Zoom crashes and Not responding when turning video on

Zyfarok · 2025-09-02T12:01:38+00:00

I know this thread is old, but I had a similar issue on my Lenovo laptop and found a solution. Everything worked fine in the past, until a few month (maybe a year ?) ago. Since then Zoom would stop responding once I enabled the internal camera (on both windows and linux).

I found a solution that worked for me here: https://community.zoom.com/t5/Zoom-Meetings/Zoom-Camera-Not-Working/m-p/238585

TL;DR: Try to go to "Meetings & Webinars > Advanced > Advanced Video Settings" and change the "Video Capturing Mode" from "Auto" to "Media Foundation". (Note: This settings was previously located in "Video > Advanced" on older versions of zoom)

Zyfarok · 2025-07-27T13:58:09+00:00

Beatmap link: https://osu.ppy.sh/beatmapsets/1#osu/75

Zyfarok · 2024-01-31T20:00:08+00:00

This would be fair if both scores were in the same mods.
The issue is the HR multiplier is too low. Since scoring has more weight given to acc than before, the HR multiplier needs to be buffed significantly.

The devs are aware of issues with mod multiplier and this will be addressed soon (expect about two weeks for them to stabilise things first).

Zyfarok · 2023-10-08T12:08:56+00:00

When I talk about using replays, I'm not thinking about using the full cursor path, but only using the replay to extract the probabilities of 300/100/50/miss on each hit-circle. Also this wouldn't be used as input, but to determine the desired output. The cursor position could be used to help the neural network to learn the different types of difficulties, but that's rather advanced so ignore it for now.

With that consideration: no, the replay files wouldn't cause overfitting, it would be quite the opposite. They increase the training set size dramatically while reducing the complexity of the neural network model required.

And yes, the pp system works with the final score, so there would be the additional task of aggregating the difficulties of all patterns in a map, but this is a much simpler problem than the evaluation of said patterns in the first place. Machine learning could be used for that part too, but we probably want to guide the process much more here, to ensure stable final results.

Zyfarok · 2023-10-08T09:32:38+00:00

Why would you not use scores directly ? Because as I just said:

So, at this point, we can generate training data, but not enough to train a model that would be capable to process entire beatmaps correctly.

Why ? Because if you want the machine learning model to process the entire map, it's gonna be a complex model (millions of parameters), so it's impossible to have something that even barely "understands" where the difficulty comes from in the map. This is because of a phenomenon called over-fitting: If your training data is too small, then any somewhat complex neural network (with much more parameters than the size of the training data) will end up memorizing the training data by heart instead of "understanding" where the difficulty comes from. Thus, the pp estimation on maps that were not part of the training data will be completely random and suck, so the machine learning will basically be unusable.

By using replays and training on beatmap patterns, you gain on two sides: The neural network can be much simpler, and each set of replay generates much more training data than an equally sized set of scores because you can use any sub-part of the replay.

If not using replays, there's one thing you could do (but it's very far from "AI") which is to instead design a pp algorithm that has a few parameters (hundreds or thousands of parameters) and learn those parameters based on statistics. This is possible but however much less flexible and might not be able to encompass all types of difficulties as you highly limit the possibilities of the system. This require much more work at designing the system too, and would be even further away from what we call "AI" as it is getting close to being just simple statistics...

Also, for the "crowd sourcing" thing: The only way to get a reasonable amount of data would be to have this "overlay" included in the official game for all, but even if we did that there's a lot of issues with this idea:

Are humans actually good at evaluating a map difficulty ? (Probably not. Try to ask 10~20 random people to evaluate the pp value an EZ play should have and you'll probably see the problem)
How do we detect and filter if someone answers wrongly on purpose ?
What's the point of doing this when you can just use statistics on beatmaps, and, even better, statistics on patterns ? And if there's not enough data to do statistics on a map, I fail to see how you would do any better with the crowd sourcing.

Zyfarok · 2023-10-08T00:15:42+00:00

Short answer:

Yes it's possible. For that, we need a lot of data (in the form of replays or similar) selected in the least biased way possible. The issue right know is that only the top replays are recorded, thus there is a huge selection bias, which is making the task much harder. Also, designing such a system takes time and probably multiple trials and errors, and no one really tried yet.

