[HN Gopher] Color-Diffusion: using diffusion models to colorize ... ___________________________________________________________________ Color-Diffusion: using diffusion models to colorize black and white images Author : dvrp Score : 101 points Date : 2023-08-03 20:24 UTC (2 hours ago) (HTM) web link (github.com) (TXT) w3m dump (github.com) | buildbot wrote: | Does it work on arbitrary image sizes? | | One of the nice features of the somewhat old Deoldify colorizer | is support for any resolution. It actually does better than | photoshops colorization: https://blog.maxg.io/colorizing- | infrared-images-with-photosh... | | Edit - technically, I suppose, the way Deoldify works is by | rendering the color at a low resolution and then applying the | filter to a higher resolution using OpenCV. I think the same sub- | sampling approach could work here... | erwannmillon wrote: | Technically yes, the encoder and unet are convolutional and | support arbitrary input sizes, but the model was trained at | 64x64px bc of compute limitations. You could probably resume | the training from a 64x64 resolution checkpoint and train at a | higher resolution. | | But like most diffusion models, they don't generalize very well | to resolutions outside of their training dataset | asciimov wrote: | I'm not a fan of b&w colorization. Often the colors are wrong, | either outright color errors (like choices for clothing or cars) | or often not taking in to account lighting conditions (late in | day shadows but midday brightness). | | Then there is the issue of B&W movies. Using this kind of tech | might not give pleasing results as the colors used for sets and | outfits were chosen to work well for film contrast and not for | story accuracy. That "blue" dress might really be green. (Please, | just leave B&W movies the way they are.) | zamadatix wrote: | I think colorization with some effort put in can be pretty | decent. E.g. I prefer the 2007 colorization of It's a Wonderful | Life to the original. It's never perfect but I don't think | that's a prerequisite to being better. Some will always | disagree though. | | About every completely automated colorized video tends to be | pretty bad though. Particularly the YouTube "8k colorized | interpolated" kind of low effort channels where they just let | them pump out without caring if it's actually any good. | iamflimflam1 wrote: | I wonder if this can be used for color correction in videos. | erwannmillon wrote: | Btw, I did this in pixel space for simplicity, cool animations, | and compute costs. Would be really interesting to do this as an | LDM (though of course you can't really do the LAB color space | thing, unless you maybe train an AE specifically for that color | space. ) | | I was really interested in how color was represented in latent | space and ran some experiments with VQGAN clip. You can actually | do a (not great) colorization of an image by encoding it w/ | VQGAN, and using a prompt like "a colorful image of a woman". | | Would be fun to experiment with if anyone wants to try, would | love to see any results if someone wants to build | xigency wrote: | Question, how long did it take to train this model and what | hardware did you use? | carbocation wrote: | > _I did this in pixel space for simplicity, cool animations, | and compute costs_ | | A slight nitpick, wouldn't doing diffusion in the latent space | be cheaper? | data-ottawa wrote: | Off topic: this has an absolutely 90's sci-fi movie effect | watching the gifs, it's funny how the tech just wound up looking | like that. | erwannmillon wrote: | hahaha it reminded me of some "zoom and enhance" stuff when I | was making the animations | nerdponx wrote: | Looks like something you'd see in an X Files episode. | barrkel wrote: | It reminded me of the days of antenna pass-through VCR | players, where you had to tune into your VCR's broadcast | signal when you couldn't use SCART. | snvzz wrote: | All the examples are portraits of people. | | I have to wonder whether it works well with anything else. | erwannmillon wrote: | trained on celebA, so no, but you could for sure train this on | a more varied dataset | Eisenstein wrote: | Would it be as simple as feeding it a bunch of decolorized | images along with the originals? | atorodius wrote: | yes, so infinite training data. but the challenge will be | scaling to large resolutions and getting global consistency | jrockway wrote: | Is that challenging? Humans have awful color resolution | perception, so even if you have a huge black-and-white | image, people would think it looks right with even with | very low-resolution color information. Or, if the AI | hallucinates a lot of high frequency color noise, it | wouldn't be noticable. | | Wikipedia has a great example image here: | https://en.wikipedia.org/wiki/Chroma_subsampling. Most | people would say all of them looked fine at 1:1 | resolution. | atorodius wrote: | I meant more from a comoute standpoint, the models are | expensive to run full res | jrockway wrote: | I see what you mean. I think that you can happily scale | the B&W image down, run the model, and then scale the | chroma information back up. | | Something I was thinking about after writing the comment | is that the model is probably