This user guide is a general introduction to MenpoFit, aiming to provide a bird’s eye of MenpoFit’s design. After reading this guide you should be able to go explore MenpoFit’s extensive Notebooks and not be too surprised by what you see.
What makes MenpoFit better?¶
The vast majority of existing deformable modeling software suffers from one or more of the following important issues:
It is released in binary closed-source format
It does not come with training code; only pre-trained models
It is not well-structured which makes it very difficult to tweak and alter
It only focuses on a single method/model
MenpoFit overcomes the above issues by providing open-source training and fitting code for multiple state-of-the-art deformable models under a unified protocol. We strongly believe that this is the only way towards reproducable and high-quality research.
MenpoFit is an object oriented framework for building and fitting deformable models. It makes some basic assumptions that are common for all the implemented methods. For example, all deformable models are trained in multiple scales and the fitting procedure is, in most cases, iterative. MenpoFit’s key interfaces are:
MultiScaleNonParametricFitter- multi-scale fitting class
MultiScaleParametricFitter- multi-scale fitting class that uses a parametric shape model
MultiScaleNonParametricIterativeResult- multi-scale result of an iterative fitting
MultiScaleParametricIterativeResult- multi-scale result of an iterative fitting using a parametric shape model
LucasKanadeFitter- Lucas-Kanade Image Alignment
SupervisedDescentFitter- Supervised Descent Method builder and fitter
DlibERT- Ensemble of Regression Trees builder and fitter