MNN
tinyengine
| MNN | tinyengine | |
|---|---|---|
| 3 | 3 | |
| 8,313 | 740 | |
| 0.9% | 3.1% | |
| 8.0 | 5.6 | |
| 11 days ago | about 1 month ago | |
| C++ | C | |
| - | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
MNN
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[D][R] Deploying deep models on memory constrained devices
However, I am looking on this subject through the problem of training/finetuning deep models on the edge devices, being increasingly available thing to do. Looking at tflite, alibaba's MNN, mit-han-lab's tinyengine etc..
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What’s New in TensorFlow 2.10?
There are a ton of mobile deployment options that support PyTorch+TF models. It's hard to argue TFLite is the best.
https://github.com/alibaba/MNN
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Newbie having error code of cannot build selected target abi x86 no suitable splits configured
I found a solution on GitHub check your app's build.gradle, defaultConfig section - you need to add x86 to your ndk abiFilters ndk.abiFilters 'armeabi-v7a','arm64-v8a', 'x86' GitHub Hope it will help. You have to find that file and edit it as given here
tinyengine
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[D] Run Pytorch model inference on Microcontroller
TinyEngine from MCUNet. Looks great, targeting ARM CM4.
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[D][R] Deploying deep models on memory constrained devices
However, I am looking on this subject through the problem of training/finetuning deep models on the edge devices, being increasingly available thing to do. Looking at tflite, alibaba's MNN, mit-han-lab's tinyengine etc..
- TinyEngine: High-performance neural network library for Microcontrollers
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
prnf - A lightweight tiny printf alternative. With some reasonable limitations, extensions, and alternative behaviour suited to microcontrollers.
TNN - 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.
nnom - A higher-level Neural Network library for microcontrollers.
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
ML-examples - Arm Machine Learning tutorials and examples
ai8x-synthesis - Quantization and Synthesis (Device Specific Code Generation) for ADI's MAX78000 and MAX78002 Edge AI Devices
oneflow - OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
EdgeML - This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
serving - A flexible, high-performance serving system for machine learning models
SLID-on-Microcontrollers - Speech Classification using a Convolutional Neural Network running on a Microcontroller