trained on chroma- | subsampled images. Digital cameras do it with the bayer | filter, and video cameras add 4:2:0 subsampling or | similar subsampling as they compress the image. So the AI | is probably biased towards "look like this photo was | taken with a digital camera" versus "actually reconstruct | the colors of the image". What effect this actually has, | I don't know! | atorodius wrote: | good point, I hadn't realized that you only need to | predict chroma! That actully greatly simplifies things | | re. chroma subsampling in training data: this is actually | a big problem and a good generative model will absolutely | learn to predict chroma subsampled values (or JPEG | artifacts even!). you can get around it by applying | random downscaling with antialiasing during training. | drapado wrote: | I guess you can always use a two-stage process. First | colorize, then upscale | atorodius wrote: | yeah, you can use SOTA super res, but that tends to be | generative too (even diffusion based on its own, or more | commonly based on GANs). it can be a challenge to | synthesize the right high res details. | | but that's basically the stable diffusion paper | (diffusion in latent space plus GAN superres) | erwannmillon wrote: | basically the training works as follows: Take a color image | in RGB. Convert it to LAB. This is an alternative color | space where the first channel is a greyscale image, and two | channels that represent the color information. | | In a traditional pixel-space (non latent) diffusion model, | you noise all the RGB channels and train a Unet to predict | the noise at a given timestep. | | When colorizing an image, the Unet always "knows" the black | and white image (i.e the L channel). | | This implementation only adds noise to the color channels, | while keeping the L channel constant. | | So to train the model, you need a dataset of colored | images. They would be converted to LAB, and the color | channels would be noised. | | You can't train on decolorized images, because the neural | network needs to learn how to predict color with a black | and white image as context. Without color info, the model | can't learn. | coldtea wrote: | > _You can 't train on decolorized images, because the | neural network needs to learn how to predict color with a | black and white image as context. Without color info, the | model can't learn._ | | I think the parent means with delocorized images used to | test the success and guide the training (since they can | be readily compared with the colored image they resulted | from which would be the perfect result). | | Not to use decolorized images alone to train for coloring | (which doesn't even make sense). | omoikane wrote: | Is there a reason for using LAB as opposed to YCbCr? My | understanding is that YCbCr is another model that | separates luma (Y) from chroma (Cb and Cr), but JPEG uses | YCbCr natively, so I wonder if there would be any | advantage in using that instead of LAB? | TylerE wrote: | The Y in YCbCr is linear, and is just a grayscale image. | The L channel in lab is non-linear (as are A and B), and | is a complex transfer function designed to mimic the | response of the human eye. | | A YCbCr colorspace is directly mapped from RGB, and thus | is limited to that gamut. | | LAB can encode colors brighter than diffuse white (ala | #ffffff), like an outdoor scene in direct sunlight. | | Sorta HDR (LAB) vs non-HDR (YCbCr). | | This image (https://upload.wikimedia.org/wikipedia/common | s/thumb/f/f3/Ex...) is a good demo, left side was | processed in LAB, right in YCbCr). Even reduced back down | to a jpeg, the left side is obviously more lifelike, | since the highlights and tones were preserved until much | later in processing pipeline. | atorodius wrote: | You can take arbitrary images and convert them to | grayscale for training, and do conditional diffusion | bemusedthrow75 wrote: | But convert them to grayscale how? | | Black and white film doesn't have one single colour | sensitivity. Play around with something like DxO FilmPack | sometime (it has excellent measurement-based | representations of black and white film stocks). | | It's a much more complex problem than it might seem on | the surface. | atorodius wrote: | fair, but can't you just randomize the grayscale | generation for training? | bemusedthrow75 wrote: | But since you do not have access to colour originals of | historical photos in almost every instance, you cannot | possibly train the network to have any instinct for the | colour sensitivity of the medium, can you? | | An extreme example: | | https://www.cabinetmagazine.org/issues/51/archibald.php | | https://www.messynessychic.com/2016/05/05/max-factors- | clown-... | | Colourising old TV footage can _only_ result in a | misrepresentation, because the underlying colour is false | to have any kind of usable representation on the medium | itself. | | And this caricatured example underpins the problem with | colourisation: contemporary bias is unavoidable, and can | be misleading. Can you take a black and white photo of an | African-American woman in the 1930s and accurately colour | her skin? | | You cannot. | [deleted] | dragonwriter wrote: | > Can you take a black and white photo of an