Res-Softaim Features (Default Activation Key is Left-alt!)

Demo Video: https://youtu.be/yk4MmO7PUzM

Use Rootkit's Setup guide for initial Pre-Requisites

🧰 Requirements

• Nvidia RTX 980 🆙, higher or equivalent
• And one of the following:
  • Nvidia CUDA Toolkit 11.8 DOWNLOAD HERE

🚀 Pre-setup Steps

1. Download and Unzip the AI Aimbot and stash the folder somewhere handy 🗂️.
2. Ensure you've got Python installed (like a pet python 🐍) – grab version 3.11 HERE.
   • 🛑 Facing a python is not recognized... error? WATCH THIS!
   • 🛑 Is it a pip is not recognized... error? WATCH THIS!
3. Fire up PowerShell or Command Prompt on Windows 🔍.
4. To install PyTorch, select the appropriate command based on your GPU.
   • Nvidia pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118
   • AMD or CPU pip install torch torchvision torchaudio
5. 📦 Run the file below to install all the libraries

Install Requirements.bat

🔌 How to Run (Faster 🏃‍♂️💨 Version)

Follow these steps after Python and all packages have been installed:

1. Tweak the onnxChoice variable in the menu to correspond with your hardware specs:
   • onnxChoice = 1 # CPU ONLY 🖥
   • onnxChoice = 2 # AMD/NVIDIA ONLY 🎮
   • onnxChoice = 3 # NVIDIA ONLY 🏎️
2. IF you have an NVIDIA set up, run the following

   pip install onnxruntime-gpu
   pip install cupy-cuda11x
   

3. Follow the same steps as for the Fast 🏃‍♂️ Version above except for step 4, you will run python main_onnx.py instead.

🔌 How to Run (Fastest 🚀 Version)

Follow these sparkly steps to get your TensorRT ready for action! 🛠️✨

1. Introduction 🎬 Watch the TensorRT section of the setup video 🎥 before you begin. It's loaded with useful tips!

2. Oops! Don't Forget the Environment 🌱 We forgot to mention adding environmental variable paths in the video. Make sure to do this part!

3. Get Support If You're Stumped 🤔 If you ever feel lost, you can always @Wonder your questions in our Discord 💬. Wonder is here to help!

4. Install Cupy Run the following pip install cupy-cuda11x

5. CUDNN Installation 🧩 Click to install CUDNN 📥. You'll need a Nvidia account to proceed. Don't worry it's free.

6. Unzip and Relocate 📁➡️ 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.

7. Get TensorRT 8.6 GA 🔽 Fetch TensorRT 8.6 GA 🛒.

8. Unzip and Relocate 📁➡️ 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.

9. Python TensorRT Installation 🎡 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.

   pip install "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\python\tensorrt-8.6.1-cp311-none-win_amd64.whl"
   

   🚨 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! 💪

10. Set Your Environmental Variables 🌎 Add these paths to your environment:

• C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\lib
• C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\libnvvp
• C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin

11. Download Pre-trained Models 🤖 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 🔗.

12. Run the Export Script 🏃‍♂️💻

Time to run BUILD_ENGINE.bat

Note: You can pick a different YOLOv5 model size. TensorRT's power allows for larger models if desired!

If you've followed these steps, you should be all set with TensorRT! ⚙️🚀

Dont forget to select your model in the menu!