Classifies object into categories using one of the following models:
For more information on how to train a model see any the classification of nuts tutorials: Nut classification
Select the model created for the classification of the samples.
Which category to apply the segmentation.
Object average spectrum
Classifies the object by taking the average spectrum from all pixels included in the object.
Pixel class majority
Classifies the object by the majority of the pixels in the object.
Only applicable when Pixel class majority is selected
Decides the importance of the pixels for the classification using pixel class majority.
✅ Includes prediction of each pixel and visualization of the pixel prediction on the object.
⬜ Do not include the prediction or visualization
Set parent class for hierarchical model.
Show Train/Test column in table
Adds an additional column in table showing if the object was part of Train or Test set
✅ Add Train/Test column
⬜ Do not add Train/Test column