raoyongming/GFNet
[NeurIPS 2021] [T-PAMI] Global Filter Networks for Image Classification
This project offers a highly efficient way to classify images, helping you quickly sort and label large collections of photos. It takes raw image files as input and outputs classifications (e.g., 'cat', 'dog', 'car') for each image. This is ideal for researchers, data scientists, or anyone working with large image datasets who needs accurate and fast automated image tagging.
504 stars. No commits in the last 6 months.
Use this if you need to rapidly and accurately categorize images in vast datasets, especially when working with high-resolution images where speed and computational efficiency are critical.
Not ideal if your primary task is generating new images or performing complex, open-ended image generation tasks rather than classification.
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504
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45
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 12, 2023
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