### Setup CUDA Keyring and Update Repositories

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download and install the CUDA keyring, then update the package list to include CUDA repositories.

```bash
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.0-1_all.deb
sudo dpkg -i cuda-keyring_1.0-1_all.deb
sudo apt-get update
```

--------------------------------

### Install CUDA Toolkit and Run Installer

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download and silently install the CUDA toolkit.

```bash
wget https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux.run
sudo sh cuda_12.6.3_560.35.05_linux.run --silent --toolkit
```

--------------------------------

### Download and Install CUDA Toolkit

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download the CUDA toolkit installer and silently install it with the toolkit option.

```bash
wget https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda_11.1.1_455.32.00_linux.run
sudo sh cuda_11.1.1_455.32.00_linux.run --silent --toolkit
```

--------------------------------

### Install NVIDIA Driver (Desktop)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install the NVIDIA driver silently, disabling nouveau, enabling DKMS, installing libglvnd, and running nvidia-xconfig. This is for desktop installations.

```bash
sudo sh NVIDIA-Linux-x86_64-515.65.01.run --silent --disable-nouveau --dkms --install-libglvnd --run-nvidia-xconfig
```

--------------------------------

### Install NVIDIA Driver (Laptop)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install the NVIDIA driver silently, disabling nouveau, enabling DKMS, and installing libglvnd. This is for laptop installations.

```bash
sudo sh NVIDIA-Linux-x86_64-515.65.01.run --silent --disable-nouveau --dkms --install-libglvnd
```

--------------------------------

### Install System Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Installs necessary system packages for DeepStream and NVIDIA components. Ensure these are installed before proceeding.

```bash
sudo apt-get install dkms
sudo apt-get install libssl1.1 libgstreamer1.0-0 gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav libgstreamer-plugins-base1.0-dev libgstrtspserver-1.0-0 libjansson4 libyaml-cpp-dev libjsoncpp-dev protobuf-compiler
```

--------------------------------

### Install NVIDIA Driver (Desktop)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the NVIDIA driver on a desktop, disabling nouveau drivers, enabling DKMS, installing libglvnd, and running nvidia-xconfig.

```bash
sudo sh NVIDIA-Linux-x86_64-510.47.03.run --silent --disable-nouveau --dkms --install-libglvnd --run-nvidia-xconfig
```

--------------------------------

### Download and Install CUDA Keyring

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Downloads the CUDA keyring package and installs it, then updates the apt package list.

```bash
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-keyring_1.0-1_all.deb
sudo dpkg -i cuda-keyring_1.0-1_all.deb
sudo apt-get update
```

--------------------------------

### Install GCC 12 and Update Alternatives

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install GCC version 12 and configure the system to use it as the default compiler.

```bash
sudo apt-get install gcc-12 g++-12
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 12
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-12 12
sudo update-initramfs -u
```

--------------------------------

### Install Essential Packages

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Installs fundamental development tools and kernel headers required for DeepStream installation.

```bash
sudo apt-get update
sudo apt-get install gcc make git libtool autoconf autogen pkg-config cmake python3 python3-dev python3-pip
sudo apt-get install linux-headers-$(uname -r)
```

--------------------------------

### Install CUDA Toolkit

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Downloads and installs the CUDA 12.8.1 toolkit silently.

```bash
wget https://developer.download.nvidia.com/compute/cuda/12.8.1/local_installers/cuda_12.8.1_570.124.06_linux.run
sudo sh cuda_12.8.1_570.124.06_linux.run --silent --toolkit
```

--------------------------------

### Setup Inside DeepStream Docker Container

Source: https://context7.com/marcoslucianops/deepstream-yolo/llms.txt

Install necessary build tools and multimedia packages inside the Docker container. Compile the custom inference library and run the DeepStream application.

```bash
# Inside container:
apt-get install build-essential

# Install multimedia packages (needed for MP4 streams with audio in DS 8.0)
/opt/nvidia/deepstream/deepstream/user_additional_install.sh

export CUDA_VER=12.8
make -C /workspace/nvdsinfer_custom_impl_Yolo clean && \
    make -C /workspace/nvdsinfer_custom_impl_Yolo

deepstream-app -c /workspace/deepstream_app_config.txt
```

