1adrianb/face-alignment
Face Alignment
This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a facial landmark detector and reconstruction tool, utilizing deep learning to identify precise geometric points on human faces from image datasets.
The library allows for the selection of specific detection backends to balance accuracy and processing speed. It supports the integration of precomputed bounding box files, which enables the system to bypass the initial detection phase and proceed directly to landmark extraction.
The toolkit includes capabilities for batch image processing and hardware-accelerated inference to reduce coordinate prediction latency. It provides workflows for both two-dimensional image space and three-dimensional spatial coordinate regression.
Features
- Facial Landmark Detection - Identifies precise 2D and 3D coordinates of key facial features using deep learning models.
- Facial Landmark Analysis - Locates specific geometric points on a human face to enable alignment and expression analysis.
- 3D Spatial Mapping - Extracts three-dimensional coordinates of facial landmarks to create depth and structure models.
- Face Alignment - Provides a deep learning toolkit for detecting 2D and 3D facial landmark coordinates.
- Coordinate Regression - Predicts facial feature locations in both two-dimensional image space and three-dimensional spatial coordinates.
- Deep Learning Execution - Utilizes PyTorch tensor-based computational graphs to perform forward passes for facial feature regression.
- Precomputed Coordinate Integration - Allows loading external bounding box files to bypass the detection stage and proceed directly to landmark extraction.
- Bounding Box Integration - Integrates external facial bounding box files to trigger direct landmark extraction.
- Computer Vision Libraries - Offers a specialized set of tools for processing facial images and extracting spatial features.
- Batch Image Processing - Enables the analysis of all images within a directory to extract facial landmarks in a single execution.
- Hardware-Accelerated Inference - Supports routing model computations to GPUs to minimize the latency of coordinate predictions.
- PyTorch Computer Vision Pipelines - Uses PyTorch models to automate the detection and alignment of faces across image batches.
- Computer Vision - Library for 2D and 3D facial landmark detection.
- Computer Vision Models - Library for 2D and 3D face alignment.
- Face Alignment And Reconstruction - Framework for solving 2D and 3D facial alignment problems.
- Model Implementations - Face alignment implementation.
- Facial, Action and Pose Recognition - Listed in the “Facial, Action and Pose Recognition” section of the The Incredible Pytorch awesome list.
- Keypoint detection - Listed in the “Keypoint detection” section of the Ailia Models awesome list.
