models
onnx
models | onnx | |
---|---|---|
7 | 38 | |
7,192 | 16,858 | |
1.4% | 1.0% | |
4.8 | 9.5 | |
12 days ago | 6 days ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
models
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AMD Accelerates AI Adoption on Windows 11 With New Developer Tools for Ryzen AI
Uh, 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.
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Need Help With Darknet YOLOv4-Tiny Model In Unity Barracuda
I am new to object detection models and I need help running my object detection Darknet YOLOv4-Tiny Model In Unity Barracuda. I trained my model and then i converted it to ONNX format with 2 methods. One method was using pytorch-YOLOv4 from github and the other by converting my model to tensorflow and then to onnx and shown here: "https://github.com/onnx/models/blob/main/vision/object_detection_segmentation/yolov4/dependencies/Conversion.ipynb"
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Need Help Converting Darknet Yolov4-tiny Model to ONNX
Then i tried to convert it again using another method that i found here "https://github.com/onnx/models/blob/main/vision/object_detection_segmentation/yolov4/dependencies/Conversion.ipynb" in order to convert it from darknet to tensorflow and then to onnx but i didn't have any luck.
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Text generation with GPT-2 in Ruby
Here we use the GPT-2 model distributed by the ONNX official. Download GPT-2-LM-HEAD from the link.
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YOLOv7 object detection in Ruby in 10 minutes
Download pre-trained models from the ONNX Model Zoo
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Has anyone successfully converted an onnx model to tensorflow? Here's the problems I'm having...
Instructions to reproduce the problem: I am trying to convert a proprietary model at work but for now i'll use mobilenetv2-7.onnx to explain/reproduce the issue.
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How to identify identical frames that are not technically duplicates? Ie if I am taking a video of a car, it stops for 1 minute (and within that minute nothing changes visually), and then drives away. How would I remove all but 1 of the frames when it is stopped?
One approach could be run a pre-trained object detector (like one of these) on each frame and then a simple object tracker on top of it (like this).
onnx
- Onyx, a new programming language powered by WebAssembly
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From Lab to Live: Implementing Open-Source AI Models for Real-Time Unsupervised Anomaly Detection in Images
Once your model has been trained and validated using Anomalib, the next step is to prepare it for real-time implementation. This is where ONNX (Open Neural Network Exchange) or OpenVINO (Open Visual Inference and Neural network Optimization) comes into play.
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Object detection with ONNX, Pipeless and a YOLO model
ONNX is an open format from the Linux Foundation to represent machine learning models. It is becoming extensively adopted by the Machine Learning community and is compatible with most of the machine learning frameworks like PyTorch, TensorFlow, etc. Converting a model between any of those formats and ONNX is really simple and can be done in most cases with a single command.
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38TB of data accidentally exposed by Microsoft AI researchers
ONNX[0], model-as-protosbufs, continuing to gain adoption will hopefully solve this issue.
[0] https://github.com/onnx/onnx
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Reddit’s LLM text model for Ads Safety
Running inference for large models on CPU is not a new problem and fortunately there has been great development in many different optimization frameworks for speeding up matrix and tensor computations on CPU. We explored multiple optimization frameworks and methods to improve latency, namely TorchScript, BetterTransformer and ONNX.
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Operationalize TensorFlow Models With ML.NET
ONNX is a format for representing machine learning models in a portable way. Additionally, ONNX models can be easily optimized and thus become smaller and faster.
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Onnx Runtime: “Cross-Platform Accelerated Machine Learning”
I would say onnx.ai [0] provides more information about ONNX for those who aren’t working with ML/DL.
[0] https://onnx.ai
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Does ONNX Runtime not support Double/float64?
It's not clear why you thing this sub is appropriate for some third party system with a Python interface. Why don't you try their discussion group: https://github.com/onnx/onnx/discussions
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Async behaviour in python web frameworks
This kind of indirection through standardisation is pretty common to make compatibility between different kinds of software components easier. Some other good examples are the LSP project from Microsoft and ONNX to represent machine learning models. The first provides a standard so that IDEs don't have to re-invent the weel for every programming language. The latter decouples training frameworks from inference frameworks. Going back to WSGI, you can find a pretty extensive rationale for the WSGI standard here if interested.
- Pickle safety in Python
What are some alternatives?
SSD-Mobilenet-Custom-Object-Detector-Model-using-Tensorflow-2 - This repository contains the script and process to create custom SSD Mobilenet model for object detection
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
netron - Visualizer for neural network, deep learning and machine learning models
stable-diffusion-webui - Stable Diffusion web UI
onnx-tensorflow - Tensorflow Backend for ONNX
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]
redisai-examples - RedisAI showcase
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
stable-diffusion - A latent text-to-image diffusion model
tensorboard - TensorFlow's Visualization Toolkit
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/sd-webui/stable-diffusion-webui]