7 ms·

Video encoding requires using your eyes

92 points by zdw 2y ago

okramcivokram 2y ago
I don't see (or maybe don't recognize) any issues with the image that they're talking about (ringing, color shift, or fake details). It most certainly doesn't look awful to me, it looks exactly the same, only a bit sharper.
- SG- 2y ago
  the fact that it looks different is the problem.
- sgarland 2y ago
  It’s mostly only visible in the closeup of the kid. There are hairs that have been unnecessarily accentuated, and his eye and eyebrow outline look hyper-sharpened, with rough edges. The non-zoomed image looks fine to me, and I (to some extent) know what I’m looking for. Some private torrent trackers that pride themselves on having transparent encodes will look for this kind of stuff; you have to do multiple test encodes tweaking various parameters to ffmpeg, agonizing over A/B screencaps, only to inevitably be told you either missed some minuscule detail in a single scene, or that your encode is bloated.
- AlotOfReading 2y ago
  You can see some ringing in the sky around the trees and on the line between the crow's beak/feathers if you look closely. (Alvin's?) fur goes much farther down his forehead as well. People who work deeply with codecs are usually hypersensitive to these sorts of issues that mere mortals like us need to try to see. There used to be a legendary blog called "Diaries of an x264 developer" by Fiona Glaser [0] where she'd go on long rants about various ways to cheat in encoder comparisons [1], much like this. [0] https://web.archive.org/web/2012/http://x264dev.multimedia.cx/ https://web.archive.org/web/2012/http://x264dev.multimedia.c... [1] https://web.archive.org/web/20130215095527/http://x264dev.multimedia.cx/archives/472 https://web.archive.org/web/20130215095527/http://x264dev.mu...
  - machrider 2y ago
    Appreciate this, I was feeling the same way as the original comment. It looks maybe over-sharpened, but I don't see anything as glaring as the text of the article makes it sound! (Of course, I'm not a video codec developer.) It does remind me of how stereo & speaker manufacturers sometimes boost treble a little bit (rather than being perfectly "transparent" to the original signal) because it gives the impression of clarity. But ideally each step in the processing chain "colors" the signal as little as possible, because those little differences can add up.
    - LegionMammal978 2y ago
      Yeah, audio response curves have always been a bit confusing to me. Like, they say that headphones should use a Harman curve because that sounds 'best' to listeners, but how valid is it as an objective measure? (E.g., will listeners 50 years from now find a different curve 'better', the same way that instrument tuning has changed over centuries?) And how much of it is responding to current practices in recording and mixing? Of course, you won't get a sound as if you're in the same room (without a very fancy setup), so you'll generally want some sort of transformation to get an acceptable output. And artists often want to aim for a certain effect on top of that. But with how things currently are, many of the decisions going into the final sound are very opaque.
      - HPsquared 2y ago
        The thing that gets me about audio is people obviously have different ears. Some are more sensitive to high frequencies, etc. It's even age-dependent. It's like salt preference on food.
      - astrange 2y ago
        > Like, they say that headphones should use a Harman curve because that sounds 'best' to listeners, but how valid is it as an objective measure? It should be valid because it's "neutral". IIRC it's basically a conversion to simulate how a neutrally tuned speaker would sound if you were in the same room. There are many reasons objective headphone measurements aren't actually objective for you though. The biggest one is that they're taken in a silent room, so a single CPU fan or anything near you makes it invalid. Noise cancelling can mean a lot in practice. The other reasons are that different people have different ear shapes, some people wear glasses so the headphones can't get a seal, your amp isn't electrically compatible with the headphone, your music is badly mastered so you prefer a headphone badly tuned the opposite way, etc.
- dist-epoch 2y ago
  Ringing is pretty obvious to me. It has a specific meaning in this context, it means edges are over-sharpened to the point that "fake" extra edges appear. https://en.wikipedia.org/wiki/Ringing_artifacts https://en.wikipedia.org/wiki/Ringing_artifacts
  - astrange 2y ago
    That is what it should mean, but in image compression people use it to mean "mosquito noise" artifacts, which come from quantizing DCT compression applied to edges. (Nyquist theorem = DCT is bad at edges because they're made of an infinite number of frequencies.)
    - cvz 2y ago
      It's the exact same phenomenon in both. Not sure where you're making the distinction.
      - astrange 2y ago
        It doesn't come from "oversharpening".
        cvz 2y ago
        Sharpening and bandwidth-limiting have the exact same effect, because the maximum sharpness of an image (like any other signal) depends on its bandwidth. There is no difference in the type of artifact produced. That's why the artifact from both has the same name of "ringing".
        astrange 2y ago
        It doesn't come from "sharpening" at all though. That implies an increase in frequencies. This compression artifact comes from rounding them, so they're moved in both directions.
    - bestham 2y ago
