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Update Notes

  • [2021.08.28] Refactor data processing pipeline and support multi-scale training (#311).

  • [2021.05.30] Release ncnn int8 models, and new pre-trained models with ShuffleNetV2-1.5x backbone. Much higher mAP but still realtime(26.8mAP 21.53ms).

  • [2021.03.12] Apply the Transformer encoder to NanoDet! Introducing NanoDet-t, which replaces the PAN in NanoDet-m with a TAN(Transformer Attention Net), gets 21.7 mAP(+1.1) on COCO val 2017. Check nanodet-t.yml for more details.

  • [2021.03.03] Update Nanodet-m-416 COCO pretrained model. COCO mAP(0.5:0.95)=23.5. Download in Model Zoo.

  • [2021.02.03] Support EfficientNet-Lite and Rep-VGG backbone. Please check the config folder. Download models in Model Zoo

  • [2021.01.10] NanoDet-g with lower memory access cost, which designed for edge NPU or GPU, is now available! Check config/nanodet-g.yml and download in Model Zoo.

  • [2020.12.19] MNN python and cpp demos are available.

  • [2020.12.05] Support voc .xml format dataset! Refer to config/nanodet_custom_xml_dataset.yml.

  • [2020.12.01] Great thanks to nihui, now you can try NanoDet running in web browser! 👉 https://nihui.github.io/ncnn-webassembly-nanodet/