Fine-Tune a Semantic Segmentation Model with a Custom Dataset

look, fine-tuning semantic segmentation models is just applying basic machine learning principles, but the real headache is the data. you can fine-tune anything, sure, but if your custom dataset is garbage, your model is garbage. we're spending all our time curating messy labels instead of debugging the model architecture.

the cost isn't the fine-tuning itself, it's the manual labor. getting high-quality, labeled data for complex segmentation is brutal. it’s not a magic solution; it’s just scaling the data collection problem. don't assume the pre-trained weights solve your data hygiene issues. it's just shifting the bottleneck.