--------------------------------

### Install CUDA Toolkit

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download and silently install the CUDA toolkit. Ensure CUDA 11.4.1 is used.

```bash
wget https://developer.download.nvidia.com/compute/cuda/11.4.1/local_installers/cuda_11.4.1_470.57.02_linux.run
sudo sh cuda_11.4.1_470.57.02_linux.run --silent --toolkit
```

--------------------------------

### Install OpenCV

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/INT8Calibration.md

Installs the OpenCV development library using apt-get. Ensure your system's package list is up-to-date before running.

```bash
sudo apt-get install libopencv-dev
```

--------------------------------

### Install DeepStream SDK (6.0.1)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install DeepStream 6.0.1 for Servers and Workstations using the provided .deb package.

```bash
sudo apt-get install ./deepstream-6.0_6.0.1-1_amd64.deb
```

--------------------------------

### Install CUDA Toolkit

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the CUDA toolkit, including the toolkit component.

```bash
sudo sh cuda_11.6.1_510.47.03_linux.run --silent --toolkit
```

--------------------------------

### Install CUDA Toolkit

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Downloads and installs the CUDA Toolkit silently. Ensure you have the correct version for your drivers.

```bash
wget https://developer.download.nvidia.com/compute/cuda/12.1.1/local_installers/cuda_12.1.1_530.30.02_linux.run
sudo sh cuda_12.1.1_530.30.02_linux.run --silent --toolkit
```

--------------------------------

### Install CUDA Toolkit

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download and install the CUDA toolkit silently. This includes the necessary libraries and tools for GPU computing.

```bash
wget https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
sudo sh cuda_11.8.0_520.61.05_linux.run --silent --toolkit
```

--------------------------------

### Install DeepStream SDK (6.0)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install DeepStream 6.0 for Servers and Workstations using the provided .deb package.

```bash
sudo apt-get install ./deepstream-6.0_6.0.0-1_amd64.deb
```

--------------------------------

### Install DeepStream SDK

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install the DeepStream SDK from a local .deb package, clear the GStreamer registry cache, and create a symbolic link for CUDA.

```bash
sudo apt-get install ./deepstream-5.1_5.1.0-1_amd64.deb
rm ${HOME}/.cache/gstreamer-1.0/registry.x86_64.bin
sudo ln -snf /usr/local/cuda-11.1 /usr/local/cuda
```

--------------------------------

### Install YOLOv9 Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/YOLOv9.md

Clone the YOLOv9 repository and install required Python packages. Ensure ONNX and related libraries are installed for model conversion.

```bash
git clone https://github.com/WongKinYiu/yolov9.git
cd yolov9
pip3 install -r requirements.txt
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Install YOLOv13 Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/YOLOv13.md

Clone the YOLOv13 repository and install necessary Python packages. It is recommended to use a virtual environment.

```bash
git clone https://github.com/iMoonLab/yolov13.git
cd yolov13
pip3 install -e .
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Install NVIDIA Driver (Desktop)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the NVIDIA driver for desktops, disabling nouveau and enabling DKMS. This command should be run before rebooting.

```bash
sudo sh NVIDIA-Linux-x86_64-535.179.run --no-cc-version-check --silent --disable-nouveau --dkms --install-libglvnd --run-nvidia-xconfig
```

--------------------------------

### Install Gold-YOLO Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/GoldYOLO.md

Clone the Gold-YOLO repository and install the required Python packages. It's recommended to use a virtual environment.

```bash
git clone https://github.com/huawei-noah/Efficient-Computing.git
cd Efficient-Computing/Detection/Gold-YOLO
pip3 install -r requirements.txt
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Install NVIDIA Driver (Laptop)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the NVIDIA driver on a laptop, disabling nouveau drivers and enabling DKMS. This command also installs libglvnd.

```bash
sudo sh NVIDIA-Linux-x86_64-510.47.03.run --silent --disable-nouveau --dkms --install-libglvnd
```

--------------------------------

### Install DeepStream 7.1

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download and install DeepStream 7.1 for servers and workstations. This includes setting up CUDA symbolic links.

