snap-research/EfficientFormer
EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]
This project provides pre-trained image classification models optimized for speed and size on mobile devices. It takes an image as input and outputs a classification of what's in the image. This is ideal for mobile app developers or product managers creating features that require real-time image recognition on smartphones.
1,109 stars. No commits in the last 6 months.
Use this if you need to integrate fast, accurate image classification directly into a mobile application with minimal latency and a small model footprint.
Not ideal if you require the absolute highest classification accuracy at the expense of model size and inference speed on mobile hardware, or if your application primarily runs on powerful server-side GPUs.
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1,109
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Language
Python
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Last pushed
Aug 13, 2023
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