Custom rust tensorrt model and weights (#132)

* rust custom model

* new model engine and weights

* Conda installation

.gitignore

@@ -19,3 +19,5 @@ venv
 *.old
 elite
 !Robloxmodel.pt
+!rust.pt
+!rust.engine

Conda/00 - Conda.md

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+# Conda: A Package and Environment Manager
+
+## What is Conda?
+
+Conda is an open-source package management system and environment management system. It was created for Python programs, but it can package and distribute software for any language.
+
+## Key Features of Conda
+
+1. **Package Management**: Conda helps you manage and keep track of packages in your projects. It can install packages from the Conda package repository and other sources.
+
+2. **Environment Management**: Conda allows you to create separate environments containing files, packages, and their dependencies that will not interfere with each other. This can be extremely useful when working on projects with different requirements.
+
+3. **Cross-Platform**: Conda is a cross-platform tool, which means it works on Windows, macOS, and Linux.
+
+4. **Language Agnostic**: Originally, Conda was created for Python. Now, it can handle packages from any language, which is a big advantage over pip, which is Python-specific.
+
+## Benefits of Using Conda
+
+- **Simplicity**: Conda simplifies package management and deployment.
+- **Reproducibility**: Conda allows you to share your environments with others, which helps in reproducing research.
+- **Isolation**: With Conda, you can easily create isolated environments to separate different projects.
+- **Wide Package Support**: Conda supports a wide array of packages, and it's not limited to Python.
+
+In conclusion, Conda is a powerful tool for managing packages and environments, making it easier to manage projects and their dependencies.

Conda/01 - Miniconda install instructions.md

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+```markdown
+# Installing Miniconda
+
+Follow these steps to install Miniconda on your system:
+
+## Step 1: Download Miniconda
+
+First, download the appropriate Miniconda installer for your system from the [official Miniconda website](https://docs.conda.io/en/latest/miniconda.html).
+
+## Step 2: Run the Installer
+
+- **Windows**: Double click the `.exe` file and follow the instructions.
+- **macOS and Linux**: Open a terminal, navigate to the directory where you downloaded the installer, and run the following command:
+```
+
+```bash
+bash Miniconda3-latest-Linux-x86_64.sh
+```
+
+Replace `Miniconda3-latest-Linux-x86_64.sh` with the name of the file you downloaded.
+
+## Step 3: Follow the Prompts
+
+The installer will prompt you to review the license agreement, choose the install location, and optionally allow the installer to initialize Miniconda3 by appending it to your `PATH`.
+
+## Step 4: Verify the Installation
+
+To verify that the installation was successful, open a new terminal window and type:
+
+```bash
+conda list
+```
+
+If Miniconda has been installed and added to your `PATH`, this should display a list of installed packages.
+
+## Step 5: Update Conda to the Latest Version
+
+It's a good practice to make sure you're running the latest version of Conda. You can update it by running:
+
+```bash
+conda update conda
+```
+
+That's it! You have successfully installed Miniconda on your system.
+
+Now when you open up a terminal you should see a prompt and (base) to indicate no conda enviroment is active.
+
+![Your console](imgs/console.jpg)

Conda/02 - Create RootKit environment.md

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+```markdown
+# Creating a New Conda Environment with Python 3.11
+
+Follow these steps to create a new Conda environment with Python 3.11:
+
+## Step 1: Open a Terminal
+
+Open a terminal window. This could be Git Bash, Terminal on macOS, or Command Prompt on Windows.
+
+## Step 2: Create a New Conda Environment
+
+To create a new Conda environment with Python 3.11, use the following command:
+```
+
+```bash
+conda create --name RootKit python=3.11
+```
+
+In this command, `RootKit` is the name of the new environment, and `python=3.11` specifies that we want Python 3.11 in this environment.
+
+## Step 3: Activate the New Environment
+
+After creating the new environment, you need to activate it using the following command:
+
+```bash
+conda activate RootKit
+```
+
+Now, `RootKit` is your active environment.
+
+## Step 4: Verify Python Version
+
+To verify that the correct version of Python is installed in your new environment, use the following command:
+
+```bash
+python --version
+```
+
+This should return `Python 3.11.x`.
+
+That's it! You have successfully created a new Conda environment with Python 3.11.

