Training with half an image produces different results than with a selection of that same image

There are two ways to use only part of a folio image in Pixel: either you cut the image beforehand and give Pixel the pre-cut image, or you give Pixel the whole image and select only a part of it to be submitted back to rodan. I had a theory that these two processes produced different results; I went out to test that theory and have emerged even more bamboozled than before! Oh well. Here are the results of my test:

I first did a Pixel run using a cropped image of only the two lower staves of folio 288. I then did a Pixel run using the full image of 288, but selected the exact same region as the cropped image to submit to rodan. I then tested the models produced by each Pixel run on both the full image and the cropped one. In both cases, the result of each model was the same for both images.

- The cropped image models produced perfect layers.
- The full image models produced an impeccable layer 2 (staff lines), but then put all of the text (should be layer 3) in layer 1 with the neumes. Layer 3 was completely empty. (Hence the bamboozlement)

Important point: I used the Salzinnes models to separate the layers in all four Pixel runs. They do fairly well! However, the Salzinnes models do not have a layer 3; instead, the text is included in the background layer. So maybe this affected the results? But why would the models then put the text in layer 1, instead of in the background? And why did it only happen in one of the two cases? Help.

These are the cropped image models:
[Background Model Salzinnes model 4of4.hdf5.zip](https://github.com/user-attachments/files/16894012/Background.Model.Salzinnes.model.4of4.hdf5.zip)
[Model 1 Salzinnes model 4of4.hdf5.zip](https://github.com/user-attachments/files/16894013/Model.1.Salzinnes.model.4of4.hdf5.zip)
[Model 2 Salzinnes model 4of4.hdf5.zip](https://github.com/user-attachments/files/16894014/Model.2.Salzinnes.model.4of4.hdf5.zip)
[Model 3 Salzinnes model 4of4.hdf5.zip](https://github.com/user-attachments/files/16894017/Model.3.Salzinnes.model.4of4.hdf5.zip)

And these are the full image models:
[Background Model 288 w_ Salzinnes models.hdf5.zip](https://github.com/user-attachments/files/16894035/Background.Model.288.w_.Salzinnes.models.hdf5.zip)
[Model 1 288 w_ Salzinnes models.hdf5.zip](https://github.com/user-attachments/files/16894036/Model.1.288.w_.Salzinnes.models.hdf5.zip)
[Model 2 288 w_ Salzinnes models.hdf5.zip](https://github.com/user-attachments/files/16894038/Model.2.288.w_.Salzinnes.models.hdf5.zip)
[Model 3 288 w_ Salzinnes models.hdf5.zip](https://github.com/user-attachments/files/16894040/Model.3.288.w_.Salzinnes.models.hdf5.zip)