...but why? Why do any of this?

It's amazing how you can easily replicate my teammates in comp

This video made me understand why my friends call me a bot.

Calling Valorant a csgo gamemode is the funniest and most fitting description of the game I've ever heard

the AI is like a noob and a pro fighting over the controls. you're getting close.

Just got this recommended. Really good work! I am impressed by the performance you can achieve with transfer learning on your "small" annotated Valorant dataset. You still remember how high the performance for different objects was on your test set (accuracy or MAP if you have computed that)? It also really hurt me not seeing your model TURN upon hearing someone behind :D Would really love to see you including audio next, and then seeing some nice 180 flicks in version 2.0.

Anyone else just get recommended this video 1 year later? Great video btw

When i was doing my project with computer vision, I gained almost x10 performance increase just by downscaling input image by some ratio. Of course, it lowers the accuracy of results, but, sometimes full resolution is MUCH bigger than enough and downscaling isn't going to affect the results at all. So, by downscaling input images you can boost performance for free by finding the optimal level of downscaling.

One thing I thought you could do is make it so a label has to show up for 150ms (roughly a standard pro reaction time) - that way it doesn't shoot at every 1 frame ghost it thinks it sees, but only at persistent threats - and also it makes it seem more realistic and human-like by having somewhat realistic reaction times. You could also have it move the aim slowly over time in trial movements until it's over the top of the marked target and only shoot once it lines up, which would not only improve reliability of the aim but make it seem even more human-like and I just realised this video was from may 2021 and you're likely not even working on this any more oh well

Pretty interesting video, ans it's really well made as well. And it has subtitles! Thanks!

This takes "My teammate is a bot" to a whole new level

Not me getting false banned for "3rd party program" then this guys making an ai for valorant 💀💀

Why do I honestly think this bot could at least get bronze... Iron is a weird place

So, I know this video is kind of old, but I just discovered your channel and I'm watching all your videos 😅. I'm a PhD in machine learning, and I saw on the quick code that appears on the video that you are using large images. I don't think that this is necessary. You could downscale the images, use on your model, and recalculate afterwards where the BB is on the real feed. A second thing I would suggest os already use a pretrained huggingface object detection model just to see if it detects the caracteres as a person and use simple code to see the color of the border. This solution should help with the low data amount. You could even create data this way :) I don't have a solution for the spikes and mollies tough. Either way awesome video!

now get 8 more people and make a custom lobby so the bot can learn from actual gameplay experiences.

This is a prime example of a KZfaqr who needs a shit ton more attention. Well done!

when Riot don't make bots in custom so you do it yourself

I said it before and I'll say it again. These are the *best* videos on KZfaq right now. You sir are on the fast track to 2mio subs if you keep up this frequency and quality. Good luck and well done 👍

The only flaw I see is that it doesn't know to trash talk

Bro said he didnt share the code but somehow I see this in all of my ranked games

You need to reduce the size of the images the neural net is provided with. Go black and white and scale down the images, this will let it perform so much faster

This is gold. Things I think you can do (although it's been a year so who knows what happened) is obviously have it be aware to object presence, as you have said in the video, but also respond to sounds, voice commands (via wheel ore voice chat), awareness to economy, and most importantly, have it teabag other players.

This project really is incredible - the way the video was captured, the way inputs were sent to the game, the problem solving of getting a used dongle when the exploit was patched, all of it was wild!

As someone getting a PhD in Machine Learning, you're doing the work of someone getting a PhD in Machine Learning.

why just after 1 year? youtube hello?

THIS IS SOO GOOD. As a person just starting off with OpenCV and AI and stuff and an interest in Valorant, this is godly. I do want to see your code just to see how you used all the AI libraries and stuff purely from an academic standpoint but it makes sense why you would not want to.

This is extremely cool, and I’m super impressed! You’ve given me the motivation to get started on a few personal projects I’ve been considering. I love stuff like this, combining hardware hacking and multiple devices and data streams - managing complexity like that and coming up with solutions for problems in that space is so much fun.

