ubicloud VS LAVIS

The docs still say the Elastic license is used but looking at https://github.com/ubicloud/ubicloud/blob/main/LICENSE it looks like the project might have switched to GNU Affero General Public License v3.0 in the last day.

At Ubicloud, we have 100% line and branch coverage that is mandated on every PR (https://github.com/ubicloud/ubicloud). We also have an E2E test suite that we run periodically and with every commit. We did not really feel like our tests are slowing us down, it actually makes us faster since we have a higher trust to the payload and many manual checks that would need to be done is safely skipped.

> Taken from here: https://ubicloud.com/

Am I the only one getting a certificate error browsing there?

Link to our project: https://github.com/ubicloud/ubicloud

We’re choosing Elastic V2 for three reasons: (1) We’re planning to monetize through a managed service and we’d like the license to support that, (2) Later if we change our mind, we think it’s easier on our users if we go from a restrictive license to a more permissive one, and (3) The Elastic V2 license is much simpler than its cousin, Server Side Public License (SSPL).

That said, Elastic V2 is a new license and doesn’t seem to as popular as SSPL. Also, some projects out there mix and match multiple licenses in their repo to be able to call themselves open source.

Any insights / feedback on Elastic V2 or software licenses in general?

For multimodal, there's China (*many), then Salesforce.

Been trying for all day to get a working inference for this example: https://github.com/salesforce/LAVIS/tree/main/projects/instructblip

There's also been big breakthroughs in computer vision. Not that long ago it was hard to recognize if a photo contained a bird; that's solved now by models like CLIP, Yolo, or Segment Anything. Now research has moved on to generating 3D scenes from images or interactively answering questions about images.

The new hotness is multimodal vision-language models like InstructBLIP that can interactively answer questions about images. Check out the examples in the github repo, I would not have thought this was possible a few years ago.

Salesforce’s BLIP family has a new member– InstructBLIP, a vision-language instruction-tuning framework using BLIP-2 models. It has achieved state-of-the-art zero-shot generalization performance on a wide range of vision-language tasks, substantially outperforming BLIP-2 and Flamingo. (Source)

Github

Most of my workflows are self-made. For captioning I used Blip-2 in a custom script I made that automates the process by going into directories and their sub-directories and creates a .txt file beside each image. This way I can keep my images organized in their proper directories, without having to put dump them all in a single place.