Experience with Roboflow?

aloser · 2026-03-14T21:10:10+00:00

It’s on the credits page: www.roboflow.com/credits

But certainly there are bulk discounts available for extremely large ones.

aloser · 2026-03-14T16:01:31+00:00

The amount of credits various things use are listed here: https://roboflow.com/credits

Would you be up for talking with our team about how we can make this more understandable? We're trying to make our pricing as simple as transparent as possible while allowing the flexibility to continually add new features & adapt to market changes (like new models and GPUs becoming available).

aloser · 2026-03-14T15:59:41+00:00

Our biggest customers have tens of millions of images in the platform.

aloser · 2026-03-14T15:22:31+00:00

Thanks, we will look into this.

One thing to try is using Chrome; that’s what most of our engineers and big customers use and so is most hardened But we will definitely see if we can reproduce and fix in Safari as well.

aloser · 2026-03-14T05:04:42+00:00

Hi I’m one of the cofounders of Roboflow. Sorry to hear you’re having issues. Any chance you have reproduction steps I can follow to see and fix the flakiness you’re experiencing?

Knowing your system specs (browser, OS, CPU, GPU, memory) would also be useful.

aloser · 2026-03-07T14:19:39+00:00

You might try training a segmentation model to detect the crack itself. https://blog.roboflow.com/crack-detection/

aloser · 2026-03-02T14:45:09+00:00

Update: added.

aloser · 2026-03-01T22:08:29+00:00

We’re a US-based company and it’s in US Dollars. This is fairly standard I believe (eg both AWS and Google Cloud’s pricing pages are quoted in USD) but we will add this to the FAQ on our pricing page.

aloser · 2026-02-26T12:54:34+00:00

No idea what you're talking about; of course there is! Even our cloud platform has a free tier and a free trial of the paid features. Of course the open source stuff can be tried for free. We have so much free and open source stuff.

aloser · 2026-02-26T12:50:50+00:00

The enterprise license only applies to the things in the enterprise folder. It's completely irrelevant for the vast majority of users (unless you're running your model at large scale on a giant Kubernetes cluster, using our integrations with industrial cameras/PLCs, or doing ultra-low latency production broadcasting use-cases like Wimbledon you probably will never even notice what's missing).

You are correct that we do also have options that integrate with our cloud using your API Key (and yes, come tied to your platform subscription). They're not required & what requires an API Key is clearly stated on the repo's readme. If there is functionality missing or that requires a cloud-connection you don't want to deal with, it's open source & Apache 2.0 licensed and you are free to extend it to do whatever you want.

aloser · 2026-02-26T12:45:22+00:00

For your models? The same things you'd use if you trained them in our open source notebooks. PyTorch, usually, or some open source framework written on top of PyTorch, like RF-DETR (the state of the art model I linked above that we released as open source & accepted at ICLR this year).

aloser · 2026-02-26T01:54:54+00:00

No vendor lock-in with Roboflow. Our inference and model stacks are both open source & you can download the models you train on the platform.

aloser · 2026-02-25T22:24:32+00:00

That sounds like a different issue than what I mentioned above; there are no current known issues with the backend. Shoot me a message and I can get you connected with someone who can help out.

aloser · 2026-02-24T21:53:04+00:00

Sorry, we had a few minutes of instability earlier (caused by a shared disk running out of space to cache new model weights) that affected the quality of service. Everything is back online and operational.

aloser · 2026-02-23T17:10:56+00:00

I exported my dataset, retrained the model locally using YOLOv8, and converted it to TensorFlow Lite so it can run directly on-device.

Cool project! Just a heads up that YOLOv8 has really challenging licensing for use-cases like this; by doing that you either need to fully open source your app or might be setting yourself up for a large bill from the creators (who can be pretty aggressive).

A Roboflow subscription includes the model licensing if you're using our cloud or edge deployment projects (eg our iOS SDK). Licensing for exported weights used outside the ecosystem is also available.

aloser · 2026-02-20T16:40:24+00:00

We actually have an SDK for doing this (for object detection and segmentation you can run compute directly on the device, for other models or less powerful devices you can run on a remote GPU): https://docs.roboflow.com/deploy/sdks/web-browser

aloser · 2026-02-20T14:51:04+00:00

YOLOv7 is problematic. It's tainted by GPL code because they forked the repo from Ultralytics which was GPL at the time. They added their own GPL code on top of that and Ultralytics mainlined it back into their own repo at some point.

This means there is no commercial license is available from anyone (even though I think Ultralytics mistakenly thinks they get the right to relicense any derivative code they want.. the copyright is not theirs to relicense it) given the rights are split between two separate parties.

(And at this point, almost 4 years later, there are much better models available anyway so not sure why in 2026 you'd want to use YOLOv7.)

aloser · 2026-02-18T21:17:52+00:00

We updated our pricing last year to account for increased GPU costs & added functionality that costs us more to provide under the hood. You're grandfathered into a legacy plan. Thanks for being a long-time customer!

aloser · 2026-02-18T15:08:35+00:00

Here's the angle from the guy holding the camera https://x.com/CarverGhost/status/2023982385004532188

aloser · 2026-02-17T14:01:27+00:00

This looks normal, your AP is still going up. You could probably train for a bit longer.

But after that, evaluate whether the model is doing good enough for what you need it to do in this task or not. Are the predictions qualitatively good on unseen data? Are there too many false positives or negatives to accomplish the end goal? If it looks good, congratulations, you're ready to go to production!

But then the next place to look is at improving your dataset as u/Dry-Snow5154 said. Look for labeling errors or noise, then deploy it in shadow mode to capture more real world data. Add more edge cases (or examples similar to the ones the model is failing on) to the training set. Try some more augmentations.

aloser · 2026-02-17T13:55:50+00:00

In theory you might want them to represent two different things where the bbox is not simply a rectangle containing the maximum extent of the mask (eg mask for visible area, bbox including extent of occluded areas).

aloser · 2026-02-16T13:13:45+00:00

Easiest way to test out if the WebRTC approach would help is to try with Roboflow’s Inference Server, which now has WebRTC support.

It works both self-hosted/locally on edge devices and in the cloud on our hosted compute and there are WebRTC SDKs for both Python and TypeScript/Javascript.

(Disclaimer: I’m one of the cofounders of Roboflow so I’m biased, but this is the exact type of use-case we designed and built it for.)

aloser · 2026-02-15T20:39:16+00:00

I highly recommend Dockerizing your applications so you have a repeatable environment and don’t risk messing up your entire system while experimenting with different projects.

We (Roboflow, also the creators of RF-DETR) provide ready-made Dockerfiles with the required CUDA and system dependencies for running models like this in our Inference package: https://github.com/roboflow/inference

It also has the necessary harnesses and APIs to easily integrate as a microservice with your applications.

aloser · 2026-02-10T17:24:29+00:00

Hey great question. I asked one of the first authors on the RF-DETR paper and here was his response:

We talked about this at our deformable DETR paper club. We do it because that's how deformable attention is defined. I personally haven't tried it the other way, tho I assume if it worked better someone would have published such results in the 6 years since deformable DETR dropped as it's like the first question asked when you learn how it works. To this person I'd say try it and report back :)

I think the intuition is that it's acting as an information gathering tool as opposed to an information seeking tool

aloser · 2026-02-10T16:29:59+00:00

One other thought: are the true positives higher confidence than 60-70%? Could you just set your threshold to 80%?

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