It would be super fun to have like a league where it’s only AI you make yourself. 5v5 AI tourneys

6:04 not going to lie that far friendly on the left, i thought that was sova until you pointed it out.. i guess im just an engineered AI

whoa, I didn't know pytorch was so hard to download year ago. Now everyone can download it

Just got recommended your video today randomly and loved it. I thought you were a much bigger channel, you definitely deserve more views!

Id love to see a series on this as you keep trying to improve it, it was so much fun to watch

This is why you never take down videos. They could pop off years after uploading

This video is a year old and now is being recommended to everyone

Play unrated pleaseeee. I need to hear how the ai will react to verbal abuse

It's funny, I wrote computer vision bots for both PUBG and BDO using very similar tech. I followed nearly the same thought paths as you, used the same strategies / tech, and hit the same roadblocks. The part about being unable to load cudart had me dying, I know that pain. People would ask me why I bothered and I had no answer other than it was fun, so yeah I totally get this video and am glad to see someone else understands how satisfying making something like this can be, even though there is no real advantage to be gained.

It's things like this that make me wish I had the patients to learn coding and neural networks, I'd have so much fun just experimenting and pushing the boundaries of what I could create

I am actually planning on developing a thesis with Machine Learning and AI, and your video just shows up on my feed. Incredible, you just gives me an idea! Thank you so much for that, really appreciate it. Looking back at the older games like Counter Strike 1.6 that has bots, we are totally hoping this game also have like that bot you have made. Actually it's easier to create it on the system itself, not based on Computer Vision, but anyway... this project is smaller than large companies made for robots and self-driving cars like Tesla. Don't compare yours to them, this one-man project really amazes and inspires us on the community.

Honestly, I have watched this video about 4 times in the last month; because of how good it is, unfortunately there are not many good videos explaining how to train a custom data set, but your sources in the video's description helped me alot thank you for sharing this information.

More videos like that with deeeeep technical explanations, i understand in this video so much things that i been searching about and didn't understand

Amazing work. My daughters told me about this and I was impressed so had to check this out. Well done!!

So this is what my braindead ranked teammates were using

yo this is actually a really cool video and experiment. thanks for sharing your findings!

I worked with cv2 already but this is next level, my dude. I love this video so much and computer vision is extremely interesting. I actually consider focusing on computer vision in my future career. Anyways, thx for this awesome video and great inspiration. U are an beast

an improvement method for your labelling: you can add the ability to analyze moving images (for paint-splatters) by introducing a LSTM or similar. this will also remove the false labelling of beams or shells as enemies or spikes because the data in the short-term memory makes it impossible to mistake a bullet-shell for a spike. and the data in the long-term memory might even know which friendly is holding the spike.

"grad student or other sweatshop labor" - lol.

I think it would be really cool to have it read chat commands from teammates stuff like"!go A" "!Defend Spike" "!defuse spike"

That was a really good video explaining AI and ML. Great Job!

plz keep training this AI to point it can play at at least Iron level) Waiting for part 2)

the lack of object permanence is pretty realistic for pugs honestly.

awesome work here man ! Would definitely love to see a part 2 some day

Very interesting video! By the way, the creator of YOLO had ceased his research to prevent the tech from being used for military applications. I hope it will not be misused.

This takes "It dosen't use headphones!!!" to a new level

My dream is literally being able to do these things. I love the video, keep it up!

Bro just created an Iron 1 player. Also this bot oddly resembeled the teammates I get during my rank ups lmao.

Awesome Video. Changing the border color for enemys to a bright Pink or so could probably help with lots of false Enemys. The second one is a bit more tricky you are right. But I believe this could be since the AI get trickked in a way of an illusion like the Necker cube. Since you allways start the round facing correct you'd could use that data to make a null-point and just add the inputs and afterwards delete them again to allways have the correct view. Anyway thanks for the video I look forward for more.

