blackjack-basic-strategy VS Mattermost

It’s an easy to use inference server for computer vision models.

The end result is a Docker container that serves a standardized API as a microservice that your application uses to get predictions from computer vision models (though there is also a native Python interface).

It’s backed by a bunch of component pieces:

* a server (so you don’t have to reimplement things like image processing & prediction visualization on every project)

* standardized APIs for computer vision tasks (so switching out the model weights and architecture can be done independently of your application code)

* model architecture implementations (which implement the tensor parsing glue between images & predictions) for supervised models that you've fine-tuned to perform custom tasks

* foundation model implementations (like CLIP & SAM) that tend to chain well with fine-tuned models

* reusable utils to make adding support for new models easier

* a model registry (so your code can be independent from your model weights & you don't have to re-build and re-deploy every time you want to iterate on your model weights)

* data management integrations (so you can collect more images of edge cases to improve your dataset & model the more it sees in the wild)

* ecosystem (there are tens of thousands of fine-tuned models shared by users that you can use off the shelf via Roboflow Universe[1])

Additionally, since it's focused specifically on computer vision, it has specific CV-focused features (like direct camera stream input) and makes some different tradeoffs than other more general ML solutions (namely, optimized for small-fast models that run at the edge & need support for running on many different devices like NVIDIA Jetsons and Raspberry Pis in addition to beefy cloud servers).

[1] https://universe.roboflow.com

* Most of the time I find Roboflow extremely handy, I used it to merge datasets, augmentate, read tutorials and that kind of thing. Basically you just create your dataset with roboflow and focus on other aspects.

For computer vision, there are 100k+ open source classification, object detection, and segmentation datasets available on Roboflow Universe: https://universe.roboflow.com

Solid website and app overall for learning more about computer vision, discovering datasets, and keeping up with advancements in the field: * https://roboflow.com/learn * https://universe.roboflow.com (datasets) | https://blog.roboflow.com/computer-vision-datasets-and-apis/ * https://blog.roboflow.com

If you're lacking training images, you can also use [Roboflow Universe](https://universe.roboflow.com) to obtain them (over 100 million labeled images available)

Roboflow | Multiple Roles | Full-time (Remote) | https://roboflow.com/careers

Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of sight. Our end-to-end platform[1] provides tooling for image collection, annotation, dataset exploration and curation, training, and deployment.

Over 100k engineers (including engineers from 2/3 Fortune 100 companies) build with Roboflow. And we now host the largest collection[2] of open source computer vision datasets and pre-trained models[3].

We have several openings available, but are primarily looking for strong technical generalists who want to help us democratize computer vision and like to wear many hats and have an outsized impact. (We especially love hiring past and future founders.)

We're hiring 3 full-stack engineers this quarter and we're also looking for an infrastructure engineer with Elasticsearch experience.

[1]: https://docs.roboflow.com

[2]: https://blog.roboflow.com/computer-vision-datasets-and-apis/

[3]: https://universe.roboflow.com

Based on what I do/use when I prepare models: A good framework for creating and improving this dataset faster is to use Roboflow Universe and search “flowers” and “bouquets of flowers” in the search bar (it’s like Google Images for CV Datasets). You can search images by subject, or metadata, and clone them directly into a free public workspace (they house up to 10k images without charge). * https://universe.roboflow.com/ * https://universe.roboflow.com/search?q=flowers * https://universe.roboflow.com/search?q=bouqets

Lots of ideas will come to mind if you look and search through open source datasets: https://universe.roboflow.com/

Open source datasets: https://universe.roboflow.com/ Model training: https://docs.roboflow.com/train Model deployment: https://docs.roboflow.com/inference/hosted-api

> Tell me another platform that is free, has realtime chat, voice and video, has stable service, allows sharing images and other media, with good ownership management... and is open source.

Mattermost: https://mattermost.com/

Rocket.Chat: https://www.rocket.chat/

Nextcloud Talk: https://nextcloud.com/talk/

Self hosting and some assembly required. I've run all of them on cheap VPSes to explore a Slack/Discord replacement, neither was mindblowing but all of them seemed okay (Nextcloud's offering was rather barebones, though).

Audio and video support varies because getting those right is challenging, at best you'd just integrate with something like Jitsi, that one's actually pretty good for meetings and such: https://jitsi.org/ and has a cloud version too: https://meet.jit.si/ (yet people still go for Zoom and it's odd UI/UX choices)

I actually rather liked forums back in the day, but I guess nobody will be setting up that many phpBB instances in the current year, though projects like Discourse also seem promising: https://www.discourse.org/

I don't think many people at all will be leaving Discord, due to how entrenched the platform is (network effect): if you want people to help you with what you're working on, you go where they are, not vice versa.

Mattermost, Inc. | Senior React Native Engineer | REMOTE (US Only) | Full-Time

At Mattermost we build an open core, chat and collaboration platform focused on making users with mission critical work more productive while also allowing our customers to self-deploy and have full control over their own data.

We’re looking for a Senior React Native Engineer who has the depth to significantly move the performance needle of our app while also having the breadth to contribute across our stack.

Check out our open source mobile codebase: https://github.com/mattermost/mattermost-mobile. Meta uses the Mattermost RN app as the benchmark for performance testing of their Hermes JS engine: https://mattermost.com/blog/hermes-mattermost/. Want to set the bar for what a complex, high performing React Native app can do? Want to do it open source? Join our team!

Apply here: https://jobs.lever.co/mattermost/a38ea8f0-6c27-4178-a988-801...

Mattermost for Chat, and also for Notifications sent by Uptime-Kuma

Mattermost offers a secure, open-source solution for seamless collaboration throughout the software development lifecycle. Tailored to cater to technical and operational needs, it easily integrates with a wide range of third-party developer tools—to streamline development and engineering workflows. With self-hosted and private cloud deployment options, coupled with access to the source code, you have complete control over the data via a shared, adaptable, and extensible platform designed specifically for your team. Kindly suggested by Molasses_Major.

FWIW, most of the TypeScript lines of code are in the E2E tests[0] and the webapp dir [1], which, as the name suggests, contains "the client code for the Mattermost web app". So we should really only be counting lines of Go code.

[0] https://github.com/mattermost/mattermost/tree/master/e2e-tes...

[1] https://github.com/mattermost/mattermost/tree/master/webapp

Mattermost is an good alternative to companies, workers and teams.

oder auch Mattermost

Revolt, Guilded, Element (Matrix Client), Matrix, Cinny (Matrix Client), Spacebar, Rocket Chat, Mikoto, Mattermost, Teamspeak and Nertivia

might be overkill but https://mattermost.com/

But it seems that you're right for Mattermost.