Show HN: Image background removal without annoying subscriptions (pixian.ai)
Removing the background from images is a surprisingly common image processing task, and AI has made it really easy. The technology has come a long way since segment leader remove.bg launched here on hn in Dec 2018 [1]. Chasing remove.bg's success, a legion of providers have come on the market offering varying levels of quality & service.
Despite there being a large number of competing services, most still price for very high (~95%?) gross margins. Furthermore, subscriptions make the effective unit price a lot higher than the list price for infrequent users, and requires effort & attention to ensure you're getting value for money. This has prevented a host of use cases (e.g. infrequent professional / hobbyist) and business models (e.g. ad-supported websites & mobile apps).
We see this as an opportunity where we can jump to the market's logical conclusion to gain market share and build goodwill: cost-plus PAYGO pricing, i.e. the "S3 pricing model".
So we've built yet-another image background removal service ( https://pixian.ai - introductory post 6 months ago [2], a ton has been improved since then) but with a couple of twists:
1. Quantified quality comparison (90-120% of remove.bg, depending on image category), free for you to check your own images so you can make an informed choice.
2. Customer-friendly pricing (PAYGO @ 1-10% of competitors' subscriptions) with a generous free tier (and free while in beta).
3. A novel API result format: Delta PNG [3], which offers excellent latency & bandwidth savings. Especially useful for mobile apps.
4. Operational transparency: actual volume & latency metrics public, with more coming soon (all API providers should be showing this).
There's of course more to it than just price and we see several sources of differentiation in this market: quality, price, capability, reliability, latency, and goodwill.
As a new entrant we're looking to meet-or-beat the quality bar; beat on price, capability, reliability and latency; and to build up goodwill over time.
Our goal is to make it a no-brainer for new accounts to choose us, and to provide the tools and guidance necessary for existing accounts to make the switch with confidence.
We'd love for you to try it out and to hear your thoughts!
[1] https://news.ycombinator.com/item?id=18697601 [2] https://news.ycombinator.com/item?id=33439405 [3] https://pixian.ai/api/deltaPng
119 comments
[ 1.0 ms ] story [ 173 ms ] threadIf I can upvote twice, I would.
>Philosophy >While AI is rapidly transforming the way we as a society do business, AI itself is changing even faster. What was >cutting edge only a few years ago is now rapidly becoming commoditized.
>We choose to accept and accelerate this reality.
>We therefore see ourselves less as a tech startup, and more as an outsourced MLOps extension to your engineering team. >Our goal is to be more 'S3' and less 'Adobe' for state-of-the-art AI image processing.
Well done and well said.
Wish many hearths won
Is that intentional?
If you don't want to manually crop it, just press "ok".
That said we could probably improve the messaging in that dialog, thanks!
https://github.com/xuebinqin/U-2-Net
Pretty trivial thing to implement.
How to send and receive image between linux and iphone is left as an exercise for the reader.
Open source implementation of this
That said, I am not negative, only pointing out that at least for me (as a admittedly non-native speaker,) trivial is not a word I would use to describe it.
My use case is mineral photos, as it turns out. And I would be very surprised if the AI had been trained on these. The sad thing is -- mineral photo backgrounds tend to be very simple and smoothly-varying. Should be a slam dunk. Ah well.
A one-shot background remover doesn't give you the opportunity to interact with it and suggest that it got things wrong here and there.
Yes, I tried one of my mineral photos, and the app made several errors that it shouldn't have, as the foreground was clearly distinct from the background.
I don't know if I'm allowed to post a photo link, but here it is: https://imgur.com/a/V9H1pRH .
https://segment-anything.com/demo#
It worked fine on your example with a couple of clicks.
(also, cool shot!)
https://www.photopea.com/tuts/magic-cut-remove-image-backgro...
Even a pre-trained model and self-hosted API like RemBG[0] performs a lot worse than this "pixian" service does.
https://huggingface.co/spaces/KenjieDec/RemBG [0]
All in all, I'd say they put a LOT of effort into scaling (it's FAST) and the models (they're extremely accurate).
>Records not associated with an account are deleted or anonymized within a year of creation. Image processing records associated with an account are retained indefinitely.
>We retain them on your behalf so that you can view and download them as you wish, and to provide customer support.
Thank you, but no thank you.
https://pixian.ai/remove-image-backgrounds says:
> Right now, we retain images and results for five days after they are uploaded, after which they are permanently deleted. Please note that our data retention policies may change over time, and this current policy does not bind us in the future, or require your affirmative consent to change.
https://pixian.ai/policies/terms says:
> User Submissions and any associated Results will expire 2 weeks from the point of upload.
> The Service may provide users with the option to delete User Submissions to have them expire before their normal expiration time.
> Expired User Submissions and any associated Results are subject to deletion or retention at the Company's sole discretion.
https://pixian.ai/policies/privacy
A better solution is to have controls, at least in optional manner, which the user can use to scribble examples of the foreground(s) and backgrounds.
But almost all API users and most regular users just want a result and to not have to futz with it, hence this offering.
auto1111 has a one click installer and these extensions can be installed by going to the "extensions" tab and pasting the github URL into the "install from URL" box. auto1111 available here https://github.com/AUTOMATIC1111/stable-diffusion-webui
It runs from a python script.
Some explanations on the differences of these models would be nice for a noob.
I would think that part of the motivation for releasing the smaller models in addition to the larger ones would be use in video image segmentation and mobile filters. The smaller models might actually be more fit for purpose with regard with regard to those applications than the biggest one. However, I'd reccommend the biggest model (vit_h) for desktop or laptop image processing.
Surprisingly (?) my convoluted setup is slowly becoming this actually useful toolkit for various tasks I sometimes need to do.
1. For "objects" and "artwork" it says that quality is above 100% (108% and 119% respectively), which is weird and doesn't inspire confidence? It's also unclear generally what those percentages mean.
2. When trying this from work it says "Unable to connect to the worker. Is your firewall or proxy blocking WebSockets?" -- it's possible that the firewall is the culprit but there should be a workaround? (All methods give the same result, drag'n drop, ctrl+v, or picking from the explorer).
> Pixian.AI had 241 images that were rated good, or not rated and identical. That's 87.0% of your 277 images.
> The competitor had 201 images that were rated good, or not rated and identical. That's 72.6% of your 277 images.
> Pixian.AI achieved 241 / 201 = 119.9% of the competitor's performance
> The report is based on a set of user-provided images. We then reviewed the services' respective results separately and rated them as either good or bad. The comparison was done in a blind manner, without labels indicating which result was Pixian.AI's and which was the competitor's. We then tallied up the results and produced this report.
https://pixian.ai/comparisons/cwsslt8d78zl7vq/share/5e51cd3d...