- mrob 2y ago
  The ringing is most obvious in the striped shirt in the painting on the wall. It's added entire new stripes that don't exist in the original.
- klik99 2y ago
  As someone who works a lot with sound I notice a ton of artifacts most people don't recognize. Often those artifacts are harder to hear on cheap speakers but become far more obvious with a good setup. But they also add up and while untrained ears can't hear specific examples, they do result in an overall worse experience which is especially frustrating for high end users when they paid a lot for nice speakers and it's just revealing the grunge that was always there. That's all to say - I also could not find all the things they are talking about, probably a combination of not being trained, not working a lot with video codecs, and not having the best monitors - but I get the authors frustration, and I'm glad there's people who care about these things! But yeah, I hunted for that color shift and just not seeing it...
  - ksec 2y ago
    I remember a while ago we have a thread on HN discussing this. 50% of the world cant taste the difference between Pepsi and Coke Cola. People cant tell the difference between 128Kbps or 256Kbps MP3. etc. For the people who are sensitive to a lot of these, it is more of a curse than gift. Some cant taste the difference between Corn Fed ( or Finished ) and Grass Fed Beef. The colour shift in this article, or how the latest TV perform between OLED, QD-OLED, Four Layer OLED, Mini-LED with different brand. It turns out being able to "compare" is a skill set in itself. I would assume comparing is also a function that requires more brain power / energy, and most people's natural state would be to conserve that energy. I have been thinking about this for quite some time. Most people dont know how to compare, or what to compare it to. And precisely because most people dont know how to compare or how not to compare, we need marketing. And I think most successful founder are very good at comparing things. Steve Jobs would be a prime example.
    - deleted 2y ago
      [deleted]
- ZeroGravitas 2y ago
  I don't immediately see the issue either. Though, even if I could, this is a new way to preprocess an image before feeding it into an encoder, and the examples have both been fed through the new downsizer, then the standard encoder, presumably at the standard Netflix bitrates and then (I think) upscaled back to the original size. So if this didn't look a little compressed then that would be a methodological mistake, as you don't use downscaled encoding unless you've already decided that a full size encode has too much quality for your task. And Netflix generally has incentives set up to reduce quality until their customers notice. That's why they quote stats based on that. In web dev terms it's like reducing the size of your product images until it hurts sales. You're almost guaranteed to have artifacts visible to image compression experts before you hit the point that it affects your bottom line. If you are targeting customers on slow internet (and again if you are downscaling then you basically are) your sales are likely to initially rise as you get usable pictures to people faster.
mikeryan 2y ago
Sorta related story. I worked for a cable channel (TechTV) in the late 90s early 2ks (until Comcast bought it, laid everyone off and turned it into G4) this was the early days of cable VOD. At that time you had to pay a service by the minute to watch your video before they’d distribute it. That was the QA forced on you by the cable companies. The fun note is that those services charged double for “adult” content.
xmprt 2y ago
Is it just me or does the author here sound like they're hating just to hate? The writing doesn't sound that terrible. Maybe it's a bit amateur but isn't that what you're expect from an engineering blog post written by people whose day job is to write code. And for a layman, the image comparison isn't as bad as they make it out to seem.
- cvz 2y ago
  I am unsurprised that the author would hold a video distribution company which supposedly pays good money for experts to a higher standard than the average hobbyist blogger. I don't think it's hating for the sake of hating.
kelseyfrog 2y ago
I'd imagine that for the group of people who can see the difference, it must be very aggravating - much like when you start to see kerning mistakes. For the rest of us, though, it is imperceptible.
bonoboTP 2y ago
Is downscaling difficult? I can understand that upscaling is hard and you need learning. But when downscaling, for me OpenCV's "area" interpolation always gives great results super fast.
- Sesse__ 2y ago
  Is “area” just a box filter, which is what it sounds like? If so, it gives really blurry results; hardly great.
  - bonoboTP 2y ago
    Yes, it can be seen as a box filter (with the size equal to the stride length) on the nearest-neighbor upscaled image. Basically if you imagine overlaying the new square grid over the old one and then each new pixel gets a weighted combination of the overlapping old pixel squares, weighted by the overlap areas. To my eyes it's more pleasant than Lanczos, which has too much ringing.
- derf_ 2y ago
