pytorch-semseg and Fast-SCNN-pytorch
The architectures implemented in the first tool could be trained with the fast semantic segmentation network implemented in the second tool, making them complements.
About pytorch-semseg
meetps/pytorch-semseg
Semantic Segmentation Architectures Implemented in PyTorch
This project helps computer vision practitioners analyze images by automatically segmenting them. You provide an image, and it outputs a segmented image where each pixel is labeled with its corresponding object class (e.g., road, car, building). It's designed for researchers and engineers working with visual data who need to classify every pixel in an image.
About Fast-SCNN-pytorch
Tramac/Fast-SCNN-pytorch
A PyTorch Implementation of Fast-SCNN: Fast Semantic Segmentation Network
This tool helps researchers and engineers quickly identify and outline distinct objects within images, like roads, buildings, and vehicles in urban scenes. You input a raw image, and it outputs a segmented image where each object type is highlighted with a different color. This is ideal for anyone working with computer vision applications requiring real-time scene understanding.
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