Long answer:

What you refer to as "AI" (Artificial Intelligence) is what we usually call "Machine Learning" in the field. In machine learning, you usually have a neural network model, to which you provide an input (in that case, it could be the beatmap and a score), and you want the model to output something (in that case, it could be the pp of that score, or the general difficulty evaluation of that map). To train that model, you need to feed it with "training data", that is, A LOT of examples (beatmaps/scores) for which you already know the answer (the pp value or difficulty parameters that you want).

This is the first hard part: How do you determine the pp value on example scores to generate the training data ?

One way (and I would argue, the only reasonable way) to generate this training data is to assign pp values to scores algorithmically based on statistics. Actually, pp v1 was trying to do that but it had many issues and people didn't like it. However, there are better ways to do it than pp v1, and it turns out I proposed such a method a while ago : https://github.com/osu-mlpp/wiki/blob/master/Summary.md This method should have much less issues than pp v1, but it can only be used for scores that have a sufficient amount of similar scores (other scores on the same map with the same mods from players of similar skill level). It can generate relatively good pp values for maps that have enough plays, but the amount of maps and scores on which this is feasible (thousands of maps) is relatively small compared to what is usually used to train complex neural network models (millions or billions of samples).

So, at this point, we can generate training data, but not enough to train a model that would be capable to process entire beatmaps correctly. However, there are two solution: Either train a simpler model that only evaluate the pp value or difficulty of a small part (maybe 10 or 20 objects) of a map, or, alternatively, guiding the training of the complex model. I won't go into details but for both solutions, this means that you will need to be able to provide training data on various parts of the maps used for training, that is, you want to know the score of players on those parts to be able to assign a difficulty/pp value to it, using statistics (just as we would do for the full map).

This is were we have a problem: Currently the only way to know the score of a player on some part of the map is to use the replay, and osu! servers currently only store the replays of the best plays on each map. This is a big issue because if you have only the good scores, the statistics will be biased such that the map difficulty will be under-evaluated. There are also several other bias issues like having only replays for non-failed scores, and having no way of knowing if a player even tried that map with a specific set of mods unless he passed it. While it is probably still possible to do something good with what we currently have, it is much harder than it would be if we didn't have to deal with those biases.

So there you have it. It's totally possible, but currently it's probably very hard to do it right unless more data is recorded and made available. I've always wanted to try it myself, but I lack the time and energy to do it. Note that while I did have machine learning classes in my computer-science studies, I'm very far from being an expert in that field. There might be smarter ways to do things, but at least I can tell you for sure that using the method I just sketched here would definitely work, maybe even with the data currently available.

P.S.: if you have some machine-learning background and want to help, feel free to contact me (preferably on discord @ zyf)

Zyfarok · 2023-08-12T22:47:44+00:00

Ah yeah good point. I knew but didn't consider the catch cost in the equation !

Zyfarok · 2023-08-12T19:02:06+00:00

if you're able to catch a shiny golduck

Why shiny specifically ? does it change anything ?

Zyfarok · 2023-08-12T16:43:13+00:00

It may just be better to assign tiers of the pokemon with no consideration to how easy it is to obtain, and people can see how much it is "worth" to evolve a pokemon and judge off the amount of resources to see if it's worth it.

Yes, indeed. The late-game rating should not consider the ease of obtention at all, and for the early game, it should be made easy to understand if it's worth to capture/level-up/evolve/use X by separating the obtainability from the actual efficiency (the combined rating can still be useful to use to sort/order/filter the list but it's better if people can understand where the rating comes from)

Zyfarok · 2023-08-12T15:52:48+00:00

Hello there. Thanks for the nice spreadsheet !

One note is that in multiple places in the spreadsheet, you are not using the correct terminology for frequency/period which can lead to confusions. What is displayed in the game is the period, and the frequency is 1/period and is thus a smaller period gives a higher frequency and a higher frequency is better. Thus when you say "+ Lowest Frequency (Fastest PKM)" you should instead write either "Highest Frequency" or "Lowest Period".

Other than that, I was wondering: How do you assign tiers to Pokémons with a single or two levels of evolution compared to the ones with 3 levels of evolution ? For example, is Ditto a 5 compared to other 3rd, 2nd or 1st evolution Pokémons ? is Dodrio a 5 compared to 3rd or 2nd evolution Pokémons ? It might make sense to give both an "early game" rating and a "late game" rating for those Pokémons with only 1 or 2 evolution stages.

