Hi All! First attempt at using a semantic segmentation model and getting ~10% accuracy (goes down with each epoch).
Public model with my data here:
https://www.kaggle.com/code/gtracer/segmentation-burger-and-hotdog
TLDR:
- Segmented 20 photos of burgers and hotdogs (10 each). Created a mask for each image and the codes are: void = 0, burger = 1, and hotdog = 2
- Uploaded the data and ran a unet_learner
Was following this tutorial https://walkwithfastai.com/Segmentation on segmentation from a fast.ai alumni except I need to do it with a custom dataset so I started testing on burger and hotdog photos.
I’m making a mistake somewhere (too little data, wrong pixel segmentation, error loss function etc.) but having trouble debugging the mistake.
Any help spotting the error / improving the model would be greatly appreciated!