Making coloring pages out of your own personal photos is a fun and creative way to engage kids (and adults!) with art. Instead of generic coloring pages, you can turn special memories into custom works of art just waiting to be filled in with color.
My immediate issue, as the father of a mixed son who has just witnessed him spend hours trying to represent his own appearance accurately for an art task at school:
This turns black and mixed people into white-presenting caricatures of themselves. E.g. compare [1] and [2] where the hairstyles of the black people are turned into distinctly "white" hairstyles. My son's hair is closer in texture to that of the man on the right, and there's no way of getting it into the shape of the coloring-in page.
I get there's no ill intent here, but even for far less ethnically ambiguous inputs this "whitewashes" hairstyles and general appearance, and once I saw it I couldn't unsee it.
If my son was the age to want to use this, I'd be concerned about letting him use this, because I know he is sensitive about how he is different to his friends, etc. and this would wildly misrepresent and erase his actual appearance.
This was absolutely my first reaction as well. I scrolled through the first few photos of White families where it seemed to turn even them into 1950s caricatures of "small town White Americans" and thought "hmmm, how's it going to treat Black people?"
I was not at all surprised when it turned Black people into White people.
This to me is one of the clearest examples I've seen of what people talk about when they talk about biases in training data. Clearly the training data of "coloring books" is heavily biased towards "stereotypical 1950s white people" and turns everyone into them.
(And you can add [1] and [2] to your list of comparison images.)
The artistic license thing in itself I think is fine if only it didn't go just one direction. And you may very well be right that the examples it may have seen of coloring books may well be a very peculiar subset.
Another – presumably coincidental – issue with images [1] and [2] is that there is a person missing. I assume that’s not related to skin colour, but to me it adds to the slightly irritating effect of how the resulting images may be disconnected from human reality in ways that would commonly be understood as disrespectful. (Not to speak of the “usual” AI problems, such as additional fingers, stray body parts, etc.)
Thanks for pointing this out, seriously. As a white european guy, I'd probably never have thought of this issue, that's an important reminder about our biases
We use a model but not a diffusion model + controlnet which is what I'm assuming this website does.
Would love any feedback on the results + site [2] – before it's asked: we do not use any user uploaded images for model training, they're only stored to show you the color version of your originally uploaded image
It still has the vibe of janky edge-detection that can be done without AI. Admittedly, less janky than pure edge detection but still not quite smooth enough that I'd pay for the results.
Also, just FYI, asking three different time across these comments for people to check out your site feels a bit spammy to me. I'd suggest you do your own 'Show HN' if you are trying to engage with the community here for feedback.
Honestly, when I first started reading your comment I thought you were being over sensitive but I totally get it looking at pictures 3 and 4. Even 5 and 6 completely changes the hairstyle.
I had to look for multiple examples myself before I was sure I wasn't being oversensitive. As I said, I'm sure there's no ill intent, and in a way I'm not surprised either, because as my son himself found out, if you're going to draw line art - especially with clear, thick lines like this, then accurately representing black or mixed hair without it turning into a caricature that'd be even worse is a skill.
And one that is very likely underrepresented in the training set for no fault of theirs.
And this is why getting diversity "right" (so not the Gemini fiasco way) is hard - you can be extremely well meaning and just not have it register until someone for whom it's personal looks at it.
Feels more likely this is the opposite - the "originals" look like hallucinations.. what is the rear suspension attached to on this "bmw"[0]? Presumably it's supposed to be an R60[1]. It magically has a lot more (accurate) parts in the colouring page[2] (bigger front and back fender, seat, engine gets fins, frame changed shape, tail has license plate holder and signals, the front brake is connected to the leaver via a cable). At least these six fingered people[3] deserve each other - shame she moved her wedding ring, Inigo Montoya seeks them.
I really think this should have GenAI in the title on the webpage or on here, because it's taking the source photo and making best guesses while creating details out of whole cloth. This isn't just "another photo filter", it's instead taking the picture and running with it with sometimes pretty poor results.
