CFU-Playground
Want a faster ML processor? Do it yourself! -- A framework for playing with custom opcodes to accelerate TensorFlow Lite for Microcontrollers (TFLM). . . . . . Online tutorial: https://google.github.io/CFU-Playground/ For reference docs, see the link below. (by google)
tensorflow-onnx
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX (by onnx)
| CFU-Playground | tensorflow-onnx | |
|---|---|---|
| 2 | 7 | |
| 442 | 2,218 | |
| -0.2% | 1.1% | |
| 4.9 | 7.1 | |
| 1 day ago | 14 days ago | |
| Verilog | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
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.
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.
CFU-Playground
Posts with mentions or reviews of CFU-Playground.
We have used some of these posts to build our list of alternatives
and similar projects.
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Hacker News top posts: Jan 11, 2022
CFU Playground: Full-Stack Open-Source Framework for TinyML Acceleration on FPGA\ (3 comments)
- CFU Playground: Full-Stack Open-Source Framework for TinyML Acceleration on FPGA
tensorflow-onnx
Posts with mentions or reviews of tensorflow-onnx.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-17.
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Operationalize TensorFlow Models With ML.NET
The easiest way to transform the downloaded TensorFlow model to an ONNX model is to use the tool tf2onnx from https://github.com/onnx/tensorflow-onnx
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Which models can be converted to ONNX?
But I found that there are limitation in practice. For instance, I found that the conversion of this model to ONNX fails when using tf2onnx.
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10$ Full Body Tracking! I'm proud to release ToucanTrack (in Beta!). Get decent FBT with the power of 2 PS3 Eye Cameras and AI!
They come in the form of tflite models, so I had to convert them to onnx. I used tf2onnx for converting the pose landmark model and tflite2tensorflow for converting the pose detection model. For improving performance, I had created a small script which modified the landmark models for supporting batch inference. This script is not included in the repository, but do tell me if you need it!
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Auto Annotation using ONNX and YOLOv7 model (Object Detection)
pb to ONNX Follow tensorflow-onnx:- https://github.com/onnx/tensorflow-onnx
- Can you inference a .tflite model file using Pytorch mobile?
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💊Your daily dose of machine learning : converting deep learning models to ONNX format
You can learn more about this tool on their github repo : https://github.com/onnx/tensorflow-onnx
What are some alternatives?
When comparing CFU-Playground and tensorflow-onnx you can also consider the following projects:
deepbacksub - Virtual Video Device for Background Replacement with Deep Semantic Segmentation
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.