African- | American woman in the 1930s and accurately colour her | skin? | | AI colorization will, in general, be _plausible_ , not | _accurate_. | morelisp wrote: | In other words, bullshit. | snvzz wrote: | The original color information just isn't there. | | So bullshit is the best you're going to get. | morelisp wrote: | Well, you could also _not put more bullshit in the world | by not doing the thing._ | roywiggins wrote: | People have been colorizing photos as long as there have | been photos. | wruza wrote: | Why are you so negative about it? Pretty sure many people | would find it impressive to colorize old photos to look | at them as if these were taken in color. | | Should artists not put their bs in the world? Writers? | Musicians? Most of it is made up but plausible to make | you feel something subjective. | dragonwriter wrote: | No more so than any other colorization method that isn't | dependent on out-of-band info about the particular image | (and even that is just more constrained informed | guesswork.) | | That's what happens when you are filling in missing info | that isn't in your source. | | EDIT: Of course, color photography can be "bullshit" | rather than accurate in relation to the actual colors of | things in the image; as is the case with the red, blue, | and _green_ (actual colors of the physical items) | uniforms in Star Trek: The Original Series. But, also | fairly frequently, lots of not-intentionally-distortive | reproductions of skin tones (often most politically | sensitive in the US with racially non-White subjects, | where there are also plenty of examples of _deliberate_ | manipulation.) | morelisp wrote: | Showing color X on TVs by actually making the thing color | Y in the studio, well, _filming_ , not bullshit. It's an | intentional choice playing out as intended. It is meant | to communicate a particular thing and does so. | dragonwriter wrote: | That particular thing was _not_ intentional, and is the | reason why the (same color in person, different material) | command wrap uniform that is supposed to be color-matched | to the made-as-green uniforms isn't on screen. | | But, yes, in general inaccurate color reproduction can be | intentionally manipulated with planning to intentionally | create appearances in photos that do not exist in | reality. | jackpeterfletch wrote: | _shrug_ people like looking at colorised photos because | it helps root the image within the setting of the real | world they occupy. | | For some it's more evocative, irregardless of the | absolute accuracy. | | Having a professional do it for that picture of your | great grandad is expensive. | | Having a colourisation subreddit do it is probably worse | for accuracy. | | I think there is a place for this bullshit. | erwannmillon wrote: | Yeah, the model is racist for sure. That's a limitation | of the dataset though (celeb A is not known for its | diversity, but it was easy for me to work with, I trained | this model on Colab) | | And plausibility is a feauture, not a bug. | | There are always many plausibily correct colorizations of | an image, which you want the model to be able to capture | in order to be versatile. | | Many colorization models introduce additional losses | (such as discriminator losses) that avoid constraining | the model to a single "correct answer" when the solution | space is actually considerably larger. | atorodius wrote: | This is true, but if you have some reference images, you | can probably adapt some of the recent diffusion | adaptation work such as DreamBooth, to tell the model | ,,hey this period looked like this", and finetune it. | | https://dreambooth.github.io/ | ChrisArchitect wrote: | Author's writeup on this from May: | https://medium.com/@erwannmillon/color-diffusion-colorizing-... | aziaziazi wrote: | How much would it cost to colorize a movie with a fork of this? | morelisp wrote: | [flagged] | NBJack wrote: | I think the bigger question is would it be stable enough. Many | SD like models struggle with consistency across multiple images | (i.e. frames) even when content doesn't change much. Would he a | cool problem to see tackled. | erwannmillon wrote: | temporal coherence is def an issue with these types of | models, though I haven't tested it out with ColorDiffusion. | Assuming you're not doing anything autoregressive (from frame | to frame) to do temporal coherence, you can also parallelize | the colorization of each frame, which would affect cost. | | Tbh most cost effective would be a conditional GAN though | lajamerr wrote: | Change up the model. That allows it to see previous frames | and 1-2 future frames. | | Then train the model on movies that are color and then turn | them black and white. | | That way you can train temporal coherence. | leetharris wrote: | Quick math: | | 24 frames per second * 60 seconds per minute * 90 minute movie | length = 129600 frames | | If you could get cost to a penny per frame, about $13k? But I'd | bet you could easily get it an order of magnitude less in terms | of cost. So $1500 or so? | | And that's assuming you do 100% of frames and don't have any | clever tricks there. | caturopath wrote: | I'm willing to bet that if you just treated each frame as an | image, it would result in some