Cs go aimbot code how to#
Cs go aimbot code install#
Cs go aimbot code zip file#

Most of this training data I generated with the method I explained in my previous tutorial. Check my YouTube tutorial for more.ДЇirst, I should tell you that I used only around 1500 images to train my aimbot model. Also, you may need to change sensitivity or other minor settings.

If the mouse is flying around in-game, open the game console and type m_rawinputВ 0, this will disable raw game input. When YOLO detects objects on the screen, it should start moving the mouse and shooting the enemies. Now, when you have running the CSGO game in the background, run the YOLO_aimbot_main.py script. You may change YOLO_INPUT_SIZE if you need better accuracy, but you will lose in FPS. My yolov3/configs.py file is already configured for custom trained object detection with an input_size of 416.

Cs go aimbot code install#

Now you need to install all requirements: Now open the checkpoints folder and run linux_unzip_files.py script. Sudo apt-get install unzip unrar p7zip-full, Download P7ZIP with GUI and unzip everything.

Cs go aimbot code how to#

If you are on Linux, there are two ways how to unzip:ДЎ. If you are on Windows, unzip it using 7zip. I already zipped my trained model, which I put into the checkpoints folder.

Cs go aimbot code zip file#

You can clone it or download it as a zip file it doesn't matter. When you have Steam and CSGO downloaded, we can download my GitHub repository. In steam download Counter-Strike Global Offensive There still may be errors while installing or running Steam, but you should solve them with google help :).ДҐ. Then run Steam with the following command in the terminal: But if you are on Linux, it's a little more complicated. Second, if you are on windows, it's pretty easy and obvious how to install Steam. Why ubuntu? Because it's much easier to run TensorRT on Ubuntu than Windows 10, you can try to run it on Windows 10 with the following repository.ДЇirst, you must install TensorFlow, Python 3, Cuda, Cudnn, etc., packages to prepare the TensorFlow environment.

The code was tested on Ubuntu and Windows 10 (TensorRT not supported officially).

Then I used the technique explained in my previous tutorialВ to generate training data for my model to detect enemies accurately.ДЇirst, I would like to discuss instructions, how you can run it by yourself, results, and lastly, I will talk about code, so there will be three parts.

I created a lot of tutorials to explain every part of it. So, first, I took my YOLOv4 GitHubВ code, on which I was working for half a year, to make it easily understandable and reusable. Why water? To avoid violence, of course.Д«ut I am not talking about what we could do. Also, I thought it would be fun to create a water gun robot that could aim at approaching people and shoot the water. The same concept we could use in real life for some security system, for example, detect and recognize people around our private house and if it's an unknown person aim lights at that person or turn-on some alarm.

What is aimbot? The idea is to create an enemy detector, aim at that enemy and shoot it. After giving you a lot of explanations about YOLO, I decided to create something fun and exciting, which would be a Counter-Strike Global Offensive game aimbot. Welcome to my last YOLOv4 custom object detection tutorial from the whole series.