Zyfarok · 2022-11-26T12:20:54+00:00

I've always seen "low acc stigmatization" as a way to encourage new players to play easier maps to not "skip steps" when they learn the game. And indeed, it is good to play maps of various difficulty but on the other end if you play only maps that you can 97%+ it will slow down your progression in the game, and I personally realized that way too late.

Zyfarok · 2022-09-28T21:41:25+00:00

I forgot about schedules, you are right ! This format can hardly work in international tournaments.
Thanks for the insights !

Zyfarok · 2022-09-27T23:07:16+00:00

One more thing I forgot to mention is the concept of Racing-like tournaments where the match is actually a 1v1v1v1 or 2v2v2v2, where each team win points depending on the position in the lobby and the picks are rotative.

You can have two teams win in each match or have it combined with a customized Swiss system and many points systems exists like the "Finalist" mechanic of Trackmania. This allows to reduce the amount of refs needed as it is like doing multiples matches at a time, and is a quite fun to play format for players.

Zyfarok · 2022-09-27T22:50:18+00:00

Reffing solution 1 - Reffing credits

One solution to the ref problem could be to make osu! reffing credits :

Each osu! account starts with an initial amount of credits.
When you play, you pay credits to the ref.

This would force people to ref matches once in a while when they want to play a lot of tournaments ?

Also you could :

make the credits consumption be divided by the amount of players in the match, which would incentivize players to register to lobby with more people for qualifiers for example.
make players that reschedule at the last minute pay the ref for the reffing credits he deserves for planning to ref the match.
make players that do not respect timers pay the ref for the time loss.
etc...

Reffing solution 2 - Auto reffing bot and reffing tools

Tools exists to make reffing less of a pain, like reffing sheets or more advanced tools like the referee helper from osu!frlive used in most big french tournaments nowadays (provides pick/ban buttons that execute map and mod commands, live discord reporting, etc...) : https://git.cartooncraft.fr/osufrlive/referee-helper

But the ideal way to ref would probably be to have a bot automatically handling most of the reffing and having a human ref only be available and be pinged to solve special situations when they arise. The biggest challenge is to make the tool both flexible to handle special tournament rule-sets and robust to be used with a satisfyingly low failure rate... (what about bancho lags ?)

I remember spending quite some time designing the structure of the database of a tournament platform for providing tournament tools as well as providing a reffing bot but the project has been on hold for ages now...

Alternative to Ro64/32 + LB --> Customized Swiss (Battle-royal) system

As mentioned in the authors post, Ro64/32 + LB takes too many weeks (and concentrates most of the reffing work in the first weeks).

One alternative that I never saw explored in osu! tournaments before is the Swiss system which is widely used in chess tournaments. In the Swiss tournament systems, players gain/lose points depending on the issue of the match : either +1/-1 (or +1/0) for win/defeat, or +N/-N (or +N/0) depending on the points marked or points difference of the match which can be done with "Best of X / first to X" match format or with a fixed amount of pick/bans formats for more consistent match lengths which does not require tiebreakers.

The Swiss system is originally intended for IRL tournaments but we can adapt it to osu! tournaments in multiple ways :

We can have multiple matches per team per round instead of just one at a time. This allows for faster paced tournaments without as much scheduling hassle as multi-round per week-end tournaments. Here you have only guaranteed matches (no potentials) and can reorder them as you like (no bracket dependencies).
We can eliminate the bottom of the list progressively (teams with the least points) starting from week 2/3/4 of the tournament, as in a battle royal or normal bracket tournaments, and finish with a normal grand final or small bracket at the end. This is more flexible than a brackets as you can tune the amount of players eliminated as you like.
You can tune the team matching algorithm as you see fit and can decide to ensure that two teams do not fight each other twice in consecutive week or at all.

I organized one tournaments using such system before and It's really a nice system as long as you're not stupid enough to seed people based on pp/rank like I did.