weird stuff when you played | them as a movie. | | > penny per frame | | Where did this come from? | leetharris wrote: | I do lots of large scale ML work, this was just sort of a | random educated "order of magnitude" guess. | jurassic wrote: | This is a cool party trick, but I don't see a need for this in | any real applications. Black and white is its own art form, and a | lot of really great black and white images would look like | absolute garbage if you could convert them to color. This is | because the things that make a great black and white image | (dramatic contrasts, emphasis on shape/geometry, texture, etc) | can lose a lot of their impact when you introduce color. Our | aesthetic tolerance for contrast seems significantly reduced in | color because our expectations for the image are more anchored in | how things look in the real world. And colors which can be very | pleasing in some images are just distracting in others. | | So all this is to say.... I don't think there would be commercial | demand to, say, "upgrade" classic movies with color. Those films | were shot by cinematographers who were steeped in the black & | white medium and made lighting and compositional choices that | take greatest advantage of those creative limitations. | [deleted] | dragonwriter wrote: | > I don't think there would be commercial demand to, say, | "upgrade" classic movies with color. | | There was, and maybe there will be again once we get far enough | from the consumer burnout from the absolute deluge of that in, | mostly, the 1980s-1990s. | | https://en.m.wikipedia.org/wiki/List_of_black-and-white_film... | simonw wrote: | I've run colorization like this against historic photographs | and it had a very real impact on me - I found myself able to | imagine life when the photo or video was taken much more easily | when it was no longer in black and white. | | Here's an example I really enjoyed, of a snowball fight in | 1896: | https://twitter.com/JoaquimCampa/status/1311391615425093634 | bemusedthrow75 wrote: | > I don't think there would be commercial demand to, say, | "upgrade" classic movies with color. | | Alas there has been serious money in this in the past (VHS and | as I understand it US cable TV). | | I would not assume that we have more taste now than we did | then. (The state of cinema suggests the opposite to me at | least.) | MrVandemar wrote: | Some of the old Doctor Who stories that were filmed in colour | they only have black and white copies of. The colourisations | have been ... very good, better than I would have thought, but | not perfect. Could be an a good application. | pythonguython wrote: | Counterexample: They Shall Not Grow Old, a WW1 documentary film | with mostly colorized footage with recreated audio. The film | was commercially successful and I found it to be a great watch. | bemusedthrow75 wrote: | Colourising old photographs is the banal apotheosis application | of diffusion AI. | | It's the pinnacle of the whole thing: "imagine it for me in a way | that conforms to my contemporary expectations". | | If you're going to colourise images, have the decency to do it by | hand. If possible on a print with brushes. | | Edit: didn't think this would be popular. Maybe it's the | historical photography nerd in me, but colourising images without | effort and thought is like smashing vintage glass windows for the | fun of it: cultural vandalism. | crazygringo wrote: | If you're going to write code, have the decency to do it on | punch cards. If possible by hand punching, rather than using a | keypunch machine. | bemusedthrow75 wrote: | This isn't the point I am making. | | The point I am making is that colourisation is subjective | art, and that alone. | | Colourisation cannot fail to enforce contemporary biases | based on poor understanding of the materials. It will darken | or lighten skin inappropriately, and mislead in any number of | ways. | | Doing it by hand (in photoshop or on a print) acknowledges | the inherent bias that is involved in colourisation. | | Automating it is banal at best and dangerous at worst; | colourised images risk distorting history. | dragonwriter wrote: | > Doing it by hand (in photoshop or on a print) | acknowledges the inherent bias that is involved in | colourisation. | | No, doing it by hand doesn't acknowledge that your | interpretation is a fallible interpretation shaped by bias, | just like translating a written work (e.g., the Bible, for | a noted example where this has been done often without any | such acknowledgement being conveyed) by human effort | doesn't do that. | | Acknowledging bias in translation of either kind is _an | entirely separate action_ , orthogonal to the method of the | translation itself. | geon wrote: | How can it affect the lightness channel when it is locked? | bemusedthrow75 wrote: | The point is that the source black and white image is not | truthful about skin colour. The film locks in a level of | lightness but that lightness may be very wrong (depending | on the red and blue sensitivity of the film, the colour | of the light, the time of day, the print, whether a | filter was being sued). | | So if you colourise an image of someone who appears to be | a light-skinned 1930s African-American