  In short: no, it shouldn't be. The Netflix post is sort of bizarre. They claim to be optimizing for minimum mean-squared error (MSE) given a conventional (bicubic) upscaling process [0], but... that should have an analytic closed-form solution, as this post states? You definitely do not need multiple layers of neural networks to achieve it. Then they present VMAF results, but VMAF is very much not equivalent to MSE, so you have no idea if they even improved the metric they optimized for. Subjective results are similarly unpersuasive: it isn't clear if "the deep downscaler was preferred by 77% of test subjects" means they thought it was closer to the original or simply "better" than Lanczos[1]. Netflix may not care: longer watch times are longer watch times. But as an engineer you might want to know if that is because you actually achieved the thing you were optimizing for, or it is due to an artifact of the process that might go away the next time you change something to actually improve what you were optimizing for. You can famously make people prefer one audio track over another by making it louder, and video has similar things around sharpness and contrast (and now, thanks to ML, hallucinated detail). I agree that you can do better than Lanczos for large downscale factors [2]: you need to do something area-based, like you suggest (I have not looked at OpenCV's implementation, but it could be fine). The biggest thing to get wrong is handling gamma incorrectly, but the right thing to do depends on whether you intend to display the result at the downscaled size or upscaled back to the original size as seems to be assumed here (and whether or not your upscaler is gamma-aware, which it probably isn't). As an aside to those struggling to see the visual differences, make sure you are looking at the image in its original (1874x1596) resolution: https://redvice.org/assets/images/netflix-downscaler-compare.png https://redvice.org/assets/images/netflix-downscaler-compare... (or right-click, View Image on the original page). Otherwise you also have your browser's resampling algorithm in the mix. To my eyes on my display there is also a pretty big color shift in the featureless pink background of the painting on the right wall, but when I look at the actual pixel values, that appears to be an optical illusion. Subjective comparison is hard! [0] Unlike the post, I think this is reasonable. In the past, we did experiments that showed that optimizing for bilinear when nearest-neighbor is used (for chroma) is worse than optimizing for nearest-neighbor when bilinear is used. I suspect something similar will be true for bicubic and bilinear, but these days it may be safe to assume that you will get at least bicubic upscaling (for luma), because bilinear luma looks really bad. I haven't done a recent survey of actual playack devices, though. [1] It's also not how you report subjective test results: what was the statistical significance? There are standard protocols for these kinds of tests and it would have been helpful to cite which one was used. [2] Nobody ever says what downscaling factors are being tested here. The example graph shows 1080p to 342p, or ~3.16x, but Netflix goes as low as 144p (from, e.g, 2160p), so they can get pretty large (15x) in practice. A 6-tap filter is not going to cut it.
henning 2y ago
I love bagging on lazy engineers who just chuck code over the fence without caring about the user experience, but I seriously doubt I would notice this. The sad truth is a lot of video is watched in the background and Netflix knows this. For the specific case of a children's cartoon, I doubt the children watching will notice or care. If there is user feedback about the quality, then by all means listen to users and at least have an "advanced settings" menu in the app to let users toggle between encoders if they really care.
- lofaszvanitt 2y ago
  When will people finally learn that people do not know what they want. You, the expert has to know what works and how and whats the best way to use it properly. And do not rely on user feedback. Again. People don't know whats wrong, they don't even know what's right. They just feel that something is off. And only a very small percentage of users would write an email and even fewer would get through the automated AI bullshit or the snotty person who would dare to hand you a HOW TO USE NETFLIX pdf when you want to report something.
  - henning 2y ago
    I am not the user. What I honestly believe is right may not work out the way I expect despite my best efforts as an expert. If you can't get any user feedback on your products, that is its own problem.
- deleted 2y ago
  [deleted]
runeblaze 2y ago
> Is Lanczos an example, or the current best option What’s the best (computationally not that more expensive than Lanczos) option? Edit: also some CV researchers write like that (the Netflix writing) — bicubic is like a flag in opencv that they just use. Probably those researchers were much more preoccupied with the researchy problem than actual wide deployment, which is what many researchers do
- bick_nyers 2y ago
  It's not really possible to say what's "best" because the criteria is super subjective. I personally like the Spline family, and I default to Spline36 for both upscaling and downscaling in ffmpeg. Most people can't tell the difference between Spline36 and Lanczos3. If you want more sharpness, go for Spline64, for less sharpness, try Spline16. Edit: As far as I'm aware though OpenCV doesn't have Spline as an option for resizing.
bbstats 2y ago
Speaking of using your eyes - zooming in on small parts of single frames is not an accurate representation of watching something!
lxe 2y ago
Thought this was gonna be a thoughtful nuanced critique but instead we get a wild unsubstantiated rant.
- GrantMoyer 2y ago
  The thing is there's not much nuance to be had. Netflix's approach is just worse than existing best approaches on all axes.

