oskarnatan/semseg-bisaai
GPU-accelerated Semantic Image Segmentation with PyTorch
This project helps urban planners, smart city developers, or autonomous vehicle engineers categorize different elements within street-level images. You provide raw images of cityscapes, and the system outputs segmented images where each pixel is labeled by category, such as road, building, or pedestrian. This is ideal for those who need to understand and analyze urban environments visually.
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Use this if you need to precisely identify and map objects and areas within city street images, for tasks like urban analysis or training autonomous driving systems.
Not ideal if your primary need is object detection or image classification, rather than pixel-level categorization of every element in an image.
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Jupyter Notebook
License
MIT
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Last pushed
Sep 01, 2022
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