with colours that | appear to conform to our contemporary understanding of | light-skinned Black people of our era, you might be | getting it right, of course. | | But you might be getting it quite, quite wrong, in a way | that matters. | coldtea wrote: | > _Automating it is banal at best and dangerous at worst; | colourised images risk distorting history_ | | Well, faces still have a certain tint, the sky is mostly | blue, the grass green, water is blue, mud pools are brown, | the ground too, a lot of historical fabrics are certain | inherent colors, known flowers have known colors, | brownstones have red/brown color. A lot of it, is just not | that subjective. | | Besides different color film stock (or camera sensor "color | science") can already result in dozens of widely different | colorings of the same exactly scene. | bemusedthrow75 wrote: | > Well, faces still have a certain tint | | Do they? A _certain_ tint? | | You _cannot_ accurately colourise skin from photographic | film without an _enormous_ amount of knowledge of the | taking and processing of the film, and of the lighting | and subject. | | An AI can't do it any better than a painter. You can't | take a scan of a print or a negative and get skin tones | right. | | Think about how weird the skin tones are from scans of | wet-plate photography plates compared to the same process | used in antiquity with the aim of producing a carbon | print. | coldtea wrote: | > _Do they? A certain tint?_ | | Yes. There's just not a single one across all faces - but | I wasn't meaning that. | | What I mean is, we know the kind of tints a face will | have. A face is not suddenly going to be blue or green or | poppy red. And by how light a black and white face | appears, we can tell quite well if it's a darker one | (oilish to brown) or lighter (pinkish towards more pale). | | If we get it wrong within a range it's no big deal. Color | film stocks would also vary it widely. | | Hell, even actual people who met the person we colourise | in real life will remember (or even experience in real | time) their face's hue somewhat differently each. | bemusedthrow75 wrote: | But how brown? How pink? How light? How dark? | | This is an enormously important issue. | | Black and white films of different technologies and | manufacturers and eras actually lighten or darken skin | tones. Really _very_ significantly. | | And it's not going to be obvious from the final positive, | unless there's _extensive_ data with those images about | how the photography was done. And there never is. | | Editing because I can no longer reply: the question of | whether a skin tone is a dark one or a light one has had | severe real life impacts on people whose lives are now | only represented in photographs. You can't write this off | as micromanagement; it's about the ethics of | representation. | coldtea wrote: | > _But how brown? How pink? How light? How dark? This is | an enormously important issue_ | | Is it? | | If 2 colour film stocks took the same image of them, it | would show their hue a little (or a lot) different. | | Even if two different people actually met the same | person, they will probably describe their face as | slightly different tones from memory. (And let's not even | get into different types of color-blindness they could | have had). | | Hell, a person's hue will even look different to the same | person looking at them, in real time, depending on the | changes in lighting and the shade at the scene as they | talk (e.g. sun behind clouds vs directly sun vs shade vs | bulbs). | | It's not really "enormously important" to micromanage the | (non-existent) exact right brown or right pink. | PartiallyTyped wrote: | > Automating it is banal at best and dangerous at worst; | colourised images risk distorting history. | | There's a lot of irony in acknowledging this but not | acknowledging that each and everyone of us has their own | biases inherent to our perception and experiences. | | Like the blue and white dress; we all perceive things | differently even on identical images, monitors, screens, | etc. | crazygringo wrote: | > _Colourisation cannot fail to enforce contemporary biases | based on poor understanding of the materials. It will | darken or lighten skin inappropriately, and mislead in any | number of ways._ | | If anything, an AI trained on a large and diverse dataset | is probably going to wind up being much _more_ accurate | with regards to skin color than a human colorist would be | in most cases. | | The problem here isn't whether colorization is done by man | or machine; it's just ensuring that colorized photos are | identified as such. Which they usually are -- that's not a | new problem to be solved. | bemusedthrow75 wrote: | No it's not, not really. | | A diverse data set of black and white images doesn't have | any kind of knowledge of the colour sensitivity of the | medium in that moment. | | What film was it? How was it processed? Is it a scan of a | negative or a print? What was the colour of the lighting? | Was a particular colour tint filter used on the lens? Was | the subject wearing makeup optimised for black and white | photography? | | The black and white image, standing alone, cannot tell | you this, I think. Sure, it