92 points by zdw 2y ago

I don't see (or maybe don't recognize) any issues with the image that they're talking about (ringing, color shift, or fake details). It most certainly doesn't look awful to me, it looks exactly the same, only a bit sharper.

SG- 2y ago
the fact that it looks different is the problem.
sgarland 2y ago
It’s mostly only visible in the closeup of the kid. There are hairs that have been unnecessarily accentuated, and his eye and eyebrow outline look hyper-sharpened, with rough edges. The non-zoomed image looks fine to me, and I (to some extent) know what I’m looking for. Some private torrent trackers that pride themselves on having transparent encodes will look for this kind of stuff; you have to do multiple test encodes tweaking various parameters to ffmpeg, agonizing over A/B screencaps, only to inevitably be told you either missed some minuscule detail in a single scene, or that your encode is bloated.
AlotOfReading 2y ago
You can see some ringing in the sky around the trees and on the line between the crow's beak/feathers if you look closely. (Alvin's?) fur goes much farther down his forehead as well. People who work deeply with codecs are usually hypersensitive to these sorts of issues that mere mortals like us need to try to see. There used to be a legendary blog called "Diaries of an x264 developer" by Fiona Glaser [0] where she'd go on long rants about various ways to cheat in encoder comparisons [1], much like this. [0] https://web.archive.org/web/2012/http://x264dev.multimedia.cx/ https://web.archive.org/web/2012/http://x264dev.multimedia.c... [1] https://web.archive.org/web/20130215095527/http://x264dev.multimedia.cx/archives/472 https://web.archive.org/web/20130215095527/http://x264dev.mu...
- machrider 2y ago
  Appreciate this, I was feeling the same way as the original comment. It looks maybe over-sharpened, but I don't see anything as glaring as the text of the article makes it sound! (Of course, I'm not a video codec developer.) It does remind me of how stereo & speaker manufacturers sometimes boost treble a little bit (rather than being perfectly "transparent" to the original signal) because it gives the impression of clarity. But ideally each step in the processing chain "colors" the signal as little as possible, because those little differences can add up.
  - LegionMammal978 2y ago
    Yeah, audio response curves have always been a bit confusing to me. Like, they say that headphones should use a Harman curve because that sounds 'best' to listeners, but how valid is it as an objective measure? (E.g., will listeners 50 years from now find a different curve 'better', the same way that instrument tuning has changed over centuries?) And how much of it is responding to current practices in recording and mixing? Of course, you won't get a sound as if you're in the same room (without a very fancy setup), so you'll generally want some sort of transformation to get an acceptable output. And artists often want to aim for a certain effect on top of that. But with how things currently are, many of the decisions going into the final sound are very opaque.
    - HPsquared 2y ago
      The thing that gets me about audio is people obviously have different ears. Some are more sensitive to high frequencies, etc. It's even age-dependent. It's like salt preference on food.
    - astrange 2y ago
      > Like, they say that headphones should use a Harman curve because that sounds 'best' to listeners, but how valid is it as an objective measure? It should be valid because it's "neutral". IIRC it's basically a conversion to simulate how a neutrally tuned speaker would sound if you were in the same room. There are many reasons objective headphone measurements aren't actually objective for you though. The biggest one is that they're taken in a silent room, so a single CPU fan or anything near you makes it invalid. Noise cancelling can mean a lot in practice. The other reasons are that different people have different ear shapes, some people wear glasses so the headphones can't get a seal, your amp isn't electrically compatible with the headphone, your music is badly mastered so you prefer a headphone badly tuned the opposite way, etc.
dist-epoch 2y ago
