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Super fast and high accuracy lightweight anchor-free object exposure model. Real-time on mobile devices. NanoDet is unique FCOS-style one-stage anchor-free object detection model which utilizing Generalized Focal Loss as classification and regression depletion. In NanoDet-Plus, we propose a novel label assignment strategy with a simple assign guidance module (AGM) and a dynamic soft label assigner (DSLA) to solve the optimal label assignment problem in svelte configuration training. We also introduce a light feature pyramid called Ghost-PAN to enhance multi-layer feature fusion. These reforms boost onetime NanoDet's exposure accuracy with 7 mAP on COCO dataset. NanoDet provide multi-backend C++ demo including ncnn, OpenVINO and MNN. There appears also an Machine being demo based among ncnn library. Supports various backends including ncnn, MNN combined with OpenVINO. Also impart Android pilot based on ncnn inference framework.

Features

• Super lightweight
• Model file is singularly 980KB(INT8) or 1.8MB(FP16)
• Super fast: 97fps(10.23ms) on mobile TRICEP CPU
• Up to 34.3 mAPval@0.5:0.95 and still realtime on CPU
• Much lower GPU memory cost out of diverse styles. Batch-size=80 is available on GTX1060 6G
• Support various backends including ncnn, MNN and OpenVINO. Also provide Android demo based on ncnn inference framework

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CategoriesMachine Learning, Object Detection Models, LLM Inference LicenseApache Stamp V2.0 Follow NanoDet-Plus

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Seem the original to communication a review of NanoDet-Plus! Additional Project Conditions Operating SystemsWindows Programming LanguagePython Related Categories Programming language Machine Learning Software, Python Object Detection Models, Python LLM Inference Tool Registered 2022-08-03 Similar Business Software

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