might get a bit better at, | say, identifying a 1950s TV show. But what is the | "correct" accurate colour representation of that scene, | when televisual makeup was wildly unnatural in colour? | crazygringo wrote: | But do people have any of that knowledge either? Most of | the time, I don't think so -- they colorize stuff in a | way that just "looks right" or "looks natural" or "looks | nice" to their eye, that's all. | | And the dataset an AI is going to train on should be | using original color photos that are then converted to | B&W across a wide variety of color curves. So it should | be fairly robust to all sorts of film types. So again, I | repeat that it's probably going to wind up being _more_ | accurate with regard to skin tone than a human (with | their aesthetic biases) usually would. | bemusedthrow75 wrote: | > But do people have any of that knowledge either? Most | of the time, I don't think so -- they colorize stuff in a | way that just "looks right" or "looks natural" or "looks | nice" to their eye, that's all. | | No, indeed. Which is why doing it by hand is more | respectful of the notion that it is subjective. | | Automatic colourisation is and will be viewed | differently, as more "scientific", when it's still | absolutely beholden to the same biases and maybe | misconceptions that we can't unpick because they come | from poor training data. | | Finally: "original colour photos" are also a problem. Not | only for the part of the history where they don't exist. | But also for the part of history (until the early 1960s) | when the colour rendition of those photos was false or | incomplete. You can get a little closer to understanding | what that colour looked like, but it's important to | understand that colour emulsions vary in the way they | work: it's not black and white film with extra colour | sensitivity. | | So at best you will be colourising the black and white | film to look like the colour film, which is not reality. | And there are well-understood problems with correct | representation of skin tones with colour film until the | mid-eighties. | | I can see your point; I just think there's a bigger | picture here (pun not intended) that you're not seeing. | crazygringo wrote: | > _Automatic colourisation is and will be viewed | differently, as more "scientific"_ | | Then the solution is to correct that misperception, not | deny ourselves a useful tool. | | > _I can see your point; I just think there 's a bigger | picture here (pun not intended) that you're not seeing._ | | My overarching point is that this is a tool like any | other. And the idea that "doing it by hand is more | respectful of the notion that it is subjective" I will | push back on 100%. | | There is nothing disrespectful about colorizing a photo, | automatically or by hand. But it should always be clearly | communicated that it is subjective not objective, whether | human or machine. | | Again, if someone believes the colorization is somehow | "real" or "scientific" because a computer did it, then | correct their misbelief. Don't stop using the tool. | That's the bigger picture here. | erwannmillon wrote: | Fair enough. Honestly this was just a fun side project. I | actually coded this up last october when I was doing a deep | dive to learn about diffusion models, and saw that no one | had ever applied them to colorization. This was just a fun | opportunity to build a project that no one had done before | pkoiralap wrote: | Making music without actually knowing anything about it is the | banal apotheosis application of Generative AI. - Music nerd in | me | | Creating art without actually knowing anything about it is the | banal apotheosis application of Diffusion AI. - Artist in me | | Using ChatGPT to write essays that are better than anyone could | have ever written is the banal apotheosis application of LLMs - | Teacher in me | | It is already here. Better use, appreciate, and try to | understand how it works rather than complaining about it doing | a better job. In this instance, for example, the model can be | made to generate multiple outputs or even better, generate | output based on precise user input. | bemusedthrow75 wrote: | I'm actually concerned it is doing a _worse_ job, in | important ethical ways, than a hand colourist. But I 've | explained elsewhere. | | Colourisation cannot be done accurately from a black and | white image without context that is almost always lacking. | Hand colouring is _less_ dishonest. | dragonwriter wrote: | > But since you do not have access to colour originals of | historical photos in almost every instance, you cannot possibly | train the network to have any instinct for the colour | sensitivity of the medium, can you? | | Plenty of people say that about colorization period, which, | while I disagree, seems more sensible than your position to me, | which just seems to be fetishizing suffering. | coldtea wrote: | When did colorizing images become an "art"? | | What if the "effort" way is less accurate? | vorpalhex wrote: | There is a community of people who carefully recolor | historical photos by hand. It's really beautiful time | consuming work and often they invest heavily to get the | colors to be correct. | bemusedthrow75 wrote: | The