Ringing is pretty obvious to me. It has a specific meaning in this context, it means edges are over-sharpened to the point that "fake" extra edges appear. https://en.wikipedia.org/wiki/Ringing_artifacts https://en.wikipedia.org/wiki/Ringing_artifacts
- astrange 2y ago
  That is what it should mean, but in image compression people use it to mean "mosquito noise" artifacts, which come from quantizing DCT compression applied to edges. (Nyquist theorem = DCT is bad at edges because they're made of an infinite number of frequencies.)
  - cvz 2y ago
    It's the exact same phenomenon in both. Not sure where you're making the distinction.
    - astrange 2y ago
      It doesn't come from "oversharpening".
      - cvz 2y ago
        Sharpening and bandwidth-limiting have the exact same effect, because the maximum sharpness of an image (like any other signal) depends on its bandwidth. There is no difference in the type of artifact produced. That's why the artifact from both has the same name of "ringing".
        astrange 2y ago
        It doesn't come from "sharpening" at all though. That implies an increase in frequencies. This compression artifact comes from rounding them, so they're moved in both directions.
  - bestham 2y ago
mrob 2y ago
The ringing is most obvious in the striped shirt in the painting on the wall. It's added entire new stripes that don't exist in the original.
klik99 2y ago
As someone who works a lot with sound I notice a ton of artifacts most people don't recognize. Often those artifacts are harder to hear on cheap speakers but become far more obvious with a good setup. But they also add up and while untrained ears can't hear specific examples, they do result in an overall worse experience which is especially frustrating for high end users when they paid a lot for nice speakers and it's just revealing the grunge that was always there. That's all to say - I also could not find all the things they are talking about, probably a combination of not being trained, not working a lot with video codecs, and not having the best monitors - but I get the authors frustration, and I'm glad there's people who care about these things! But yeah, I hunted for that color shift and just not seeing it...
- ksec 2y ago
  I remember a while ago we have a thread on HN discussing this. 50% of the world cant taste the difference between Pepsi and Coke Cola. People cant tell the difference between 128Kbps or 256Kbps MP3. etc. For the people who are sensitive to a lot of these, it is more of a curse than gift. Some cant taste the difference between Corn Fed ( or Finished ) and Grass Fed Beef. The colour shift in this article, or how the latest TV perform between OLED, QD-OLED, Four Layer OLED, Mini-LED with different brand. It turns out being able to "compare" is a skill set in itself. I would assume comparing is also a function that requires more brain power / energy, and most people's natural state would be to conserve that energy. I have been thinking about this for quite some time. Most people dont know how to compare, or what to compare it to. And precisely because most people dont know how to compare or how not to compare, we need marketing. And I think most successful founder are very good at comparing things. Steve Jobs would be a prime example.
  - deleted 2y ago
    [deleted]
ZeroGravitas 2y ago
I don't immediately see the issue either. Though, even if I could, this is a new way to preprocess an image before feeding it into an encoder, and the examples have both been fed through the new downsizer, then the standard encoder, presumably at the standard Netflix bitrates and then (I think) upscaled back to the original size. So if this didn't look a little compressed then that would be a methodological mistake, as you don't use downscaled encoding unless you've already decided that a full size encode has too much quality for your task. And Netflix generally has incentives set up to reduce quality until their customers notice. That's why they quote stats based on that. In web dev terms it's like reducing the size of your product images until it hurts sales. You're almost guaranteed to have artifacts visible to image compression experts before you hit the point that it affects your bottom line. If you are targeting customers on slow internet (and again if you are downscaling then you basically are) your sales are likely to initially rise as you get usable pictures to people faster.

