ML Deformer attributes

This topic covers the settings in the ML Deformer Attribute Editor tab.

For steps on how to use the ML Deformer, see Create an ML Deformer and Create an ML Deformer using separate Target geometry.

In the Animation (F4), Modeling (F2), and Rigging (F3) menu sets: Deform > ML Deformer

The ML Deformer tab in the Attribute Editor

Tip: You can test and experiment with ML Deformer sample files in the Content Browser (Windows > Content Browser > Examples > Animation > MLDeformer).

Sample ML Deformer animation in the Content Browser

ML Deformer Attributes

ML Model Location

Path to the folder containing trained models.

Target Morph

Toggle visualization of the Target deformation (the "goal" for the ML Deformer to approximate.)

Typically, when you are finished animating your scene, you will turn on Target Morph and set the Envelope to 1.0 to reactivate the original high quality deformation for final renders.

Target Morph Envelope

Note: This envelope slider is active only if you turn on the Target Morph option.

Lets you adjust the morph (in %) between the trained approximation and the Target.

Control Values

Lets you Select, Create, or Assign a Control Collector.

You can also click Select Control Collector

to highlight the collector in the Node Graph. A Control Collector specifies which inputs are passed into the ML Model. See the Control Collector attributes.

ML Deformer Attributes Table

Index

The placement in the array.

ML Model

Right-click on a cell to select the Trained Model to use. The ML Model contextual menu appears:

ML Model contextual menu
Option	Function
Select Model	Lets you choose the ML model to apply to the specified geometry.
Enable Model/Disable Model	Turns the deformation on the Source model on or off. This is the same as activating or disabling the Enabled button in the ML Deformer Attributes list.
Reload Model	Reloads the ML model with the latest changes.
Export Training Data...	Opens the ML Deformer Export Training Data window, where you can export the sample poses that will be used to train the model.
Train Model...	Opens the ML Deformer Training Settings where you can configure the training settings and start the training of the model.
View Training Results...	Opens the Training Results window to let you evaluate the effectiveness of the most recent training, including the error rates and how they differ between the Training and Validation results. A large difference between the Training and Validation results could be an indication of overfitting of the data. See the explanation of Overfitting in the ML Training Results window.
Open Training Job Monitor...	Opens the ML Training Job Monitor where you can view the progress of the training process.

Enabled

Toggles the ML Deformer approximation on or off.

Target Geometry

Right-click a cell to select the deformed geometry the ML model should approximate. The Target Geometry contextual menu appears:

Option	Function
Select Target Geometry	Highlights the object currently assigned as the Target geometry, or the complex deformation being approximated, in the Viewport, Outliner, and Node Editor.
Select Output Geometry	Highlights the object currently assigned as the Output, or the geometry that is being deformed by the ML Deformer, in the Viewport, Outliner, and Node Editor. \
Replace Target with Selected	Assigns the currently selected object as the Target, that is, the geometry that the model is going to approximate.
Create Target for Deformers Post ML Deformer	Creates a Target mesh based on the deformers that follow ML deformer in the deformation stack and lets you approximate other deformers in the stack without having to set up the Target manually.
Disconnect Target	Lets you unassign the object currently assigned as the Target.

Geometry

Right-click a cell to select the base geometry. The base geometry defines what vertices should be deformed by the ML Deformer.

Pose Generation

Lets you create a separate Control Collector for sample generation. See Control Collector attributes for more about controls settings.

The ML Deformer can use poses from:

Preexisting animation, for example, motion capture.
Manually created animation, for example, keyframe animation.
Randomly-generated for example, pose generation.

Pose Generator: Lets you create a separate Control Collector for sample generation. This allows different controls to be used to generate the sample poses the model will be trained on, versus the controls that drive the model itself.
Note: See the Pose Generation options in the Control Collector topic.; If your control collector uses Matrix controls, Pose generation requires a second control collector to connect the Scalar values that produce the matrix, or alternate Scalar values tied to Animator controls.; Often, the controls on a rig that are intended to be used by the animator to animate should be used to generate poses, whereas joint matrices are more commonly used as the Driver controls. See Control Collector.; Select Control Collector to highlight the collector in the Node Editor.