What should Tool become — open source or with community Edition?
Hey everyone,
I've been building a labelling tool, a desktop app (PyQt6) for capturing and annotating gesture datasets — think of it as a companion tool for gesture recognition pipelines like Gesto, making it easier to collect, label, and export hand landmark data for training models.
I'm at a fork in the road on direction, and I'd love your input:
1. Open source it — release it freely (currently GPL-3.0), let the community use it, contribute, and shape where it goes.
2. Build a paid/commercial version — invest in polish, support, and features, and offer it as a proper product.
A few things I'm weighing:
Open source could grow adoption faster and build trust in the gesture-recognition/CV space
A paid version could fund continued development and let me focus more time on it
There's also a possible middle ground — open core with paid add-ons, or free for individuals/paid for teams
What would you rather see? And if you've built or used similar dev tools, what worked (or didn't) for you?
Curious to hear your thoughts — genuinely undecided here and want to build something people actually want.
Replies
@sundar_balamurugan What would make you personally happier after a year, a bigger user base or a profitable product?
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@sophie_myers For this bigger userbase
@sundar_balamurugan Would an open community help the product improve faster?
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@casper_voigt 100% yes!
@sundar_balamurugan Is there a reason not to start free and learn from real usage?
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@ellie_russell No reason. Just starting free is the way forward.
@sundar_balamurugan If you had to choose today, which option feels more exciting?
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@ruby_diaz1 Opensource + community one.
I’d go open core / community edition. The core labeling workflow should probably be open, especially because researchers and CV teams will want to inspect, trust, and adapt the dataset pipeline. That will help adoption much faster than a fully paid tool.
But the commercial layer can still make sense around team features: collaboration, dataset versioning, advanced exports, QA/review flows, cloud sync, integrations, and support.
In short: make the core useful and trustworthy for the community, then charge for the workflows that serious teams rely on.
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@kryptonite_wei Thank you Xinyuanwei.
That's what I am working towards. Thank you.
One suggestion don't monetize too early. A great product with an active community is easier to sell later than a paid product nobody has heard of. Adoption is an asset you can't buy.
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@ella_reyes1 Thanks Ella.
Will work towards it. This is helpful to me .
As someone who works with ML tooling, i instantly trust open-source projects more because i can inspect how everything works. But I'd still pay for priority support or features that save my team hours every week.
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@rose_florean Thanks Rose.
Will keep it in mind.
@sundar_balamurugan that approach feels unsustainable. which audience do you want to serve first?
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@hana_salazars Mainly Techies. Ease the process .
My instinct would be community-first, but with a very clear commercial path from day one. For a gesture dataset tool, trust and adoption matter a lot because researchers and builders will want to inspect the pipeline, understand export formats, and adapt it to their own model workflows. Open source can help there. The paid layer could come later around team workflows: dataset versioning, QA checks, collaboration, managed storage, or support for companies building production recognition systems. One practical question: who is the user you most want to learn from first, individual ML builders or teams collecting datasets at scale? That answer probably decides the model more than the license itself.
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@rahulbhavsar Understood.
Will move out in this direction now.
@sundar_balamurugan If someone contributed their first improvement tomorrow, would that change your thinking?
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@ethan_marshall Depends on the contribution.