16.3 u2net demo
20211015 The pre-built demonstration highlights the capabilities of the package. Several images are put through the pre-built cutout model to deliver the cutout.
ml demo u2net
===== u2net ===== U2Net is a Python library for static image background removal (cutout). This MLHub package is based on u2net as backbone network. The pretrained model for u2net will be downloaded as required. See https://arxiv.org/pdf/2005.09007.pdf for a paper describing the pre-built model and https://github.com/xuebinqin/U-2-Net for details. For this demo we will randomly choose an image from which to generate a cutout and the display the original and the cutout. The first two examples illustrate the default cutout and the third utilises alpha matting to obtain the cutout. Press Enter to continue: ================ Cutout Example 1 ================ Press Enter to perform basic cutout on animal-2.jpg: Downloading u2net.pth Downloading u2net.pth to model: 168M/168M [00:25, 6.46MiB/s] Close the graphic window using Ctrl-W. Press Enter to continue:
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