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This project is an attendance system that uses face detection technology to track and record attendance. It is designed to provide a more efficient and accurate method of attendance tracking, reducing the need for manual input and minimizing errors.
A Gradio-based web application that detects whether an image is a deepfake. The application uses a pre-trained InceptionResnetV1 model from the facenet_pytorch library for face recognition, and pytorch-grad-cam for visual explainability.
Utilizing the DeepFace Library, informed by a dataset of 4M images across 4K identities curated by Facebook researchers, My 'Two Faces✌🏻' project gauges facial similarity with precision.
Generate thumbnails of detected faces in images using Python. This package leverages the MTCNN (Multi-Task Cascaded Convolutional Neural Network) for accurate face detection and OpenCV for image processing.