cONNXr
onnx2c
cONNXr | onnx2c | |
---|---|---|
2 | 1 | |
175 | 158 | |
- | - | |
0.0 | 6.6 | |
6 months ago | 23 days ago | |
C | C | |
MIT License | 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.
cONNXr
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[D] Run Pytorch model inference on Microcontroller
cONNXr - framework with C99 inference engine. Also interesting and not very active.
- [D] Machine Learning Expertise Combined with Embedded Knowlege
onnx2c
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[D] Run Pytorch model inference on Microcontroller
onnx2c - onnx to c sourcecode converter. Looks interesting, but also not very active.
What are some alternatives?
nanopb-example - This is a simple project created to test the capabilities of Google's protobuf C implementation, nanopb.
deepC - vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers
CMSIS-NN - CMSIS-NN Library
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
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
MaximAI_Documentation - START HERE: Documentation for ADI's MAX78000 and MAX78002 Edge AI devices
nnom - A higher-level Neural Network library for microcontrollers.