Hi,

Thanks to your hard work, I’m honored to be able to start segmentation so easily. As part of my initial learning, I went through the MMSegmentation tutorial to fine-tune the SegFormer model for my specific task, and I encountered a few questions.

First, I have an open dataset where each sample consists of a pair of images: a regular image and its corresponding segmentation mask. However, I do not have any information about the color values or the number of classes in the dataset—I only have the image pairs. Given this situation, how can I properly prepare this dataset for training? I attempted to create a custom dataset class, but I’m unsure how to define the label and palette information. How should I handle this?

Second, I have a question about the .pth files saved during training. As shown in the attached image, I monitored a full training cycle without making any specific changes to the configuration. I noticed that the .pth model files increase in size as the iterations progress. Generally, model files of the same architecture should have similar sizes, so why is this happening?

Image

If you need any additional details to answer my questions, please feel free to ask! I’ll be happy to share everything I’ve tried so far.

Thanks! 😊