Topic: mnn Goto Github
Some thing interesting about mnn
Some thing interesting about mnn
mnn,A tensorflow implement mobilenetv3 centernet, which can be easily deployeed on android(MNN) and ios(CoreML).
User: 610265158
mnn,benchmark for embededded-ai deep learning inference engines, such as NCNN / TNN / MNN / TensorFlow Lite etc.
Organization: ai-performance
Home Page: https://www.ai-performance.com
mnn,Facial Landmark Detection based on PyTorch
User: ainrichman
mnn,MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba
Organization: alibaba
Home Page: http://www.mnn.zone/
mnn,视觉训练框架(简单 / 模块化 / 高扩展 / 分布式 / 自动剪枝)
User: bobo0810
Home Page: https://github.com/bobo0810/Classification/wiki
mnn,🛠 A lite C++ toolkit of awesome AI models, support ONNXRuntime, MNN, TNN, NCNN and TensorRT.
User: deftruth
Home Page: https://github.com/DefTruth/lite.ai.toolkit
mnn,🍅MGMatting with MNN/TNN/ONNXRuntime C++, GPU/CPU, support dynamic shape. (https://github.com/DefTruth/lite.ai.toolkit)
User: deftruth
mnn,🍅🍅NanoDet、NanoDet-Plus with ONNXRuntime/MNN/TNN/NCNN C++. (https://github.com/DefTruth/lite.ai.toolkit)
User: deftruth
mnn,☕️ A vscode extension for netron, support *.pdmodel, *.nb, *.onnx, *.pb, *.h5, *.tflite, *.pth, *.pt, *.mnn, *.param, etc.
User: deftruth
Home Page: https://marketplace.visualstudio.com/items?itemName=DefTruth.netron-vscode-extension
mnn,🔥Robust Video Matting C++ inference toolkit with ONNXRuntime、MNN、NCNN and TNN, via lite.ai.toolkit.
User: deftruth
mnn,🍅🍅 Super fast accurate face detector ! SCRFD(CVPR 2021) with MNN/TNN/NCNN/ONNXRuntime C++. (https://github.com/DefTruth/lite.ai.toolkit)
User: deftruth
mnn, 🚀🚀🌟 YOLOP with ONNXRuntime C++/MNN/TNN/NCNN (https://github.com/DefTruth/lite.ai.toolkit)
User: deftruth
mnn,AoE (AI on Edge,终端智能,边缘计算) 是一个终端侧AI集成运行时环境 (IRE),帮助开发者提升效率。
Organization: didi
Home Page: https://didi.github.io/AoE
mnn,Real time portrait matting on mobile phone using MNN inference engine.
User: digital-nomad-cheng
mnn,RetinaNet face detection model inference on edge/mobile device utilizing MNN framework.
User: digital-nomad-cheng
mnn,MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:
User: dog-qiuqiu
mnn,Harmony framework for connecting scRNA-seq data from discrete time points
Organization: dpeerlab
mnn,C++ Helper Class for Deep Learning Inference Frameworks: TensorFlow Lite, TensorRT, OpenCV, OpenVINO, ncnn, MNN, SNPE, Arm NN, NNabla, ONNX Runtime, LibTorch, TensorFlow
User: iwatake2222
mnn,Sample projects for InferenceHelper, a Helper Class for Deep Learning Inference Frameworks: TensorFlow Lite, TensorRT, OpenCV, ncnn, MNN, SNPE, Arm NN, NNabla, ONNX Runtime, LibTorch, TensorFlow
User: iwatake2222
mnn,Sample projects to use MNN. PoseNet, SemanticSegmentation, etc.
User: iwatake2222
mnn,Android face detection 30+ FPS, pretrained weight 1MB.
User: jackweiwang
mnn, 💎1MB lightweight face detection model (1MB轻量级人脸检测模型)
User: linzaer
mnn,an edge-real-time anchor-free object detector with decent performance
User: lsh9832
mnn,Sharpen your low-resolution pictures with the power of AI upscaling
User: lucchetto
mnn,Lane detection model for mobile device via MNN project
User: maybeshewill-cv
mnn,mediapipe-hand,mediapipe-body,mediapipe-face, mediapipe-embedding, mediapipe-classifier and so on.MNN inference
User: mirroryuchen
mnn,alibaba MNN, mobilenet classifier, centerface detecter, ultraface detecter, pfld landmarker and zqlandmarker, mobilefacenet
User: mirroryuchen
mnn,nndeploy是一款模型端到端部署框架。以多端推理以及基于有向无环图模型部署为基础,致力为用户提供跨平台、简单易用、高性能的模型部署体验。
Organization: nndeploy
Home Page: https://nndeploy-zh.readthedocs.io/zh/latest/
mnn,🍅🍅🍅YOLOv5-Lite: Evolved from yolov5 and the size of model is only 900+kb (int8) and 1.7M (fp16). Reach 15 FPS on the Raspberry Pi 4B~
User: ppogg
mnn,Jetson Nano image with deep learning frameworks
User: qengineering
Home Page: https://qengineering.eu/install-tensorflow-2.4.0-on-jetson-nano.html
mnn,Machine vision apps
User: qengineering
Home Page: https://qengineering.eu/
mnn,Raspberry Pi 4 Bullseye 64-bit OS with deep learning examples
User: qengineering
Home Page: https://qengineering.eu/deep-learning-examples-on-raspberry-32-64-os.html
mnn,Raspberry Pi 4 Buster 64-bit OS with deep learning examples
User: qengineering
Home Page: https://qengineering.eu/deep-learning-examples-on-raspberry-32-64-os.html
mnn,NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
User: rangilyu
mnn,A toolbox for deep learning model deployment using C++ YoloX | YoloV7 | YoloV8 | Gan | OCR | MobileVit | Scrfd | MobileSAM | StableDiffusion
User: talkuhulk
Home Page: http://www.hulk.show/aidb-webassembly-demo/
mnn,Imported from https://gitee.com/techshoww/mnn-yolov5.
User: techshoww
mnn,TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
Organization: tencent
mnn,ChineseOcr Lite Mnn,超轻量级中文OCR PC Demo,使用MNN推理
User: thomaszheng
mnn,llm deploy project based mnn.
User: wangzhaode
mnn,Deploy deep learning model on difference hardware and framework. (TensorRT/ONNX/MNN/RKNN)
User: xiaochus
mnn,在Android使用深度学习模型实现图像识别,本项目提供了多种使用方式,使用到的框架如下:Tensorflow Lite、Paddle Lite、MNN、TNN
User: yeyupiaoling
mnn,A curated list of awesome inference deployment framework of artificial intelligence (AI) models. OpenVINO, TensorRT, MediaPipe, TensorFlow Lite, TensorFlow Serving, ONNX Runtime, LibTorch, NCNN, TNN, MNN, TVM, MACE, Paddle Lite, MegEngine Lite, OpenPPL, Bolt, ExecuTorch.
User: yulv-git
mnn,fast deployment for yolo detectors
User: zhoujiahuan
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