effort is obviously going to be less accurate. | | But it reflects the fact that an accurate colourisation of a | black and white image without access to every possible detail | about the scene and processing from the photographer's | perspective is impossible. | | Black and white film is substantially more complex and varied | than people understand. Its sensitivities are complex and | vary from processing run to processing run, and people at the | time knew of the weaknesses of black and white and often used | false colour to get an acceptable rendition. | | Colourisation is a form of expression, not a form of | recovery. | coldtea wrote: | > _But it reflects the fact that an accurate colourisation | of a black and white image without access to every possible | detail about the scene and processing from the photographer | 's perspective is impossible._ | | Accurate colourisation is impossible even in a color | photograph. There is no "canonical" film stock that | accurately represents all actual real-life colors. | | The expectation from colourisation is not an accurate | representation of the original colors, but a good | application of color based on our knowledge (whether from | historical facts a human colorist knows or from training | with similar objects and materials a NN did) that matches a | realistic representation of the scene. | | If a human colourist draws a dress and doesn't know the | color of it, nor have they any historical information about | what the person depicted wore that day, they're going to | take a guess. That's kind of what the NN will do as well. | vorpalhex wrote: | I think a lot of it depends on what you are doing and why. | | Yes, recolors can be inaccurate but they can make historical | moments feel more alive and connected. At the same time one can | imagine the issues of a recolor that is inaccurate and that is | troubling with historical photographs. | | At the same time I have a bunch of old family photos I'd love | to recolorize. Maybe the colors won't be quite right but that's | an OK failure mode for family photos! | | I'd love to see a version where you can drop just a spot or two | of the correct color and let the AI fill it out. My grandmother | had stark red hair but most algorithms will color her as a | blond. It'd be nice to fix that, using one of the color photos | we do have. | erwannmillon wrote: | You can do this with spatial palette t2i or controlnet. Give | a super lores spatial palette as conditioning like this: http | s://camo.githubusercontent.com/8e488996fd309165fb065b0cd... | | https://github.com/TencentARC/T2I-Adapter | geon wrote: | How was anything destroyed? the original grayscale is still | there. | bemusedthrow75 wrote: | Colourised images absolutely replace mono images in image | searches, unfortunately; I've seen this again and again. It | gets more difficult to find originals. | | But also you have to consider that bias is being introduced | in the colour rendition. That causes damage. | | For example, you could see a photograph of an African | American woman in the 20s or 30s, and your AI would say, this | is an African American woman and colour her skin in some way. | | But a lighter-skinned-looking African American woman in a | pre/early-post-war photo is a challenge. She may have had | darker skin -- been unable to "pass" -- and the film simply | didn't get that across because of its colour sensitivity. | | Or she may actually have been light-skinned and able to | "pass" (or wearing makeup that helped). | | Automatically colouring that image introduces risks to the | reading of history; you can read that woman's entire life | completely wrong. | | It's also common with photos of men from that era who worked | outdoors. Many of them will come across much darker-skinned | in photos than they actually would have appeared in real | life, because not-readily-visible sun damage can look odd in | mono. But if you colourise all those sun-baked people the | same way, what happens to those of mixed heritage among them? | (A thing that is already rather "airbrushed out" of history.) | | Without knowing about the lighting, the material, the | processing and the source of the positive (is it a negative | scan? was it a good one? or is it a scan of a print?) you | cannot make accurate impressions of skin tone. | | And given the power and importance of photography in the | history of the USA in particular -- photography coincides | with and actually helps define the modern unified US self- | image -- this is not something to blaze through without care. | | This is a far less tricky problem in more homogeneous | societies, obviously. But even then, there is this perception | from photographs that British women in the 1920s were all | deathly pale; colourisation preserves that illusion that | actually comes in part from photographic style. | mrkeen wrote: | Nice, I'll have to try smashing vintage glass windows. Thanks | for the tip! | erwannmillon wrote: | touche, nevertheless, colors go brrrrrrrr | bemusedthrow75 wrote: | Don't get me wrong. It's impressive technology. I'm amazed at | what it can do. | | Also horrified. ___________________________________________________________________ (page generated 2023-08-03 23:00 UTC)