KZfaq algorithm as unusual as always, glad i found this gem of a channel

i think u gotta distinguish not just from enemy, but enemy head, body, and legs, so it knows where to aim to.

This is actually really cool, i recently did a project using opencv and yolov5, and i was wondering if i could make a valorant bot like you did. i am absolutely blown by this

You knew that what you made wasn't perfect, but the feel of making something on your own is awesome. great video!

It is so painfull to see ai struggling, knowing he is just not good enought and there is nothing it can do until some human makes a better version of itself.

I'm glad this vid got recommended to me. For enemy detection, you could probably use the fact that the game outlines all enemies in the same bright red color to make the job easier on yolov5.

"this looks fun, but i might get banned if i test it in a multiplayer lobby" "ever heard of tf2?"

Great video! Love the approaches you took :)

This is hard AF, I've tried computer vision before. This guy did a great job Well done

you should setup a custom game 5v5 with these bots, then spectate and see who wins!!

You should set 2 of these up and have them 1v1 eachother

What an amazing project, these types of projects are what we engineers think of doing and give up saying it's way too much work 😂. Anyway great work and good content.

have a 5v5 with copies of this bot

You should meet TacticalPumpkin

Hey love the content, speaking as a overglorified trolley collector studying computer science and biomechatronics, ive only ever really worked with prerecorded material for AI, so forgive me if this cant be applied. I thought could be interesting using interpolation to track specific markers between set intervals/frames to track the future, pass and present frames for charactor motion and to predict where to aim and shoot with the low frame rate. For the navigation aspect, my big dumb idea for that is using planar homography, taking in the height of the player model and angle to visually map and record coordinates around the map and develop a nav mesh which the ai could then use to get around corners

Incredibly knowledgeable and we'll-spoken teacher. Nice tutorials comfortableness with the subject makes starting soft real exciting!!

Wow youtube algorithm took its time

hes designed a very evil new generation aimbot and he doesn't know

dude this video is awesome! AI technology is amazing. Hope you continue to improve this type of stuff!

There is probably a way to randomly generate training data. The games assets are probably available, so rendering pngs of just character models (with alpha 0 background) at different distances and angles, placing them randomly into background shots of the game and automatically generating the outlining box where the png got placed (that you till now had to manually draw) could give you lot's of training data very quickly wich should improve the results of your AI model by a lot. Just an idea

it would be cool to see 2 AI's 1v1 each other in valorant

I’m actually a CS student that is like kinda losing passion. I love playing game and all but after going through 3 years of pain automata theory and algorithm which burnt my brain with a little twist of discrete math. I don’t really see how all these things can help me in any practical way as web development job and other common field actually dont really need much theory So kinda lost. Be like why am i here… why am i suffering for no apparent reason 💀 I recently got into like data science and getting deeper with developing machine learning model. Find it quite interesting since it’s actually highly practical (we need to train data anyways so it cant be non practical) other than machine learning math course. Buttt My uni didn’t offer much unit for this field so pretty blur on what I can do other than training facial recognition models…and it kinda gets boring along the way. In the mean time, i grind much Valorant to get through uni stress THEN KZfaq RECOMMENDED THIS. Just wanna thank you alot as final sem student here and sincerely lost on what the hell i should do for my future. This project is definitely awesome and fun. It’s an inspiration to me for real. I really wanna grind more ml knowledge to be able to make project like this ahahhahaa Would love to see more owo ❤️

this is still really impressive! well done!!

No way... this guy finally found a way to have fun in Valorant

if only you could train it using a REPLAY SYSTEM

id like to see this model play against itself and learn the game see how good it can get

I've been looking everywhere for someone who Is trying to accomplish the same task . Subbed !

Very good work I can see potential and it seems like fun to develop

Considering that this was 2 years ago, its pretty impressive. The newer CV models might perform better. Do you have a recent version of this project?

