QuarkDet lightweight object detection in PyTorch .Real-Time Object Detection on Mobile Devices.

手把手教你OpenVINO下部署NanoDet模型，intel i7-7700HQ CPU实测6ms一帧

nanodet int8 量化，实测推理2ms一帧！

🥭 移动端MNN部署学习笔记。支持Android与iOS。

🍉 移动端TNN部署学习笔记，支持Android与iOS。

用opencv部署nanodet目标检测，包含C++和Python两种版本程序的实现

Some Nanodet trained models

🍅🍅NanoDet、NanoDet-Plus with ONNXRuntime/MNN/TNN/NCNN C++. (https://github.com/DefTruth/lite.ai.toolkit)

This repo is implemented based on detectron2

🍅 Deploy ncnn on mobile phones. Support Android and iOS. 移动端ncnn部署，支持Android与iOS。

NanoDetのPythonでのONNX推論サンプル

NanoDetをGoogle Colaboratory上で訓練しONNX形式のファイルをエクスポートするサンプル(This is a sample to training NanoDet on Google Colaboratory and export a file in ONNX format)

Implemented the prediction inference process of the NANODET model in ONNX format and TFLite format

NanoDet: Tiny Object Detection for TFJS and NodeJS

Navigation software for autonomous robot. Real-time object detection using high-performance neural network inference computing framework. To communicate with microcontroller, text-based bluetooth communication. Progress of the roboter is shown on Website: We communicate with the server using websockets https://github.com/cyrillkuettel/rover/

Deploy nanodet, the super fast and lightweight object detection, in your web browser with ncnn and webassembly

docker images for training, mining and infer for ymir

Nanodet, NanodetPlus, Yolov5, Yolov6, Yolov7, MobileSSD etc. deployment with ncnn/dnn/mnn/SNPE/mace/Torch onto Android

本仓库在OpenVINO推理框架下部署Nanodet检测算法，并重写预处理和后处理部分，具有超高性能！让你在Intel CPU平台上的检测速度起飞！ 并基于NNCF和PPQ工具将模型量化(PTQ)至int8精度，推理速度更快！

awesome AI models with NCNN, and how they were converted ✨✨✨