Conda/03 - Clone or copy the AI Aimbot repo.md

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+```markdown
+# Cloning a GitHub Repository
+
+Cloning a GitHub repository creates a local copy of the remote repo. This allows you to save all files from the repository on your local computer. Here's how you can do it:
+
+## Step 1: Copy the Repository URL
+
+Navigate to the main page of the repository on GitHub and click the "Code" button. Then click the "copy to clipboard" button to copy the repository URL.
+
+## Step 2: Open a Terminal
+
+Open a terminal window on your computer. If you're using Windows, you can use Git Bash or Command Prompt. On macOS, you can use the Terminal app.
+
+## Step 3: Navigate to the Directory
+
+Navigate to the directory where you want to clone the repository using the `cd` (change directory) command. For example:
+```
+
+```bash
+cd /path/to/your/directory
+```
+
+## Step 4: Clone the Repository
+
+Now, run the `git clone` command followed by the URL of the repository that you copied in step 1:
+
+```bash
+git clone https://github.com/RootKit-Org/AI-Aimbot.git
+```
+
+Replace `https://github.com/RootKit-Org/AI-Aimbot.git` with the URL you copied.
+
+## Step 5: Verify the Cloning Process
+
+Navigate into the cloned repository and list its files to verify that the cloning process was successful:
+
+```bash
+cd AI-Aimbot
+ls
+```
+
+Replace `AI-Aimbot` with the name of your repository if you called it something else. The `ls` command will list all the files in the directory.
+
+That's it! You have successfully cloned a GitHub repository to your local machine.
+
+By cloning the repo, any later changes you can git pull.

Conda/04 - Start installing the requirements.md

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+```markdown
+# Installing Requirements
+
+Follow these steps to install all the requirements to your system:
+
+## Step 1: Activate your environment:
+
+## Step 2: Only if you have an NVIDIA graphics card - Download and Install CUDA:
+
+Nvidia CUDA Toolkit 11.8 [DOWNLOAD HERE](https://developer.nvidia.com/cuda-11-8-0-download-archive)
+
+## Step 3: Install PYTORCH:
+
+- For NVIDIA GPU:
+
+pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113
+
+- For AMD or CPU only:
+
+pip install torch torchvision torchaudio
+
+## Step 4: Install requirements.txt:
+
+pip install -r requirements.txt
+
+## Step 5: Install additional modules:
+
+Because you are using Conda, you need to install additional requirements in your environment.
+
+pip install -r Conda/additionalRequirements.txt
+
+## Step 6: Test your installation:
+
+To test your installation, run the following command:
+
+python main.py
+
+You should now have a working AI AIMBOT. If you want to use the fastest version continue the installation steps on the RootKit AI Aimbot README.md
+```

Conda/additionalRequirements.txt

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+argilla
+bettercam
+datasets
+fastapi
+langchainplus-sdk
+langsmith
+markdownlit
+onnx
+onnxruntime
+opencv-python
+panel
+pygetwindow
+sentence-transformers
+streamlit
+streamlit-camera-input-live
+streamlit-extras
+streamlit-faker
+streamlit-image-coordinates
+streamlit-keyup
+transformers

customModels/rust/readme.md

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+# Explain your model
+Rust dataset.  6k images - 10/10/80 split.  Included weights file - best.pt
+
+Tell the community about your model
+- What data was it trained on?
+- Rust Images
+- How much data was it trained on?
+- 6k Images
+- How many models do you have?
+- 1
+- Are they for pytorch, onnx, tensorrt, something else?
+- tensorrt
+- Any set up info
+