: A highly interactive notebook using the Oxford-IIIT Pet Dataset. It demonstrates how to use the U-Net architecture to classify every pixel into categories like "pet," "border," or "surrounding".
: This comprehensive guide covers building and training a segmentation model from scratch. It focuses on the architectural details of U-Net and includes a walkthrough for creating custom PyTorch datasets. image-segmentation-jupyter-notebook
: Best for those with GPU access, this article uses the NVIDIA NGC catalog to provide optimized containers and pretrained models. It is particularly useful for industrial tasks like identifying defective parts on assembly lines. : A highly interactive notebook using the Oxford-IIIT
: A highly interactive notebook using the Oxford-IIIT Pet Dataset. It demonstrates how to use the U-Net architecture to classify every pixel into categories like "pet," "border," or "surrounding".
: This comprehensive guide covers building and training a segmentation model from scratch. It focuses on the architectural details of U-Net and includes a walkthrough for creating custom PyTorch datasets.
: Best for those with GPU access, this article uses the NVIDIA NGC catalog to provide optimized containers and pretrained models. It is particularly useful for industrial tasks like identifying defective parts on assembly lines.