```bash
wget --content-disposition 'https://api.ngc.nvidia.com/v2/resources/org/nvidia/deepstream/7.1/files?redirect=true&path=deepstream-7.1_7.1.0-1_amd64.deb' -O deepstream-7.1_7.1.0-1_amd64.deb
sudo apt-get install ./deepstream-7.1_7.1.0-1_amd64.deb
rm ${HOME}/.cache/gstreamer-1.0/registry.x86_64.bin
sudo ln -snf /usr/local/cuda-12.6 /usr/local/cuda
```

--------------------------------

### Install NVIDIA Driver (Laptop)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the NVIDIA driver for laptops, disabling nouveau and enabling DKMS. This command should be run before rebooting.

```bash
sudo sh NVIDIA-Linux-x86_64-535.179.run --no-cc-version-check --silent --disable-nouveau --dkms --install-libglvnd
```

--------------------------------

### Clone D-FINE Repo and Install Requirements

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/DFINE.md

Clone the D-FINE repository and install necessary Python packages. It's recommended to use a Python virtual environment.

```bash
git clone https://github.com/Peterande/D-FINE.git
cd D-FINE
pip3 install -r requirements.txt
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Install DeepStream SDK

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Installs the DeepStream SDK from a .deb package, clears the GStreamer registry cache, and creates a symbolic link for CUDA.

```bash
sudo apt-get install ./deepstream-6.1_6.1.0-1_amd64.deb
rm ${HOME}/.cache/gstreamer-1.0/registry.x86_64.bin
sudo ln -snf /usr/local/cuda-11.6 /usr/local/cuda
```

--------------------------------

### Install TensorRT and Associated Libraries

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Add NVIDIA CUDA repository, update package list, and install TensorRT development and runtime libraries along with cuDNN.

```bash
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ "
sudo apt-get update
sudo apt-get install libnvinfer-dev=10.4.0.26-1+cuda12.6 libnvinfer-dispatch-dev=10.4.0.26-1+cuda12.6 libnvinfer-dispatch10=10.4.0.26-1+cuda12.6 libnvinfer-headers-dev=10.4.0.26-1+cuda12.6 libnvinfer-headers-plugin-dev=10.4.0.26-1+cuda12.6 libnvinfer-lean-dev=10.4.0.26-1+cuda12.6 libnvinfer-lean10=10.4.0.26-1+cuda12.6 libnvinfer-plugin-dev=10.4.0.26-1+cuda12.6 libnvinfer-plugin10=10.4.0.26-1+cuda12.6 libnvinfer-vc-plugin-dev=10.4.0.26-1+cuda12.6 libnvinfer-vc-plugin10=10.4.0.26-1+cuda12.6 libnvinfer10=10.4.0.26-1+cuda12.6 libnvonnxparsers-dev=10.4.0.26-1+cuda12.6 libnvonnxparsers10=10.4.0.26-1+cuda12.6 tensorrt-dev=10.4.0.26-1+cuda12.6 libnvinfer-samples=10.4.0.26-1+cuda12.6 libnvinfer-bin=10.4.0.26-1+cuda12.6 libcudnn9-cuda-12=9.3.0.75-1 libcudnn9-dev-cuda-12=9.3.0.75-1
sudo apt-mark hold libnvinfer* libnvparsers* libnvonnxparsers* libcudnn9* python3-libnvinfer* uff-converter-tf* onnx-graphsurgeon* graphsurgeon-tf* tensorrt*
```

--------------------------------

### Clone YOLOv5 Repo and Install Requirements

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/YOLOv5.md

Clone the YOLOv5 repository and install necessary Python packages. It's recommended to use a virtual environment.

```bash
git clone https://github.com/ultralytics/yolov5.git
cd yolov5
pip3 install -r requirements.txt
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Download NVIDIA Driver Installer

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Downloads the NVIDIA driver installer for Linux x86_64 systems. Use the appropriate version for your hardware.

