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192 lines
9.9 KiB
Markdown
192 lines
9.9 KiB
Markdown
# 🎯 World's Best AI Aimbot 🎮
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[](https://makeapullrequest.com)
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Want to make your own bot? Then use the [Starter Code Pack](https://github.com/RootKit-Org/AI-Aimbot-Starter-Code)!
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--
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--
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## 🙌 Welcome Aboard!
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We're a charity on a mission to educate and certify the upcoming wave of developers in the world of Computer Engineering 🌍. Need assistance? Hop into our [Discord](https://discord.gg/rootkitorg) and toss your questions at `@Wonder` in the *#ai-aimbot channel* (be sure to stick to this channel or face the consequences! 😬). Type away your query and include `@Wonder` in there.
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Our *AI Aimbot* 🤖 sharpshoots targets in **any game with humanoid characters**, harnessing the power of [YOLOv5](https://github.com/ultralytics). Currently, it's a ninja against anti-cheat systems, as it's visual-only. Still, watch out for manual player reports! 👀
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Intended for educational use 🎓, our aim is to highlight the vulnerability of game devs to AI-driven cheats. Pass it along to your game developer buddies, and save their games from being outsmarted!
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**⚠ Use at your own risk! If you're caught... well, you've been warned!**
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## 📹 Instructional Media
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- [Watch the tutorial video (Works But Outdated)](https://www.youtube.com/watch?v=TCJHLbbeLhg)
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- [Watch the live stream explainer (Works But Outdated)](https://www.youtube.com/watch?v=uniL5yR7y0M&ab_channel=RootKit)
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- [Join the Discord](https://discord.gg/rootkitorg)
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## There are 3 Versions 🚀🚦🖥️
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- Fast 🏃♂️ - `main.py` ✅ Easy to set up, Works on any computer 💻
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- Faster 🏃♂️💨 - `main_onnx.py` ⚙️ May need to edit a file, Works on any computer 💻
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- Fastest 🚀 - `main_tensorrt.py` 🏢 Enterprise level hard, Works on computers with Nvidia GPUs only 🎮
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## 🧰 Requirements
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- Nvidia RTX 980 🆙, higher or equivalent
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- And one of the following:
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- Nvidia CUDA Toolkit 11.8 [DOWNLOAD HERE](https://developer.nvidia.com/cuda-11-8-0-download-archive)
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## 🚀 Pre-setup Steps
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1. Download and Unzip the AI Aimbot and stash the folder somewhere handy 🗂️.
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2. Ensure you've got Python installed (like a pet python 🐍) – grab version 3.11 [HERE](https://www.python.org/downloads/release/python-3116/).
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- 🛑 Facing a `python is not recognized...` error? [WATCH THIS!](https://youtu.be/E2HvWhhAW0g)
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- 🛑 Is it a `pip is not recognized...` error? [WATCH THIS!](https://youtu.be/zWYvRS7DtOg)
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3. Fire up `PowerShell` or `Command Prompt` on Windows 🔍.
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4. To install `PyTorch`, select the appropriate command based on your GPU.
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- Nvidia `pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118`
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- AMD or CPU `pip install torch torchvision torchaudio`
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5. 📦 Run the command below to install the required Open Source packages:
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```
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pip install -r requirements.txt
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```
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## 🔌 How to Run (Fast 🏃♂️ Version)
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Follow these steps **after** Python and all packages have been installed:
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1. Open `PowerShell` ⚡ or `Command Prompt` 💻.
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2. Input `cd `, then drag & drop the folder containing the bot code into the terminal.
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3. Hit Enter ↩️.
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4. Type `python main.py` and press Enter.
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5. Use **CAPS_LOCK** to toggle the aimbot 🎯. It begins in the *off* state.
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6. Pressing `q` 💣 at **ANY TIME** will shut down the program.
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## 🔌 How to Run (Faster 🏃♂️💨 Version)
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Follow these steps **after** Python and all packages have been installed:
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1. Open the `config.py` 📄 file and tweak the `onnxChoice` variable to correspond with your hardware specs:
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- `onnxChoice = 1` # CPU ONLY 🖥
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- `onnxChoice = 2` # AMD/NVIDIA ONLY 🎮
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- `onnxChoice = 3` # NVIDIA ONLY 🏎️
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2. IF you have an NVIDIA set up, run the following
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```
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pip install onnxruntime-gpu
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pip install cupy-cuda11x
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```
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2. Follow the same steps as for the Fast 🏃♂️ Version above except for step 4, you will run `python main_onnx.py` instead.
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## 🔌 How to Run (Fastest 🚀 Version)
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Follow these sparkly steps to get your TensorRT ready for action! 🛠️✨
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1. **Introduction** 🎬
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Watch the TensorRT section of the setup [video 🎥](https://www.youtube.com/watch?v=uniL5yR7y0M&ab_channel=RootKit) before you begin. It's loaded with useful tips!
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2. **Oops! Don't Forget the Environment** 🌱
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We forgot to mention adding environmental variable paths in the video. Make sure to do this part!
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3. **Get Support If You're Stumped** 🤔
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If you ever feel lost, you can always `@Wonder` your questions in our [Discord 💬](https://discord.gg/rootkitorg). Wonder is here to help!
