Image segmenation transfer learning on facebook/maskformer-swin-large-ade with custom dataset
Hey,I’m trying to do transfer learning with the facebook/maskformer-swin-large-ade model on a custom dataset. I tried to train the model following this tutorial and using the suggested dataset:notebooks/semantic_segmentation.ipynb at main · huggingface/notebooks · GitHubSadly, I ended up getting multiple errors and couldn’t get the training to start. What steps do I have to take to train the selected model on the already existing dataset?After I succeed with the given dataset, which steps do I have to take to create my own one?The data consists of pictures in the size of 8192x7808 and only one class should be recognized.I already have the labeled data: the original images and the black and white images which mark the object positions.Thanks in advance!
2023-03-20T12:50:30Z
Hi,That notebook is meant for models supported by theAutoModelForSemanticSegmentationAPI, like SegFormer. These models predict a label for each pixel of an image (also called “per-pixel classification”).However, MaskFormer (and related models like Mask2Former and OneFormer) don’t use per-pixel classification to solve semantic segmentation, but rather adopt a “binary mask classification” paradigm. Hence we made different notebooks for those models, which you can find here:Transformers-Tutorials/MaskFormer at master · NielsRogge/Transformers-Tutorials · GitHub.To understand the difference between “per-pixel classification” and “binary mask classification”, I’d recommend checking out ourblog post.