adobe/antialiased-cnns
pip install antialiased-cnns to improve stability and accuracy
This tool helps machine learning engineers and researchers improve the reliability and accuracy of their image classification models. By applying an antialiasing technique during the downsampling stages of convolutional neural networks, it ensures that small shifts in an input image don't drastically change the model's prediction. You provide an existing image classification model, and the tool outputs an enhanced version that performs better and more consistently.
1,681 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are building or working with image classification models and need to improve their accuracy and make them more robust to slight variations or shifts in input images.
Not ideal if your project does not involve image data or if you are not using convolutional neural networks for your computer vision tasks.
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Apr 08, 2024
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