For example, I used a random selfie of me on the beach and big rocks in the water, wearing dark sunglasses and mouth closed.
Watercolor: Added eyes to my glasses (!). The rocks and water turned green, and it looked like I was standing in a park.
Coloring Page: Ferns and trees added that weren't there before.
Both: Gave me a teethy smile when my lips were closed.
The examples on the home page must have been extremely handpicked because I'm not seeing anything to that same fidelity.
When I saw this posted late last night, I was pretty excited since I have kids, but then realized it's just determining the basic idea of what it sees in the photo, and then drawing a new image from scratch that has those elements. What I wanted is something that takes the original photo and removes things from the image until we're left with some basic line drawings, so that the people in the coloring book actually look like the people in the photo! Their examples very obviously show how different the resulting image is from the original. If Google allowed you to search by saying "Find me a coloring book image where a dad is sitting behind 2 kids with his arms around them, and the daughter is on the left and the son is on the right" then we'd end up with results almost as good.
I'm no Photoshop expert, but someone else in this discussion pointed out that Photoshop has some filters or other tools that do edge detection and can yield much more accurate results. If the techniques could be replicated in a SaaS then you'd have a much better product. Of course, if it could be done in a desktop Mac app or an iOS app, I might choose that for privacy reasons.
> If Google allowed you to search by saying "Find me a coloring book image where a dad is sitting behind 2 kids with his arms around them, and the daughter is on the left and the son is on the right" then we'd end up with results almost as good.
I've been using Stable Diffusion, and more recently Bing (app) and now GPT-4/Dall-E 3 (ChatGPT app) for that very purpose, with quite good success rate. It's perfect for when my daughter randomly asks me for a coloring page with a dancing vacuum cleaner or such. Dall-E is quite good at this, all you need to do is tack "in the style of a children coloring book" or such to the end of your prompt.
Heh, I used a photo of myself sitting on the couch with my chihuahua looking up at me over my laptop screen and it replaced her with a St Bernard. The hallucination is strong in this one.
According to whom? There’s just that sentence, surrounded by laurel leaves, above five stars. Zero indication of where that award/rating came from. Did you make it up?
When I was just starting out I made a similar app (https://github.com/rmdocherty/buck3t) using classic computer vision operations like k-means and Canny edge detection rather than (I assume) ML. It also lets you fill in the returned coloring page in the browser.
It’s simple and works relatively well but is prone to fail on high frequency objects like foliage, where the ML approach appears to a) succeed and b) stylise (seems to cause problems).
The free trial on the cloud function expired so the web app doesn’t work and the source JS code is awful but someone (maybe me) could pretty easily rewrite the cloud function into a flask server to allow local hosting.
Same here - I had a web-based system that let you do coloring pages, paint-by-number, cross-stitch patterns, etc... and it all worked in the web session. While adding an AI element does give improvements over my results. I'm not sure those improvements are worth being prompted for my email, waiting even longer for results, the results not being 100% true to the original content, and not having those results just show on-screen.
Use a personal domain with a default address that filters to a mailbox then use a different email address for every site you use. This plus random passwords from a password manager contains the privacy leakage, blast radius of credential loss, and keeps your mail spam free.
IMO your FAQ needs an entry for: when you store uploaded photos, what will they be used for. Will my uploaded photos be used as training data for your AI models for example?
The coloring page that should have shown my son and daughter sitting on a bench that looked like a bear waving magic wands… turned my son into a girl with Princess Leia hair, and my daughter into a anthropomorphized bear, no wands.
Fun, but it’s no longer a special memory. There’s so little tying the source and result.
This turns black and mixed people into white-presenting caricatures of themselves. E.g. compare [1] and [2] where the hairstyles of the black people are turned into distinctly "white" hairstyles. My son's hair is closer in texture to that of the man on the right, and there's no way of getting it into the shape of the coloring-in page.
I get there's no ill intent here, but even for far less ethnically ambiguous inputs this "whitewashes" hairstyles and general appearance, and once I saw it I couldn't unsee it.