mikeryan 2y ago

Sorta related story. I worked for a cable channel (TechTV) in the late 90s early 2ks (until Comcast bought it, laid everyone off and turned it into G4) this was the early days of cable VOD. At that time you had to pay a service by the minute to watch your video before they’d distribute it. That was the QA forced on you by the cable companies. The fun note is that those services charged double for “adult” content.

xmprt 2y ago

Is it just me or does the author here sound like they're hating just to hate? The writing doesn't sound that terrible. Maybe it's a bit amateur but isn't that what you're expect from an engineering blog post written by people whose day job is to write code. And for a layman, the image comparison isn't as bad as they make it out to seem.

cvz 2y ago
I am unsurprised that the author would hold a video distribution company which supposedly pays good money for experts to a higher standard than the average hobbyist blogger. I don't think it's hating for the sake of hating.

kelseyfrog 2y ago

I'd imagine that for the group of people who can see the difference, it must be very aggravating - much like when you start to see kerning mistakes. For the rest of us, though, it is imperceptible.

bonoboTP 2y ago

Is downscaling difficult? I can understand that upscaling is hard and you need learning. But when downscaling, for me OpenCV's "area" interpolation always gives great results super fast.

Sesse__ 2y ago
Is “area” just a box filter, which is what it sounds like? If so, it gives really blurry results; hardly great.
- bonoboTP 2y ago
  Yes, it can be seen as a box filter (with the size equal to the stride length) on the nearest-neighbor upscaled image. Basically if you imagine overlaying the new square grid over the old one and then each new pixel gets a weighted combination of the overlapping old pixel squares, weighted by the overlap areas. To my eyes it's more pleasant than Lanczos, which has too much ringing.
derf_ 2y ago
In short: no, it shouldn't be. The Netflix post is sort of bizarre. They claim to be optimizing for minimum mean-squared error (MSE) given a conventional (bicubic) upscaling process [0], but... that should have an analytic closed-form solution, as this post states? You definitely do not need multiple layers of neural networks to achieve it. Then they present VMAF results, but VMAF is very much not equivalent to MSE, so you have no idea if they even improved the metric they optimized for. Subjective results are similarly unpersuasive: it isn't clear if "the deep downscaler was preferred by 77% of test subjects" means they thought it was closer to the original or simply "better" than Lanczos[1]. Netflix may not care: longer watch times are longer watch times. But as an engineer you might want to know if that is because you actually achieved the thing you were optimizing for, or it is due to an artifact of the process that might go away the next time you change something to actually improve what you were optimizing for. You can famously make people prefer one audio track over another by making it louder, and video has similar things around sharpness and contrast (and now, thanks to ML, hallucinated detail). I agree that you can do better than Lanczos for large downscale factors [2]: you need to do something area-based, like you suggest (I have not looked at OpenCV's implementation, but it could be fine). The biggest thing to get wrong is handling gamma incorrectly, but the right thing to do depends on whether you intend to display the result at the downscaled size or upscaled back to the original size as seems to be assumed here (and whether or not your upscaler is gamma-aware, which it probably isn't). As an aside to those struggling to see the visual differences, make sure you are looking at the image in its original (1874x1596) resolution: https://redvice.org/assets/images/netflix-downscaler-compare.png https://redvice.org/assets/images/netflix-downscaler-compare... (or