pytorch-segmentation and semantic-segmentation
About pytorch-segmentation
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.
About semantic-segmentation
sithu31296/semantic-segmentation
SOTA Semantic Segmentation Models in PyTorch
This project helps experts in computer vision automatically identify and delineate specific objects or regions within images. You input an image, and it outputs a segmented image where different objects (like people, faces, or elements in a scene) are highlighted or outlined. It's designed for researchers and practitioners who need precise pixel-level classification in fields like scene understanding or medical imaging.
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