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YOLOv6 2.0

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@Chilicyy Chilicyy released this 05 Sep 10:37
· 317 commits to main since this release

v2.0 release

YOLOv6 has a series of models for various industrial scenarios, including nano/tiny/s/m/l, which the architectures vary considering the model size for better accuracy-speed trade-off. And some Bag-of-freebies methods are introduced to further improve the performance, such as self-distillation and more training epochs. For industrial deployment, we adopt QAT with channel-wise distillation and graph optimization to pursue extreme performance.

New Features

  • Release M/L models and update N/T/S models with enhanced performance.⭐️ Benchmark
  • 2x faster training time.
  • Fix the degration of performance when evaluating on 640x640 inputs.
  • Customized quantization methods. 🚀 Quantization Tutorial