right-click, View Image on the original page). Otherwise you also have your browser's resampling algorithm in the mix. To my eyes on my display there is also a pretty big color shift in the featureless pink background of the painting on the right wall, but when I look at the actual pixel values, that appears to be an optical illusion. Subjective comparison is hard! [0] Unlike the post, I think this is reasonable. In the past, we did experiments that showed that optimizing for bilinear when nearest-neighbor is used (for chroma) is worse than optimizing for nearest-neighbor when bilinear is used. I suspect something similar will be true for bicubic and bilinear, but these days it may be safe to assume that you will get at least bicubic upscaling (for luma), because bilinear luma looks really bad. I haven't done a recent survey of actual playack devices, though. [1] It's also not how you report subjective test results: what was the statistical significance? There are standard protocols for these kinds of tests and it would have been helpful to cite which one was used. [2] Nobody ever says what downscaling factors are being tested here. The example graph shows 1080p to 342p, or ~3.16x, but Netflix goes as low as 144p (from, e.g, 2160p), so they can get pretty large (15x) in practice. A 6-tap filter is not going to cut it.

henning 2y ago

I love bagging on lazy engineers who just chuck code over the fence without caring about the user experience, but I seriously doubt I would notice this. The sad truth is a lot of video is watched in the background and Netflix knows this. For the specific case of a children's cartoon, I doubt the children watching will notice or care. If there is user feedback about the quality, then by all means listen to users and at least have an "advanced settings" menu in the app to let users toggle between encoders if they really care.

lofaszvanitt 2y ago
When will people finally learn that people do not know what they want. You, the expert has to know what works and how and whats the best way to use it properly. And do not rely on user feedback. Again. People don't know whats wrong, they don't even know what's right. They just feel that something is off. And only a very small percentage of users would write an email and even fewer would get through the automated AI bullshit or the snotty person who would dare to hand you a HOW TO USE NETFLIX pdf when you want to report something.
- henning 2y ago
  I am not the user. What I honestly believe is right may not work out the way I expect despite my best efforts as an expert. If you can't get any user feedback on your products, that is its own problem.
deleted 2y ago
[deleted]

runeblaze 2y ago

> Is Lanczos an example, or the current best option What’s the best (computationally not that more expensive than Lanczos) option? Edit: also some CV researchers write like that (the Netflix writing) — bicubic is like a flag in opencv that they just use. Probably those researchers were much more preoccupied with the researchy problem than actual wide deployment, which is what many researchers do

bick_nyers 2y ago
It's not really possible to say what's "best" because the criteria is super subjective. I personally like the Spline family, and I default to Spline36 for both upscaling and downscaling in ffmpeg. Most people can't tell the difference between Spline36 and Lanczos3. If you want more sharpness, go for Spline64, for less sharpness, try Spline16. Edit: As far as I'm aware though OpenCV doesn't have Spline as an option for resizing.

bbstats 2y ago

Speaking of using your eyes - zooming in on small parts of single frames is not an accurate representation of watching something!

lxe 2y ago

Thought this was gonna be a thoughtful nuanced critique but instead we get a wild unsubstantiated rant.

GrantMoyer 2y ago
The thing is there's not much nuance to be had. Netflix's approach is just worse than existing best approaches on all axes.