BentoML
openpilot
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BentoML | openpilot | |
---|---|---|
16 | 838 | |
6,441 | 47,150 | |
3.5% | 2.0% | |
9.8 | 10.0 | |
about 11 hours ago | 1 day ago | |
Python | Python | |
Apache License 2.0 | 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.
BentoML
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Who's hiring developer advocates? (December 2023)
Link to GitHub -->
- Ask HN: Who is hiring? (November 2022)
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[D] How to get the fastest PyTorch inference and what is the "best" model serving framework?
For 2), I am aware of a few options. Triton inference server is an obvious one as is the ‘transformer-deploy’ version from LDS. My only reservation here is that they require the model compilation or are architecture specific. I am aware of others like Bento, Ray serving and TorchServe. Ideally I would have something that allows any (PyTorch model) to be used without the extra compilation effort (or at least optionally) and has some convenience things like ease of use, easy to deploy, easy to host multiple models and can perform some dynamic batching. Anyway, I am really interested to hear people's experience here as I know there are now quite a few options! Any help is appreciated! Disclaimer - I have no affiliation or are connected in any way with the libraries or companies listed here. These are just the ones I know of. Thanks in advance.
- PostgresML is 8-40x faster than Python HTTP microservices
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Show HN: Truss – serve any ML model, anywhere, without boilerplate code
In this category I’m a big fan of https://github.com/bentoml/BentoML
What I like about it is their idiomatic developer experience. It reminds me of other Pythonic frameworks like Flask and Django in a good way.
I have no affiliation with them whatsoever, just an admirer.
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[P] Introducing BentoML 1.0 - A faster way to ship your models to production
Github Page: https://github.com/bentoml/BentoML
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Show HN: Bentoctl – An open-source Terraform deployment tool for ML
Elastic License 2: https://github.com/bentoml/bentoctl/blob/v0.3.1/LICENSE.md which also applies to their Yatai kubernetes thing, but strangely not (yet?) to the similarly named repo which is Apache-2: https://github.com/bentoml/BentoML/blob/main/LICENSE
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How to Build a Machine Learning Demo in 2022
Using a general-purpose framework such as FastAPI involves writing a lot of boilerplate code just to get your API endpoint up and running. If deploying a model for a demo is the only thing you are interested in and you do not mind losing some flexibility, you might want to use a specialized serving framework instead. One example is BentoML, which will allow you to get an optimized serving endpoint for your model up and running much faster and with less overhead than a generic web framework. Framework-specific serving solutions such as Tensorflow Serving and TorchServe typically offer optimized performance but can only be used to serve models trained using Tensorflow or PyTorch, respectively.
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MLH, Open Source, Mapillary & Me
BentoML - BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models.
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Why do so many people think Python is easier to productionize than R?
Also mlflow is not that optimized because it doesnt microbatch like torchserve/tfserving/bentoml. https://github.com/bentoml/BentoML/tree/master/benchmark
openpilot
- I need some help understanding video uploads.
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Thomas Massie Failed to Stop "Kill Switch" Mandate That Could Disable Vehicles
Indeed. Comma.ai [1] does this [2] in a very open way.
Unfortunately existing manufacturers are unlikely to implement this in a complete local-first way.
[1] https://comma.ai
[2] https://github.com/commaai/openpilot/blob/master/selfdrive/m...
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Ask HN: Who is hiring? (November 2023)
See our open source driving agent on GitHub: https://github.com/commaai/openpilot
- Beginners Guide: Subaru Vehicles with Eyesight
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cv.c: experimental computer library in C; A Robot's guide to seeing the world -- introductory guide to CV
Hello! I was absolutely enthralled by Computer Vision when I came across some of Geohotz's streams about developing Comma.ai (a self-driving company) and I decided to delve into Computer Vision about a week back. I began by working on Aadv1k/cv.c which was meant to "imitate" OpenCV, as the phrasing goes "You Learn by building" I would be lying if I said this program is decent, it is not. I havent optimized much of it and this is like my 3rd C project :P Here is what all I got working (I will continue work on this), the only dependency here is STB * Smoothing * Gaussian blur * Median filter * Bilateral Filter * Box Filter * Edge detection * Unsharp mask * Laplacian Filter (Difference of Gaussian) * Sobel operator * Color * Greyscale * Thresholding * Global * Otsu's Method
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Can I use my Galaxy S10+ with my 2016 CR-V to run Flowpilot?
1.) Will this system work with my car? 2016 CR-Vs show up under the list of cars, but it says touring trim and I do not have the touring trim. I have found resources that state that any trim will still work with this and I am wondering if my car still has the actuators or ability to work with these systems.
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2020 Sierra/GMC CAN ids
Finally, worse comes to worse, manually extracting the DBC and parsing it using Cabana.
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Best Setup for Remote Control?
It's probably best you search for the Retropilot Discord. This is beyond what the normal comma.ai people or community try to do.
- If you have a Comma Three and a 2023 Corolla or 2023 Prius, comma is looking for testers for a "Toyota B Harness"
What are some alternatives?
sunnypilot - sunnypilot is a fork of comma.ai's openpilot, an open source driver assistance system. sunnypilot offers the user a unique driving experience for over 260 supported car makes and models with modified behaviors of driving assist engagements. sunnypilot complies with comma.ai's safety rules as accurately as possible.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
carla - Open-source simulator for autonomous driving research.
opendbc - democratize access to car decoder rings
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
clearml - ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
dragonpilot - dragonpilot - 基於 openpilot 的開源駕駛輔助系統
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
kubeflow - Machine Learning Toolkit for Kubernetes
netron - Visualizer for neural network, deep learning and machine learning models