Getting the resolution down 2 to 3 times would massively benefit fps and save some computing power

Damn bro top tier content, I'm sure you had to visit multiple countries to produce a masterpiece like this

100% work on this, I'd love to see you create something that can best you at valorant. having the bot use sound as well could be interesting. I'm sure this took quite a few hours

This would be super funny in an actual match

This is getting recommended after 1 year lol

One thing you could do is connect a wireless audio adapter into the game PC and have it transmit to the Bot PC. Then you could use an audio library to monitor the left and right audio channels for things like footsteps, gun shots, volume, etc. Then compare those findings to the mini map to see if those sounds are coming from a teammate or enemy. If it couldn't be coming from a friendly, have the AI turn in the direction of the sound. That'd be a way to at least get some basic sound integration done.

I Hope to see more of this!

here’s an idea, you should 3d render all characters, unplanted spike, planted spike, and all maps, then name those objects and what they are to the ai (a player or spike. you could work on all the gadgets and whatnot later for now keep it simple to build a base) give that information to the ai and run it through set scenarios just to see how it can identify objects using the 3d model for reference to the 2d image it sees. model the characters with two parts, head and body so it can try and for headshots. another thing you should teach the ai is physics and principles in valorant; ex: a player cannot be outside the map so shooting at an object that isn’t in these parameters cannot be deemed an enemy or whatever else can’t be outside the map. also teach the ai all the information about the guns, how fast they shoot, how precise they are, their damage, the difference shooting from un crouched, crouched, slow walking, walking, slow walking crouched, every possibility. once you do that start marking the most effective guns at what range so the bot can see when an enemy is further away or closer using its knowledge of the map and characters it has on hand. run the bot through set scenarios like go forward until you see this corner then make a left. from there have different (but keep it simple) objects be on this route to see how the ai will react. once the ai can start to understand the game you can start teaching it other things, like mollies, sage wall, slow orb, Phoenix’s ult, and other small things. from there you can use the ai’s math and predictive properties to make it predict where players will go, move, plant, etc. this is a huge project and you’ll need a more powerful computer.before you say it’s cheating let me explain how it isn’t. 1. the ai knows everything a human could know the ai isn’t going into the game files and seeing where people are, it’s not using the in game knowledge of hitboxes it’s using its own. 2. you also might be saying the ai having a 3d model of all players characters and map might be unfair however humans have the same thing, we learned the map and it’s 3d properties with the characters too, now you also might be thinking “humans had to learn the map they couldn’t download it” and you would be right however there is a work around to this, if you make the ai go through all the maps, and circle all the characters from far and close you might be able to replicate the same 3d downloaded learning from experience however the ai would need to be doing this for quite sometime. it would just depend on what you constitute as crossing the line between an ai and cheating. thank you for your time if you read this

Reinforcment learning is better at such tasks than ML or DL

KZfaq just recommended me this today and turned out it's a pretty good video

Wow this is a great idea and I will try to replicate your work on my stream using reinforcement learning. Great work by the way 👏

Oh so that's how an Iron Player is created

youtube recommended us all at once

Crazy! I was working at an AI coaching startup last year and my first job was making CV AI to process Valorant footage! Had to deal with A TON of the same issues, except my job was just to rip data out of video and not to play the game itself. The weeks of labelling still gives me a headache to think about ( accounting for colorblind options, aspect ratios, compression artifacts, languages, blegh).

It's more interesting than applicable, but I threw one of your images into facebook's segment anything demo. It can pretty accurately find characters very quickly and make masks of them. You probably don't want real time segmentation (and it has no label, so you'd need another tool), but it's neat to see. You could also potentially train off of pro gameplay / vods, using tools like segment anything to ease the burden of annotation. I started thinking of the map idea right before you said it (especially making it some form of grid). You could potentially create another model just for that based on various game states. It's pretty cool. Crosshair placement would also be another thing.