After training a model using the ML Deformer, you can find a metadata.json file in the same folder as the trained model. This file contains useful information about the training process, which you can find outlined below.
| Field | Type | Description |
|---|---|---|
| version | Object (int, int) | Has "major" and "minor" components. Indicates which version of the metadata (and implicitly the ml deformer) this applies to. |
| startFrame | Integer | The start of training data frame range. |
| endFrame | Integer | The frame range of training data. |
| sampleCount | Integer | The number of training frames. |
| controlDefinitions | Array of Objects | List of controls used as inputs to the model. Each index represents a single float value. Includes the input plug (only the index is relevant) and the min and max values seen in the training set for this control. |
| deltaCount | Integer | Number of vertex deltas per frame in the export file. Recorded during export. Should match affectCount exactly. |
| exportDate | String | When the training data was exported. (Format: yyy-mm-dd hh:mm:ss (timezone)) |
| exportTime | Float | Time taken to export the data, in seconds. |
| exportFormat | String | File format the training data was saved as.
|
| affectCount | Integer | Number of vertices affected by this model. Should equal fullCount if operating on the full geometry. |
| fullCount | Integer | Total vertices on the deforming mesh. |
| affectMap | Array of integers | Array of vertex indices representing the vertices affected by the model. This uses Maya's vertex indices, and will be empty if working on the full mesh. |
| deltaUnits | String | The scene units in use when the training data was exported. Useful for conversions. |
| deltaMode | Integer | Integer value representing which delta mode was exported. Redundant with deltaExportType. |
| deltaExportType | String | String abbreviation of deltaMode. Values are "dos" for surface mode or "dbp" for offset.
Note: There are other potential values for the mlDeformer -vertexDeltas command, but only dos or dbp are used during export.
|
| smoothingIterations | Integer | Number of iterations of smoothing the base mesh undergoes before calculating or applying deltas. Also applies to exported vertex frames. |
| subsetState | String | Indicates whether the complete or partial geometry is deformed. |
| componentTagExpression | String | The component tag expression defining which vertices will be affected by the deformer. |
| geometry | String | Name of the geometry node in Maya. |
| lossMetric | String | Loss function used while training. Will always be "MSE" (Mean Squared Error). |
| trainingTime | Float | Time spent training the model, in seconds. |
| trainingDate | String | When the model was trained. (Format: yyy-mm-dd hh:mm:ss (timezone)) |
| finalTrainLoss | Float | Final training loss as measured by the loss metric. |
| bestTrainEpoch | Integer | The epoch with the lowest training loss. |
| minTrainLoss | Float | The lowest training loss (as it was in the bestTrainEpoch). |
| minTrainMAE | Float | Lowest training loss using Mean Absolute Error (MAE) loss calculation (measured in scene units). |
| finalValidationLoss | Float | Final validation loss as measured by the loss metric. |
| bestValidationEpoch | Integer | The epoch with the lowest validation loss. |
| minValidationLoss | Float | The lowest validation loss (as it was in the bestValidationEpoch). |
| minValidationMAE | Float | Lowest validation loss using Mean Absolute Error (MAE) loss calculation (measured in scene units). |
| learningRate | Float | Learning rate during training. |
| batchSize | Integer | Number of samples per training batch. |
| epochs | Integer | Total number of epochs to finish training. |
| userPrincipalShapes | Boolean | Indicates if training used principal shapes. The trained model's outputs will be shape weights, not deltas. |
| principaleShapeCount | Integer | Number of principal shapes trained on. |
| shapeConstructionOption | Integer | Indicates the option used for constructing the principal shapes.
|
| modelDefinition | Object | The model's hidden layers as defined by training parameters. This definition will have been parsed during training to define the actual pytorch model structure. |
| exportSurfaceInformation | Boolean | Whether the data includes extra surface information (i.e. vertex frames). |
| surfaceFrameMap | Array of integers | List of vertex indices with vertex frames included in the export data. This uses Maya's vertex indices, and is 10% of the mesh by default. |
| surfaceRepresentation | String | How the surface information has been exported. Indicates the format of vertex frames.
|
| surfaceFrameSize | Integer | How many values are associated with each vertex frame, depending on its representation. The value will be 9 or 6 depending on the surfaceRepresentation. |
Example of metadata.json structure
{
"version": {
"major": 1,
"minor": 0
},
"startFrame": 0,
"endFrame": 2000,
"sampleCount": 2001,
"controlDefinitions": [
{
"src_plug": "mlDeformer1.controlValues[0]",
"minimum": -99.99280023258999,
"maximum": 99.89342451625558
},
...
{
"src_plug": "mlDeformer1.controlValues[11]",
"minimum": -99.89837234610832,
"maximum": 99.97574443880183
}
],
"deltaCount": 342,
"exportDate": "2025-01-08 14:18:39 (UTC)",
"exportTime": 43.439516599988565,
"exportFormat": "shelf",
"affectCount": 342,
"fullCount": 342,
"affectMap": [],
"deltaUnits": "cm",
"deltaMode": 1,
"deltaExportType": "dos",
"smoothingIterations": 0,
"exportSurfaceInformation": true,
"surfaceFrameMap": [
0,
5,
11,
12,
23,
30,
55,
59,
84,
91,
96,
131,
158,
161,
177,
183,
185,
195,
197,
205,
207,
222,
236,
246,
257,
258,
262,
269,
286,
292,
295,
306,
313,
338
],
"surfaceRepresentation": "3x3",
"surfaceFrameCount": 34,
"surfaceFrameSize": 9,
"subsetState": "complete",
"componentTagExpression": "*",
"geometry": "pCylinderShape1",
"lossMetric": "MSE",
"trainingTime": 4.866239299997687,
"trainingDate": "2025-01-08 14:19:39 (UTC)",
"finalTrainLoss": 0.015372385734485256,
"bestTrainEpoch": 99,
"minTrainLoss": 0.015372385734485256,
"minTrainMAE": 0.058620557851261565,
"finalValidationLoss": 0.0242560015833793,
"bestValidationEpoch": 99,
"minValidationLoss": 0.0242560015833793,
"minValidationMAE": 0.07153895289743718,
"learningRate": 0.0005,
"batchSize": 128,
"epochs": 100,
"usesPrincipalShapes": false,
"principalShapeCount": 0,
"shapeConstructionOption": 0,
"modelDefinition": {
"version": 1.0,
"hidden_layers": [
{
"neurons": 512,
"activation": "LeakyReLU",
"dropout_ratio": 0.0
},
{
"neurons": 512,
"activation": "LeakyReLU",
"dropout_ratio": 0.0
}
]
}
}