Red Analyze Tool Supervised Mode Tool Parameters
The VisionPro Deep Learning tool parameters adjust the how the neural network model is trained, and also how the tool processes statistical results.
For the majority of applications, the most common Tool Parameters to be adjusted are the following:
- Feature Size
- Training Set
- Perturbation
- Sampling Density
Restore Parameters
Restore Parameter button is designed for the easy turning back of tool parameter values to the values that you chose in the last training task. It remembers all values in Tool Parameter used in the last training session. So, if you changed any of its values and now want to revert this change, you can click it to roll back to the tool parameter values which are used in the last training. Note that it is disabled when the tool has never been trained or there were no changes from the initial set of tool parameter values.
The following steps explain how Restore Parameter works:
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Restore Parameter button is always disabled when the current tool was not trained.
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Once the current tool is trained, the checkpoint of parameter rollback is set to the values in Tool Parameter of the last training session. At this point, if you change any value in Tool Parameters, the button is enabled.
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Click Restore Parameter button and it reverts the changed value to the value of the checkpoint.
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If you train the current tool again, with some changes in Tool Parameters, then the checkpoint of parameter rollback is updated to the changed parameter values. Again, the button is disabled unless you make another change for the values in Tool Parameters.
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If you make another change and click Restore Parameter button again, it reverts the changed value into the value of the updated checkpoint.
Note that if you re-process a trained tool after changing the values in Processing Parameters, the checkpoint of parameter rollback is not updated, and thus Restore Parameter remains enabled. The checkpoint is updated only after the training of a tool is completed.
Disabled |
Enabled |
Irreversible parameters that changing these parameters will reset the tool
Network Model, Exclusive, Feature Size, Masking Mode, Color, Centered, Scaled, Scaled Mode (Uniform/Non-uniform), Legacy Mode, Oriented, Detail
Irreversible parameters that these parameters are not invertible in nature
Low Precision, Simple Regions
Other irreversible parameters
Training Set, Heatmap in Green Classify High Detail (This parameter does not affect the prediction performance)
Overlay parameter in Masking Mode in Blue Read