Hey. I’m doing binary segmentation using Mask2FormerForUniversalSegmentation.from_pretrained and Mask2FormerImageProcessor. I’m following this tutorial Transformers-Tutorials/MaskFormer/Fine-tuning/Fine_tuning_MaskFormerForInstanceSegmentation_on_semantic_sidewalk.ipynb at master · NielsRogge/Transformers-Tutorials · GitHub
My custom dataset contains a single class. I’m not quite sure if Mask2Former supports binary segmentation or should I treat this task as a 2-class segmentation, considering 0-background and 1-myClass.
I have tried both cases but I’m struggling with the arguments ignore_index and reduce_labels.
The model does not learn and the IoU is around 0.2 for both classes (background and myClass) along all epochs.
I’m stuck in this point, any idea?