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4. **Install Cupy**
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Run the following `pip install cupy-cuda11x`
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5. **CUDNN Installation** 🧩
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Click to install [CUDNN 📥](https://developer.nvidia.com/downloads/compute/cudnn/secure/8.9.6/local_installers/11.x/cudnn-windows-x86_64-8.9.6.50_cuda11-archive.zip/). You'll need a Nvidia account to proceed. Don't worry it's free.
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6. **Unzip and Relocate** 📁➡️
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Open the .zip CuDNN file and move all the folders/files to where the CUDA Toolkit is on your machine, usually at `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8`.
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7. **Get TensorRT 8.6 GA** 🔽
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Fetch [`TensorRT 8.6 GA 🛒`](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/secure/8.6.1/zip/TensorRT-8.6.1.6.Windows10.x86_64.cuda-11.8.zip).
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8. **Unzip and Relocate** 📁➡️
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Open the .zip TensorRT file and move all the folders/files to where the CUDA Toolkit is on your machine, usually at `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8`.
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9. **Python TensorRT Installation** 🎡
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Once you have all the files copied over, you should have a folder at `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\python`. If you do, good, then run the following command to install TensorRT in python.
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```
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pip install "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\python\tensorrt-8.6.1-cp311-none-win_amd64.whl"
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```
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🚨 If the following steps didn't work, don't stress out! 😅 The labeling of the files corresponds with the Python version you have installed on your machine. We're not looking for the 'lean' or 'dispatch' versions. 🔍 Just locate the correct file and replace the path with your new one. 🔄 You've got this! 💪
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10. **Set Your Environmental Variables** 🌎
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Add these paths to your environment:
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- `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\lib`
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- `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\libnvvp`
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- `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin`
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11. **Download Pre-trained Models** 🤖
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You can use one of the .engine models we supply. But if it doesn't work, then you will need to re-export it. Grab the `.pt` file here for the model you want. We recommend `yolov5s.py` or `yolov5m.py` [HERE 🔗](https://github.com/ultralytics/yolov5/releases/tag/v7.0).
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12. **Run the Export Script** 🏃♂️💻
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Time to execute `export.py` with the following command. Patience is key; it might look frozen, but it's just concentrating hard! Can take up to 20 minutes.
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```
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python .\export.py --weights ./yolov5s.pt --include engine --half --imgsz 320 320 --device 0
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```
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Note: You can pick a different YOLOv5 model size. TensorRT's power allows for larger models if desired!
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If you've followed these steps, you should be all set with TensorRT! ⚙️🚀
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## ⚙️ Configurable Settings
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*Default settings are generally great for most scenarios. Check out the comments in the code for more insights. 🔍 The configuration settings are now located in the `config.py` file!<br>
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**CAPS_LOCK is the default for flipping the switch on the autoaim superpower! ⚙️ 🎯**
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`useMask` - Set to `True` or `False` to turn on and off 🎭
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`maskWidth` - The width of the mask to use. Only used when `useMask` is `True` 📐
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`maskHeight` - The height of the mask to use. Only used when `useMask` is `True` 📐
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`aaQuitKey` - The go-to key is `q`, but if it clashes with your game style, swap it out! ⌨️♻️
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`headshot_mode` - Set to `False` if you're aiming to keep things less head-on and more centered. 🎯➡️👕
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`cpsDisplay` - Toggle off with `False` if you prefer not to display the CPS in your command station. 💻🚫
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`visuals` - Flip to `True` to witness the AI's vision! Great for sleuthing out any hiccups. 🕵️♂️✅
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`aaMovementAmp` - The preset should be on point for 99% of players. Lower the digits for smoother targeting. Recommended doses: `0.5` - `2`. ⚖️🕹️
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`confidence` - Stick with the script here unless you're the expert. 🧐✨
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`screenShotHeight` - Same as above, no need for changes unless you've got a specific vision. 📏🖼️
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`screenShotWidth` - Keep it constant as is, unless you've got reasons to adjust. 📐🖼️
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`aaDetectionBox` - Default's your best bet, change only if you've got the know-how. 📦✅
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`onnxChoice` - Gear up for the right graphics card—Nvidia, AMD, or CPU power! 💻👾
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`centerOfScreen` - Keep this switched on to stay in the game's heart. ❤️🖥️
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## 📊 Current Stats
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The bot's efficiency depends on your setup. We achieved 100-150 CPS with our test specs below 🚀.
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- AMD Ryzen 7 2700
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- 64 GB DDR4
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- Nvidia RTX 3080
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💡 Tip: Machine Learning can be tricky, so reboot if you keep hitting CUDA walls.
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## 🤝 Community Based
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We're all about collaboration. Your contributions can earn you credit and potential 💰!
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**Want to volunteer? Have video or program ideas? Tell us!**
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## ⚠️ Known Cheat-Detectable Games
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Splitgate (reported by a Discord user 🕵️♂️), EQU8 detects win32 mouse movement library.
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## 🚀 Custom Aimbots and Models
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Show off your work or new models via Pull Requests in `customScripts` or `customModels` directories, respectively. Check out the `example-user` folder for guidance.
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## 🌠 Future Ideas
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- [x] Mask Player to avoid false positives
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Happy Coding and Aiming! 🎉👾
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