```bash
wget https://us.download.nvidia.com/XFree86/Linux-x86_64/525.125.06/NVIDIA-Linux-x86_64-525.125.06.run
```

--------------------------------

### Download and Install CUDA Toolkit

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download the CUDA toolkit and install it silently with the toolkit option. This includes the NVIDIA driver version 515.65.01.

```bash
wget https://developer.download.nvidia.com/compute/cuda/11.7.1/local_installers/cuda_11.7.1_515.65.01_linux.run
sudo sh cuda_11.7.1_515.65.01_linux.run --silent --toolkit
```

--------------------------------

### Install MMDetection Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/CODETR.md

Install the MMDetection framework and its dependencies, including PyTorch, MMCV, and MMDeploy. Ensure you are using a Python virtual environment.

```bash
git clone https://github.com/open-mmlab.git
cd mmdetection
pip3 install openmim
mim install mmengine
mim install mmdeploy
mim install "mmcv>=2.0.0rc4,<2.2.0"
pip3 install -v -e .
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Configure TensorRT Repositories and Install

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Adds the NVIDIA TensorRT repository, updates package lists, and installs TensorRT and cuDNN libraries. It then holds these packages to prevent automatic updates.

```bash
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/3bf863cc.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ "
sudo apt-get update
sudo apt-get install libnvinfer8=8.5.3-1+cuda11.8 libnvinfer-plugin8=8.5.3-1+cuda11.8 libnvparsers8=8.5.3-1+cuda11.8 libnvonnxparsers8=8.5.3-1+cuda11.8 libnvinfer-bin=8.5.3-1+cuda11.8 libnvinfer-dev=8.5.3-1+cuda11.8 libnvinfer-plugin-dev=8.5.3-1+cuda11.8 libnvparsers-dev=8.5.3-1+cuda11.8 libnvonnxparsers-dev=8.5.3-1+cuda11.8 libnvinfer-samples=8.5.3-1+cuda11.8 libcudnn8=8.7.0.84-1+cuda11.8 libcudnn8-dev=8.7.0.84-1+cuda11.8 python3-libnvinfer=8.5.3-1+cuda11.8 python3-libnvinfer-dev=8.5.3-1+cuda11.8
sudo apt-mark hold libnvinfer* libnvparsers* libnvonnxparsers* libcudnn8* python3-libnvinfer*
```

--------------------------------

### Install DeepStream 7.0 SDK

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download and install the DeepStream 7.0 SDK for servers and workstations. This command also ensures the correct CUDA version is linked.

```bash
wget --content-disposition 'https://api.ngc.nvidia.com/v2/resources/org/nvidia/deepstream/7.0/files?redirect=true&path=deepstream-7.0_7.0.0-1_amd64.deb' -O deepstream-7.0_7.0.0-1_amd64.deb
sudo apt-get install ./deepstream-7.0_7.0.0-1_amd64.deb
rm ${HOME}/.cache/gstreamer-1.0/registry.x86_64.bin
sudo ln -snf /usr/local/cuda-12.2 /usr/local/cuda
```

--------------------------------

### Install NVIDIA Driver for Laptops (Silent)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the NVIDIA driver on laptops, disabling nouveau and enabling dkms. This step requires a reboot.

```bash
sudo sh NVIDIA-Linux-x86_64-560.35.03.run --no-cc-version-check --silent --disable-nouveau --dkms --install-libglvnd
```

--------------------------------

### Download YOLOv12 Repository and Install Requirements

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/YOLOv12.md

Clone the YOLOv12 repository and install its dependencies, including ONNX and ONNX Runtime. Using a Python virtual environment is recommended.

```bash
git clone https://github.com/sunsmarterjie/yolov12.git
cd yolov12
pip3 install -e .
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Install MMYOLO Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/RTMDet.md

Install the necessary dependencies for the MMYOLO framework, including PyTorch, MMCV, and other required libraries. It is recommended to use a Python virtual environment.