If my son was the age to want to use this, I'd be concerned about letting him use this, because I know he is sensitive about how he is different to his friends, etc. and this would wildly misrepresent and erase his actual appearance.
[3] and [4] is another stark example.
[5] and [6]....
[1] https://portraitart.app/static/gallery/group1_original_1024....
[2] https://portraitart.app/static/gallery/group1_coloring_page_...
[3] https://portraitart.app/static/gallery/portrait4_original_10...
[4] https://portraitart.app/static/gallery/portrait4_coloring_pa...
[5] https://portraitart.app/static/gallery/basketball2_original_...
[6] https://portraitart.app/static/gallery/basketball2_coloring_...
I was not at all surprised when it turned Black people into White people.
This to me is one of the clearest examples I've seen of what people talk about when they talk about biases in training data. Clearly the training data of "coloring books" is heavily biased towards "stereotypical 1950s white people" and turns everyone into them.
(And you can add [1] and [2] to your list of comparison images.)
1. https://portraitart.app/static/gallery/father1_original_1024...
2. https://portraitart.app/static/gallery/father1_coloring_page...
[1]: https://portraitart.app/static/gallery/group1_original_1024....
[2]: https://portraitart.app/static/gallery/group1_coloring_page_...
We use a model but not a diffusion model + controlnet which is what I'm assuming this website does.
Would love any feedback on the results + site [2] – before it's asked: we do not use any user uploaded images for model training, they're only stored to show you the color version of your originally uploaded image
[1] https://static.dreamandcolor.com/aa828ad1-5696-4d4e-95eb-bcd...
[2] https://dreamandcolor.com/
Also, just FYI, asking three different time across these comments for people to check out your site feels a bit spammy to me. I'd suggest you do your own 'Show HN' if you are trying to engage with the community here for feedback.
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And one that is very likely underrepresented in the training set for no fault of theirs.
And this is why getting diversity "right" (so not the Gemini fiasco way) is hard - you can be extremely well meaning and just not have it register until someone for whom it's personal looks at it.
[0]: https://portraitart.app/static/gallery/motorcycle1_original_... [1]: https://wallup.net/1960-bmw-r60-classic-bike-motorbike/ [2]: https://portraitart.app/static/gallery/motorcycle1_coloring_... [3]: https://portraitart.app/static/gallery/wedding1_coloring_pag...
[1]: https://www.pexels.com/photo/orange-and-black-bmw-motorcycle...
For example, I used a random selfie of me on the beach and big rocks in the water, wearing dark sunglasses and mouth closed.
Watercolor: Added eyes to my glasses (!). The rocks and water turned green, and it looked like I was standing in a park. Coloring Page: Ferns and trees added that weren't there before. Both: Gave me a teethy smile when my lips were closed.
The examples on the home page must have been extremely handpicked because I'm not seeing anything to that same fidelity.
I'm no Photoshop expert, but someone else in this discussion pointed out that Photoshop has some filters or other tools that do edge detection and can yield much more accurate results. If the techniques could be replicated in a SaaS then you'd have a much better product. Of course, if it could be done in a desktop Mac app or an iOS app, I might choose that for privacy reasons.
I've been using Stable Diffusion, and more recently Bing (app) and now GPT-4/Dall-E 3 (ChatGPT app) for that very purpose, with quite good success rate. It's perfect for when my daughter randomly asks me for a coloring page with a dancing vacuum cleaner or such. Dall-E is quite good at this, all you need to do is tack "in the style of a children coloring book" or such to the end of your prompt.
According to whom? There’s just that sentence, surrounded by laurel leaves, above five stars. Zero indication of where that award/rating came from. Did you make it up?
https://colorbliss.art
It’s simple and works relatively well but is prone to fail on high frequency objects like foliage, where the ML approach appears to a) succeed and b) stylise (seems to cause problems).
The free trial on the cloud function expired so the web app doesn’t work and the source JS code is awful but someone (maybe me) could pretty easily rewrite the cloud function into a flask server to allow local hosting.
Fun, but it’s no longer a special memory. There’s so little tying the source and result.
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