nanopb-example VS cONNXr

Compare nanopb-example vs cONNXr and see what are their differences.

nanopb-example

This is a simple project created to test the capabilities of Google's protobuf C implementation, nanopb. (by TSMotter)
Protobuf protocol-buffers nanopb Example
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cONNXr

Pure C ONNX runtime with zero dependancies for embedded devices (by alrevuelta)
Onnx Machine Learning ai-framework protocol-buffers embedded-devices
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nanopb-example cONNXr
1 2
1 175
- -
2.2 0.0
over 2 years ago 6 months ago
C C
- MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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nanopb-example

Posts with mentions or reviews of nanopb-example. We have used some of these posts to build our list of alternatives and similar projects.

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.

What are some alternatives?

When comparing nanopb-example and cONNXr you can also consider the following projects:

stm32-bootloader - Customizable Bootloader for STM32 microcontrollers. This example demonstrates how to perform in-application-programming of a firmware located on an external SD card with FAT32 file system.

CMSIS-NN - CMSIS-NN Library

Protobuf - Protocol Buffers - Google's data interchange format

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

nanopb - Protocol Buffers with small code size

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

protobuf - Protocol Buffers - Google's data interchange format [Moved to: https://github.com/protocolbuffers/protobuf]

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).

nanopb-example vs stm32-bootloader cONNXr vs CMSIS-NN nanopb-example vs Protobuf cONNXr vs ai8x-synthesis nanopb-example vs nanopb cONNXr vs deepC nanopb-example vs protobuf cONNXr vs MaximAI_Documentation cONNXr vs ML-examples cONNXr vs nnom cONNXr vs tinyengine cONNXr vs TinyMaix