deepinsight/insightface

InsightFace is an open-source Python toolkit for analyzing faces in images and video using deep learning. "Deep learning" here means AI trained on large datasets to recognize patterns. The toolkit covers several face-related tasks: detecting where faces appear in an image, recognizing whose face it is (face recognition), aligning facial landmarks (eyes, nose, mouth positions), estimating age, and swapping faces between images or video frames. The project supports both 2D and 3D face analysis. "2D" means working with standard photos, while "3D" refers to reconstructing the shape and depth of a face from a flat image, useful in more advanced applications like realistic face rendering. At its core, InsightFace provides pre-trained AI models and the code to use them. One of the well-known methods it implements is ArcFace, a widely-cited approach to face recognition that appeared in the CVPR 2019 research conference. It also includes face detection models, face swap models, and tools for training your own face recognition systems on custom data. The Python package lets you load an image and run detection, recognition, and alignment in just a few lines of code. The underlying deep learning framework is PyTorch (version 1.6+) or MXNet, and the library requires Python 3. License terms: the code is MIT-licensed, but the pre-trained models are available for non-commercial research purposes only, and commercial use requires a separate agreement. InsightFace is relevant for researchers building face-based AI systems, or developers adding face recognition, detection, or face-swap features to their applications. The full README is longer than what was provided.