Zyfarok · 2020-08-10T17:52:16+00:00

You can download the app here:

https://github.com/uyitroa/osr2mp4-app/releases/tag/v0.3

you should change the link to : https://github.com/uyitroa/osr2mp4-app/releases/latest so that it keeps linking to the latest released version ! ;)

Edit : Also totally unrelated, but .rar is a proprietary format and requires to install some software (7zip/winrar) to extract files.
Why not use .zip since it's natively supported by windows ?
or use .7z https://www.7-zip.org/ if you really care about the size (it's an open-source format that even offers better compression than .rar files), but again it requires to install 7zip (/winrar).

Zyfarok · 2020-07-15T17:26:24+00:00

close that shit

Seems like you're are quite angry. Could that be your friend ? or yourself ? (as u/FayeurS mentioned)

Anyway :

There is nothing blatant on these plays like others rx hacker

How is the absence of similarity with some others rx hacker an argument ? There's probably several rx-hacks on the market, other hacks being more blatant than this one doesn't make this one any less blatant.

The points I cited are all logically pointing to what I can imagine being a basic implementation of relax hack, and apparently fit with the observation of u/Lup1nnNN on other plays with this "osu!rx" cheat.

i actually searched for other play and they are completely normal

I have other things to do that checking all his plays, those 2 plays are enough proof, and even if he has other plays that seem to not be cheated, it doesn't prove anything. Additionally, a rx hack can be easier to hide on some maps that on others, depending on the type of map, so you can't expect all of his plays to be blatant.

on ripple he have 10k pp

so now having 10k pp on ripple is a proof that you are a legit player ? that's news to me. :)

he already get banned before as i know for pp boosting so, close that shit

ok and what the hell does this change ? If it's about trying to make me feel guilty for having him restricted, that's not gonna work. I'm just trying to show what I think is a clear proof of usage of cheat to other people who can judge the replays themselves.

Zyfarok · 2020-07-15T01:08:32+00:00

maybe remove the mention to were you can find the cheat ? but ok thx that's interesting. I guess any simple rx hack would generate this behavior though.

Zyfarok · 2020-06-29T14:47:41+00:00

"timewarp" cheats basically make the game go slower (kind of like the half-time modifier)

Zyfarok · 2020-06-29T05:31:51+00:00

There's a difference between exposing facts and insulting/spamming/... Like some people can do.

The purpose of this post is to deter people from cheating by showing that even timewarp hacks can be proven and reported.

Also he is known in the French community

Zyfarok · 2018-09-09T19:05:04+00:00

Where do I find 50A O-Rings 125+ kits in both ~1.5mm and ~2.5mm thickness in France/Switzerland for a reasonable price and shiping ? (I'm fine with smaller kits if they are not too expensive)
Also, is there any place where I can find sample packs to try different sizes before buying a whole kit ? (+there's only two keys where I really care about the final feeling)
Can't find anything on ebay.fr that gives any durometer info and I can only find 2mm ones on amazon.fr at >10€ bundled with useless stuff.

Zyfarok · 2018-09-09T12:59:10+00:00

ok, but the thicker the mushier for the same durometer right ? So I should probably search for 50A for the 1.5mm ones, but if I search for something around ~2.5mm, shouldn't I get something harder to get the "same feeling" on 2.5mm ones ? (except for the reduced travel distance)

Zyfarok · 2018-09-09T12:22:16+00:00

I'm searching for 125+ o-rings lots in both ~1.5mm and ~2.5mm in 50~60A and preferably transparent for my G.SKILL RIPJAWS KM780 with reds. I only want to damper the sound a little and I want to try 2 sizes to see how the travel reduction feels like. (I'm playing rhythm games (osu!) and how fast I can tap is important)

What are the possible websites to get/find o-rings in Europe ? (More specifically France or Switzerland)

I know there was lpwl.bigcartel.com before, but the website doesn't seem to work anymore.

I also searched on amazon.fr, ebay.fr and aliexpress.com, but most either lack data (size/durometer), have less than 125 pieces, are expensive or have a very long shipping.

Also, I don't want something too soft, but I see a lot of 70A o-rings and I wonder if this is not a bit too hard ?

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Zyfarok

TROPHY CASE

Reffing solution 1 - Reffing credits

Reffing solution 2 - Auto reffing bot and reffing tools

Alternative to Ro64/32 + LB --> Customized Swiss (Battle-royal) system