telepresence VS label-studio

I trialled Telepresence[0] for my company 2 or 3 years ago, that does this sort of thing very slickly. It didn't quite work for us back then, I forget why, but I imagine it's come along a way since then.

[0] https://www.telepresence.io

How does this compare to Telepresence?

seems to be very similar to https://www.telepresence.io

If they're web services you work on, you might try https://www.telepresence.io/ (Requires something to be installed in the cluster though, easily done).

Depending on the context, the type of code you do, you may want to also look into the sister protocol to LSP, DAP—debug adaptor protocol. It really depends on your context whether local dev, dev against a remote server, and if the latter whether you run under GCP and thus have the “Snapshot Debugger”, or under Kubernetes with something like Ambassadar/Emissary and thus can run Telepresence, whether you do local or remote Docker and thus most IDEs don't necessarily magically work especially if the containers are competently locked down, etc.

If you're on Kubernetes remotely, Telepresence [0] might be worth a look.

[0] https://www.telepresence.io

Sounds Like Telepresence (https://github.com/telepresenceio/telepresence) which intercepts traffic to a service on the cluster and directs it to your local environment.

This seems to be very similar to Telepresence, which I just couldn't get to work for us.

What the difference with okteto and telepresence ?

14. LabelStudio by Human Signal | Github | tutorial

For instance, the COCO Annotator is a web-based image annotation tool tailored for the COCO dataset format, allowing collaborative labeling with features like attribute tagging and automatic segmentation. Similarly, Label Studio offers an easy-to-use interface for bounding box object labeling in images.

Huh?

I wrote my own system for classifying a stream of texts in Python, I might Open Source it one of these days but I have to get it to the point where it is modular enough that I can customize it to do the particular things I want without subjecting people to my whims... I use it every day and I'm not afraid to demo it because it is rock solid.

My understanding is that my system would not be hard to adapt to work on images for certain kinds of tasks.

Pytorch is open source, Huggingface is open source. CUDA isn't. This is

https://labelstud.io/

and for annotating text spans there are so many open source tools

https://github.com/doccano/doccano

I worked for a company a few years back that built annotation tools for projects we sold to customers but never quite got to a polished general purpose annotator. Today there are an overwhelming number of companies in this space and products I never heard of, many of which are cloud based or paid. Looks like a gold rush to me.

LabelStudio is free for single use. https://labelstud.io/

LabelStudio is pretty nice, and free & open source, but I have yet to try out their ML integration with a YOLO object detection model.

Label Studio is an open source data labeling tool that includes annotation functionality. It provides a simple user interface (UI) that lets you label various data types, including text, audio, time series data, videos, and images, and export the information to various model formats.

I’m fairly new to deep learning and learning as I got so sorry if this is very basic, but I’m working on a model for detecting invasive coconut rhinoceros beetles destroying palm trees using drone photography. The 1080p photos I’m given were taken 250ft AGL and were cropped into equal size smaller images with some having one or more palm trees and some having none. Im using I’m using labelStudio to generate the XML files that point to their jpg counterparts path.