ultralytics
Tribuo
ultralytics | Tribuo | |
---|---|---|
27 | 15 | |
22,973 | 1,223 | |
7.1% | 0.3% | |
9.8 | 4.8 | |
4 days ago | about 1 month ago | |
Python | Java | |
GNU Affero General Public License v3.0 | Apache 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.
ultralytics
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The CEO of Ultralytics (yolov8) using LLMs to engage with commenters on GitHub
Yep, I noticed this a while ago. It posts easily identifiable ChatGPT responses. It also posts garbage wrong answers which makes it worse than useless. Totally disrespectful to the userbase.
https://github.com/ultralytics/ultralytics/issues/5748#issue...
- FLaNK Weekly 08 Jan 2024
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My kid sounds like ChatGPT, and soon yours might, too
There are obvious places it is being used that I have noticed organically. For instance, check out the answers in this repo:
https://github.com/ultralytics/ultralytics/issues/5748#issue...
If you read the answers there, the style of answering is always to repeat the question in a very specific way. Once you see it you can’t in-see it.
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
When browsing the state-of-the-art in object detection on Papers with Code, I found the YOLO model to be one of the most popular, accurate, and fastest. That being said, I would recommend having a look at Ultralytics, which provides the tools to evaluate, predict, and export the latest versions of YOLO models with only a few lines of code.
- Instance segmentation of small objects in grainy drone imagery
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Breaking the Myth: Object Detection Isn't Hard as Thought
YOLOv8 (You Only Look Once) is an open-source Computer Vision AI model released on January 10th, 2023. It’s called YOLO because it detects everything inside an image in a single pass. The new version can perform image detection, classification, instance segmentation, tracking, and pose estimation tasks.
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How I use "AI" to entertain my cat
Next, I needed to figure out, how can I access the stream, recognize an animal, then let Max know? There are tons of examples of recognizing an object via camera frames, but I ultimately found this python library called ultralytics that supports RTSP streams and classifying objects in the video frames using pre-built models. The docs looked like it would be pretty low effort, so after some experimentation, I was successful in having the ultralytics library recognize objects from my cheap camera!
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How to load the optimizer state_dicts in yolov8?
I have created an issue in their Github as well but so far not much help has been recieved. You can check that here
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Autodistill: A new way to create CV models
And the target models include: * YOLOv8 (You Only Look Once) * YOLO-NAS * YOLOv5 * and DETR
Tribuo
- FLaNK Weekly 08 Jan 2024
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Is deeplearning4j a good choice?
It seems to have been picked up by Eclipse and there is also Oracle Labs' Tribuo and Deep Java Library. All seem active, but I don't know much about any of them. I agree it's probably best to follow the community and use a more popular tool like PyTorch.
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Stochastic gradient descent written in SQL
We built model & data provenance into our open source ML library, though it's admittedly not the W3C PROV standard. There were a few gaps in it until we built an automated reproducibility system on top of it, but now it's pretty solid for all the algorithms we implement. Unfortunately some of the things we wrap (notably TensorFlow) aren't reproducible enough due to some unfixed bugs. There's an overview of the provenance system in this reprise of the JavaOne talk I gave here https://www.youtube.com/watch?v=GXOMjq2OS_c. The library is on GitHub - https://github.com/oracle/tribuo.
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Just want to vent a bit
Although it may be a bit more work, you can do both machine learning and AI in Java. If you are doing deep learning, you can use DeepJavaLibrary (I do work on this one at Amazon). If you are looking for other ML algorithms, I have seen Smile, Tribuo, or some around Spark.
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Anybody here using Java for machine learning?
We've been developing Tribuo on Github for two years now, MS are very actively developing ONNX Runtime (and the Java layer is fairly thin and wrapped over the same C API they use for node.js and C#), and things like XGBoost and LibSVM have been around for many years and the Java bits are developed in tree with the rest of the code so updated along with it. Amazon have a team of people working on DJL, though you'd have to ask them what their plans are.
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Java engineer wants to be a researcher
FWIW, Oracle actually did release a Java ML library - https://github.com/oracle/tribuo.
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txtai 3.4 released - Build AI-powered semantic search applications in Java
Tribuo (tribuo.org, github.com/oracle/tribuo). ONNX export support is there for 2 models at the moment in main, there's a PR for factorization machines which supports ONNX export, and we plan to add another couple of models and maybe ensembles before the upcoming release. Plus I need to write a tutorial on how it all works, but you can check the tests in the meantime.
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Hottest topics for research for JAVA software engineers
You can do ML & data science in Java (full disclosure: I help run TensorFlow-Java, I maintain ONNX Runtime's Java interface, and I'm the lead developer on Oracle Labs' Java ML library Tribuo, so I'm pretty biased). It tends not to be as favoured in research, though I've published academic ML papers which used Java implementations. People do deploy ML models quite a bit in Java in industry.
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John Snow Labs Spark-NLP 3.1.0: Over 2600+ new models and pipelines in 200+ languages, new DistilBERT, RoBERTa, and XLM-RoBERTa transformers, support for external Transformers, and lots more!
It might be worth having a look at the ONNX Runtime Java API in addition to TF-Java, it'll let you deploy the rest of the HuggingFace pytorch models that don't have TF equivalents. I built the Java API a few years ago, and it's now a supported part of the ONNX Runtime project. We use it in Tribuo to provide one of our text feature embedding classes (BERTFeatureExtractor).
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If it gets better w age, will java become compatible for machine learning and data science?
The IJava notebook kernel works pretty well for data science on top of Java. We use it in Tribuo to write all our tutorials, and if you've got the jar file in the right folder everything is runnable. For example, this is our intro classification tutorial - https://github.com/oracle/tribuo/blob/main/tutorials/irises-tribuo-v4.ipynb.
What are some alternatives?
segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
yolo_tracking - BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
oj! Algorithms - oj! Algorithms
GroundingDINO - Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
spark-nlp - State of the Art Natural Language Processing
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/Auto-GPT]
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
yolov8_onnx_python - YOLOv8 inference using Python
grobid - A machine learning software for extracting information from scholarly documents