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Top 23 Onnx Open-Source Projects
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
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YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
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SaaSHub
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burn
Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
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MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
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silero-models
Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
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PINTO_model_zoo
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
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yolov7_d2
🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
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3DDFA_V2
The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.
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FastDeploy
⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.
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X-AnyLabeling
Effortless data labeling with AI support from Segment Anything and other awesome models.
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optimum
🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools
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SaaSHub
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Ref https://www.youtube.com/watch?v=0GwnxFNfZhM https://github.com/ultralytics/yolov5 https://dev.to/gfstealer666/kaaraich-yolo-alkrithuemainkaartrwcchcchabwatthu-object-detection-3lef https://www.kaggle.com/datasets/devdgohil/the-oxfordiiit-pet-dataset/data
Project mention: What's the best PyTorch model visualization tool? | news.ycombinator.com | 2024-04-28Netron seems to be the best that I've seen so far. https://github.com/lutzroeder/netron
Project mention: AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source | news.ycombinator.com | 2024-02-12ncnn uses Vulkan for GPU acceleration, I've seen it used in a few projects to get AMD hardware support.
https://github.com/Tencent/ncnn
ONNX Runtime: ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Project mention: Search for anything ==> Immich fails to download textual.onnx | /r/immich | 2023-09-15
Project mention: AMD Accelerates AI Adoption on Windows 11 With New Developer Tools for Ryzen AI | /r/AMD_Stock | 2023-05-23Uh, maybe they didn't feel the need to look. I already pointed you to the ONNX project. Here are some ONNX-based. These are just the ones being shared with the community. The limit of AMD's responsibility is writing the low-level libraries to support ONNX.
Project mention: 3 years of fulltime Rust game development, and why we're leaving Rust behind | news.ycombinator.com | 2024-04-26You can use libtorch directly via `tch-rs`, and at present I'm porting over to Burn (see https://burn.dev) which appears incredibly promising. My impression is it's in a good place, if of course not close to the ecosystem of Python/C++. At very least I've gotten my nn models training and running without too much difficulty. (I'm moving to Burn for the thread safety - their `Tensor` impl is `Sync` - libtorch doesn't have such a guarantee.)
Burn has Candle as one of its backends, which I understand is also quite popular.
Project mention: Weird A.I. Yankovic, a cursed deep dive into the world of voice cloning | news.ycombinator.com | 2023-10-02I doubt it's currently actually "the best open source text to speech", but the answer I came up with when throwing a couple of hours at the problem some months ago was "Silero" [0, 1].
Following the "standalone" guide [2], it was pretty trivial to make the model render my sample text in about 100 English "voices" (many of which were similar to each other, and in varying quality). Sampling those, I got about 10 that were pretty "good". And maybe 6 that were the "best ones" (pretty natural, not annoying to listen to).
IIRC the license was free for noncommercial use only. I'm not sure exactly "how open source" they are, but it was simple to install the dependencies and write the basic Python to try it out; I had to write a for loop to try all the voices like I wanted. I ended using something else for the project for other reasons, but this could still be fairly good backup option for some use cases IMO.
[0] https://github.com/snakers4/silero-models#text-to-speech
Project mention: Fast Llama 2 on CPUs with Sparse Fine-Tuning and DeepSparse | news.ycombinator.com | 2023-11-23Interesting company. Yannic Kilcher interviewed Nir Shavit last year and they went into some depth: https://www.youtube.com/watch?v=0PAiQ1jTN5k DeepSparse is on GitHub: https://github.com/neuralmagic/deepsparse
Project mention: New models and developer products announced at OpenAI DevDay | news.ycombinator.com | 2023-11-06>How do you detect speech starting and stopping?
https://github.com/snakers4/silero-vad
Project mention: Introducing Cellulose - an ONNX model visualizer with hardware runtime support annotations | /r/tensorflow | 2023-05-23[1] - We use onnx-tensorrt for this TensorRT compatibility checks.
Project mention: [D] Object detection models that can be easily converted to CoreML | /r/MachineLearning | 2023-07-25
Project mention: X-AnyLabeling: Effortless Data Labeling with AI, Segment Anything and Others | news.ycombinator.com | 2024-03-19
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
Project mention: FastEmbed: Fast and Lightweight Embedding Generation for Text | dev.to | 2024-02-02Shout out to Huggingface's Optimum – which made it easier to quantize models.
Onnx related posts
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AI Inference now available in Supabase Edge Functions
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จำแนกสายพันธ์ุหมากับแมวง่ายๆด้วยYoLoV5
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FastEmbed: Fast and Lightweight Embedding Generation for Text
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Show HN: OnnxStream running TinyLlama and Mistral 7B, with CUDA support
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OnnxStream running TinyLlama and Mistral 7B, with CUDA support
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Oracle-samples/sd4j: Stable Diffusion pipeline in Java using ONNX Runtime
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A note from our sponsor - SaaSHub
www.saashub.com | 1 May 2024
Index
What are some of the best open-source Onnx projects? This list will help you:
Project | Stars | |
---|---|---|
1 | yolov5 | 46,921 |
2 | netron | 26,110 |
3 | ncnn | 19,234 |
4 | onnxruntime | 12,736 |
5 | clip-as-service | 12,193 |
6 | YOLOX | 9,012 |
7 | models | 7,192 |
8 | burn | 7,074 |
9 | MMdnn | 5,780 |
10 | SynapseML | 4,970 |
11 | silero-models | 4,546 |
12 | onnx-simplifier | 3,550 |
13 | PINTO_model_zoo | 3,301 |
14 | yolov7_d2 | 3,130 |
15 | deepsparse | 2,873 |
16 | silero-vad | 2,829 |
17 | 3DDFA_V2 | 2,784 |
18 | onnx-tensorrt | 2,760 |
19 | FastDeploy | 2,705 |
20 | mmdeploy | 2,511 |
21 | X-AnyLabeling | 2,477 |
22 | tensorflow-onnx | 2,214 |
23 | optimum | 2,141 |
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