TNN
MNN
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| TNN | MNN | |
|---|---|---|
| 1 | 3 | |
| 4,281 | 8,293 | |
| 1.1% | 1.3% | |
| 2.5 | 8.1 | |
| 5 days ago | 3 days ago | |
| C++ | C++ | |
| GNU General Public License v3.0 or later | - |
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.
TNN
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
What are some alternatives?
Stable-Diffusion-NCNN - Stable Diffusion in NCNN with c++, supported txt2img and img2img
tensorflow - An Open Source Machine Learning Framework for Everyone
libfacedetection - An open source library for face detection in images. The face detection speed can reach 1000FPS.
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
EAST - A tensorflow implementation of EAST text detector
ML-examples - Arm Machine Learning tutorials and examples
FastDeploy - ⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.
oneflow - OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
dlstreamer - This repository is a home to Intel® Deep Learning Streamer (Intel® DL Streamer) Pipeline Framework. Pipeline Framework is a streaming media analytics framework, based on GStreamer* multimedia framework, for creating complex media analytics pipelines.
serving - A flexible, high-performance serving system for machine learning models
OpenMLDB - OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.