yassouali/pytorch-segmentation
:art: Semantic segmentation models, datasets and losses implemented in PyTorch.
This project helps scientists and researchers in fields like medical imaging or autonomous driving to precisely outline objects within images. It takes raw images and their corresponding pixel-level annotations (telling the system what each pixel represents, e.g., 'tumor', 'road', 'sky') and trains models to automatically identify and highlight specific regions. The output is a highly accurate model capable of segmenting new, unseen images, delineating boundaries of objects with pixel-perfect precision.
1,814 stars. No commits in the last 6 months.
Use this if you need to train a robust image segmentation model from scratch or fine-tune an existing one, and require detailed control over models, datasets, and training parameters.
Not ideal if you are looking for a pre-trained, off-the-shelf solution for common objects without needing to train on custom datasets.
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Feb 23, 2025
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