MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba. Full multimodal LLM Android App:[MNN-LLM-Android](./project/android/apps/MnnLlmApp/README.md)
💎1MB lightweight face detection model (1MB轻量级人脸检测模型)
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
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 …
🛠 A lite C++ toolkit of 100+ Awesome AI models, support ORT, MNN, NCNN, TNN and TensorRT. 🎉🎉
🍅🍅🍅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~
MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:
llm deploy project based mnn. This project has merged into MNN.
Sharpen your low-resolution pictures with the power of AI upscaling
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。
nndeploy is an end-to-end model inference and deployment framework. It aims to provide users with a powerful, easy-to-use, high-performance, and mainstream framework compatible model inference and deployment experience.一款端到端的模型推理和部署框架。它旨在为用户提供功能强大、简单易用、高性能且兼容主流框架的模型推理和部署体验。
A toolbox for deep learning model deployment using C++ YoloX | YoloV7 | YoloV8 | Gan | OCR | MobileVit | Scrfd | MobileSAM | StableDiffusion
an edge-real-time anchor-free object detector with decent performance
C++ Helper Class for Deep Learning Inference Frameworks: TensorFlow Lite, TensorRT, OpenCV, OpenVINO, ncnn, MNN, SNPE, Arm NN, NNabla, ONNX Runtime, LibTorch, TensorFlow
alibaba MNN, mobilenet classifier, centerface detecter, ultraface detecter, pfld landmarker and zqlandmarker, mobilefacenet
benchmark for embededded-ai deep learning inference engines, such as NCNN / TNN / MNN / TensorFlow Lite etc.
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
Raspberry Pi 4 Buster 64-bit OS with deep learning examples
Add a description, image, and links to the mnn topic page so that developers can more easily learn about it.
To associate your repository with the mnn topic, visit your repo's landing page and select "manage topics."