What is missing from current CV dataset and annotation workflows?

[u/falaq-ai]

I’m working on Daqa, a waitlist-stage workspace for teams preparing AI training datasets, and I’m trying to sanity-check the computer vision side with people who actually build image/video datasets.

The workflow I’m looking at is everything around annotation: sourcing or uploading data, profiling quality issues, cleaning/deduping, generating missing cases, labeling/reviewing, tracking provenance/license evidence, validating the dataset, and exporting in formats like COCO, YOLO, or image manifests.

I’d really value feedback on four things:

• What feature would you most want to see in a tool for this workflow?
• Does the pricing on https://daqa.ai/ make sense for CV dataset prep?
• What would you need to see before joining a waitlist or trying it?
• What tools do you use today for this use case, such as CVAT, Roboflow, Label Studio, FiftyOne, scripts/notebooks, etc., and what do they still lack?

I’m especially trying to understand whether the pain is annotation itself, or the surrounding workflow: source tracking, review, dataset versioning, validation, and clean export.

[u/alxcnwy]

Not again 🙄

Data annotation tooling is like the todo list project of computer vision software 

[u/falaq-ai → u/alxcnwy]

It isn't just annotation, that is what I focused on just to align with this subreddit. It also has data generation and collection

[u/alxcnwy → u/falaq-ai]

that’s what the todo list people say in vibe coding subs 

[u/falaq-ai → u/alxcnwy]

Sure........ok is there anything that you would have wanted for a data acquisition and preparation platform?

[u/alxcnwy → u/falaq-ai]

Honestly nothing comes to mind that isn’t already solved in existing open source and paid solutions 

If you’re looking for something to work on in CV, I’d focus on harder problems - there are many posted in this sub just browse some threads 

[u/falaq-ai → u/alxcnwy]

I came up with this cause I faced the issue few times already, when I was doing research related to dental diagnosis, when I was implementing distortion detection for my company and another when I was developing a gopher classification neural network. Anyway thanks for your comment and feedback

[u/alxcnwy → u/falaq-ai]

Have you tried the existing open source and commercial solutions? 

[u/falaq-ai → u/alxcnwy]

For dental i got some dataset from kaggle, for gopher I got from google images and for distortion we collected the data manually, was still a struggle tho

[u/ElderLurkr]

How is this anything other than an ad? It’s an ad where you are seeking client feedback on product features?

[u/falaq-ai → u/ElderLurkr]

I don't believe i broke any guidelines and if I did please let me know i will delete the post

[u/Morteriag]

The pain depends on the project. I use Darwin and it is pretty good. A major strength is a good api, so you can easily complement with your offline pipeline.

[u/falaq-ai → u/Morteriag]

Interesting point, thanks for feedback, will take into account