ML.NET
onnxruntime
ML.NET | onnxruntime | |
---|---|---|
17 | 58 | |
8,895 | 13,179 | |
0.6% | 3.4% | |
9.0 | 10.0 | |
3 days ago | 6 days ago | |
C# | C++ | |
MIT License | MIT License |
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.
ML.NET
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ML.net image classification, poor GPU accuracy
You can direct your question to https://github.com/dotnet/machinelearning/issues. Perhaps it is already documented.
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Building a File Analysis Dataset with Python
Here I'm analyzing all projects in the src and test directories of the ML.NET repository. I chose to include these as separate paths because they represent two different groupings of projects in this repository.
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Extracting git repository data with PyDriller
Important Note: looping over repository commits takes a long time for large repositories. It took 52 minutes to analyze the ML.NET repository this code example refers to, which had 2,681 commits at the time of analysis on February 25th, 2023.
- Can we please be allowed to do machine learning object detection model training locally?
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ML.NET: can Microsoft's machine learning be trusted?
We checked the ML.NET 1.7.1 version. The source code of this project's version is available on GitHub.
- Stable Diffusion converted to ONNX (Demo usage, optimized to CPU)
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Why is there a lack of cool repos?
machine learning? https://github.com/dotnet/machinelearning
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what is the future of ML.NET?
You can follow some of our plans by taking a look at our roadmap which we'll be updating shortly to more accurately reflect the areas we're investing in.
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Does anyone actually use ML.NET?
Re: ONNX, if you run into similar issues in the future, feel free to reach out in our GitHub repo or the ONNX Runtime repo and we'd be happy to help!
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Requesting Senior Project Ideas
Good clarification, I think using something like ML.NET could be cool but I have some experience with Blazor that might be fun to use as well, I think generally performance monitoring or optimizing systems seems interesting to me, and I'm really open to other ideas as well. Let me know if any of that helps narrow my question down!
onnxruntime
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SamGIS - Segment Anything applied to GIS
Starting from version 1.5.1 the backend integrates changes borrowed from sam_onnx_full_export, to support OnnxRuntime 1.17.x and later versions. Please note that on MacOS directly running the project from the command line suffers from memory leaks, making inference operations slower than normal. It's best therefore running the project inside a docker container, unless in case of development or debugging activities.
- SamGIS - Segment Anything adattato al GIS
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Giving Odin Intelligence
I've found a suitable for my idea ONNX example. I'm going to use this example as a strong foundation for the project. But to make things more interesting I'll add just a few enhancements:
- New exponent functions that make SiLU and SoftMax 2x faster, at full acc
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Machine Learning with PHP
ONNX Runtime: ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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AI Inference now available in Supabase Edge Functions
Embedding generation uses the ONNX runtime under the hood. This is a cross-platform inferencing library that supports multiple execution providers from CPU to specialized GPUs.
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Deep Learning in JavaScript
tfjs is dead, looking at the commit history. The standard now is to convert PyTorch to onnx, then use onnxruntime (https://github.com/microsoft/onnxruntime/tree/main/js/web) to run the model on the browsdr.
- FLaNK Stack 05 Feb 2024
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Vcc – The Vulkan Clang Compiler
- slang[2] has the potential, but the meta programming part is not as strong as C++, existing libraries cannot be used.
The above conclusion is drawn from my work https://github.com/microsoft/onnxruntime/tree/dev/opencl, purely nightmare to work with thoes drivers and jit compilers. Hopefully Vcc can take compute shader more seriously.
[1]: https://www.circle-lang.org/
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Oracle-samples/sd4j: Stable Diffusion pipeline in Java using ONNX Runtime
I did. It depends what you want, for an overview of how ONNX Runtime works then Microsoft have a bunch of things on https://onnxruntime.ai, but the Java content is a bit lacking on there as I've not had time to write much. Eventually I'll probably write something similar to the C# SD tutorial they have on there but for the Java API.
For writing ONNX models from Java we added an ONNX export system to Tribuo in 2022 which can be used by anything on the JVM to export ONNX models in an easier way than writing a protobuf directly. Tribuo doesn't have full coverage of the ONNX spec, but we're happy to accept PRs to expand it, otherwise it'll fill out as we need it.
What are some alternatives?
TensorFlow.NET - .NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.
onnx - Open standard for machine learning interoperability
Accord.NET
onnx-tensorrt - ONNX-TensorRT: TensorRT backend for ONNX
FaceRecognitionDotNet - The world's simplest facial recognition api for .NET on Windows, MacOS and Linux
onnx-simplifier - Simplify your onnx model
OpenCvSharp - OpenCV wrapper for .NET
ONNX-YOLOv7-Object-Detection - Python scripts performing object detection using the YOLOv7 model in ONNX.
Catalyst - 🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
onnx-tensorflow - Tensorflow Backend for ONNX
Deedle - Easy to use .NET library for data and time series manipulation and for scientific programming
MLflow - Open source platform for the machine learning lifecycle