cONNXr VS nn4mc_cpp

Compare cONNXr vs nn4mc_cpp and see what are their differences.

cONNXr

Pure C ONNX runtime with zero dependancies for embedded devices (by alrevuelta)

nn4mc_cpp

Neural Networks for Microcontrollers (by correlllab)
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cONNXr nn4mc_cpp
2 1
175 28
- -
0.0 1.8
6 months ago about 2 years ago
C C++
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

cONNXr

Posts with mentions or reviews of cONNXr. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-11-14.

nn4mc_cpp

Posts with mentions or reviews of nn4mc_cpp. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-05.

What are some alternatives?

When comparing cONNXr and nn4mc_cpp you can also consider the following projects:

nanopb-example - This is a simple project created to test the capabilities of Google's protobuf C implementation, nanopb.

pico-cnn - Lightweight C implementation of CNNs for Embedded Systems

CMSIS-NN - CMSIS-NN Library

ai8x-synthesis - Quantization and Synthesis (Device Specific Code Generation) for ADI's MAX78000 and MAX78002 Edge AI Devices

deepC - vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers

MaximAI_Documentation - START HERE: Documentation for ADI's MAX78000 and MAX78002 Edge AI devices

ML-examples - Arm Machine Learning tutorials and examples

nnom - A higher-level Neural Network library for microcontrollers.

tinyengine - [NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory

TinyMaix - TinyMaix is a tiny inference library for microcontrollers (TinyML).

onnx2c - Open Neural Network Exchange to C compiler.