDance's LatentSync model. It allows you to synchronize video lips with audio input.
Python Real Time Face Detection application, using opencv, deepface
Introducing the faster and more optimized version of DeepFaceLab.
recops is a facial analysis framework, an AI forensic toolkit designed specifically for visual investigations and analysis workflows in OSINT research.
"This project uses the DeepFace library for facial recognition and OpenCV for face detection to identify the gender (male or female) in images. It scans a folder of images, detects faces, classifies gender, and saves the processed images with the detected gender label."
This project implements real-time facial emotion detection using the deepface library and OpenCV. It captures video from the webcam, detects faces, and predicts the emotions associated with each face. The emotion labels are displayed on the frames in real-time.
recognition of faces for the web
A multimodal face liveness detection module that can be used in the context of face anti-spoofing
Anonymization pipeline (faces, license plates detection & blurring) of video frames utilizing various deep learning models, part of GRUBLES project
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