```bash
git clone https://github.com/open-mmlab/mmyolo.git
cd mmyolo
pip3 install openmim
mim install "mmengine>=0.6.0"
mim install "mmcv>=2.0.0rc4,<2.1.0"
mim install "mmdet>=3.0.0,<4.0.0"
pip3 install -r requirements/albu.txt
mim install -v -e .
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Install NVIDIA Driver (Desktop - Silent)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Installs the NVIDIA driver silently on desktops, disabling nouveau drivers and enabling DKMS. Includes running nvidia-xconfig.

```bash
sudo sh NVIDIA-Linux-x86_64-570.195.03.run --no-cc-version-check --silent --disable-nouveau --dkms --install-libglvnd --run-nvidia-xconfig
```

--------------------------------

### Install DeepStream SDK

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install the DeepStream SDK 6.1.1 using the provided .deb package. This also involves removing and creating a symbolic link for the CUDA directory.

```bash
sudo apt-get install ./deepstream-6.1_6.1.1-1_amd64.deb
rm ${HOME}/.cache/gstreamer-1.0/registry.x86_64.bin
sudo ln -snf /usr/local/cuda-11.7 /usr/local/cuda
```

--------------------------------

### Install TensorRT

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Add the CUDA repository, update package lists, and install TensorRT and cuDNN packages. It's recommended to hold these packages to prevent accidental upgrades.

```bash
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/3bf863cc.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ "
sudo apt-get update
sudo apt-get install libnvinfer8=8.4.1-1+cuda11.6 libnvinfer-plugin8=8.4.1-1+cuda11.6 libnvparsers8=8.4.1-1+cuda11.6 libnvonnxparsers8=8.4.1-1+cuda11.6 libnvinfer-bin=8.4.1-1+cuda11.6 libnvinfer-dev=8.4.1-1+cuda11.6 libnvinfer-plugin-dev=8.4.1-1+cuda11.6 libnvparsers-dev=8.4.1-1+cuda11.6 libnvonnxparsers-dev=8.4.1-1+cuda11.6 libnvinfer-samples=8.4.1-1+cuda11.6 libcudnn8=8.4.1.50-1+cuda11.6 libcudnn8-dev=8.4.1.50-1+cuda11.6 python3-libnvinfer=8.4.1-1+cuda11.6 python3-libnvinfer-dev=8.4.1-1+cuda11.6
sudo apt-mark hold libnvinfer* libnvparsers* libnvonnxparsers* libcudnn8* python3-libnvinfer*
```

--------------------------------

### Install NVIDIA Driver (Desktop)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the NVIDIA driver on a desktop, disabling nouveau and enabling DKMS, and running nvidia-xconfig. This step will disable the nouveau drivers.

```bash
sudo sh NVIDIA-Linux-x86_64-460.32.03.run --silent --disable-nouveau --dkms --install-libglvnd --run-nvidia-xconfig
```

--------------------------------

### Configure NVIDIA Prime for Laptops

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Installs nvidia-prime and selects the NVIDIA GPU for systems with NVIDIA Optimus.

```bash
sudo apt-get install nvidia-prime
sudo prime-select nvidia
```

--------------------------------

### Prepare Calibration Images and Set Environment Variables

Source: https://context7.com/marcoslucianops/deepstream-yolo/llms.txt

Prepare a set of calibration images for INT8 mode and set the necessary environment variables for the calibration process. Ensure the correct number of images are selected and copied.

```bash
mkdir calibration
for jpg in $(ls -1 val2017/*.jpg | sort -R | head -1000); do
    cp "${jpg}" calibration/
done
realpath calibration/*.jpg > calibration.txt
```

```bash
export INT8_CALIB_IMG_PATH=calibration.txt
export INT8_CALIB_BATCH_SIZE=8   # increase for faster calibration / more accuracy
```

--------------------------------

### Install NVIDIA Driver for Desktops (Silent)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the NVIDIA driver on desktops, disabling nouveau and enabling dkms. This step requires a reboot and runs nvidia-xconfig.

```bash
sudo sh NVIDIA-Linux-x86_64-560.35.03.run --no-cc-version-check --silent --disable-nouveau --dkms --install-libglvnd --run-nvidia-xconfig
```

--------------------------------

### Download CUDA Toolkit

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download the CUDA toolkit local installer for Linux x86_64.

```bash
wget https://developer.download.nvidia.com/compute/cuda/11.6.1/local_installers/cuda_11.6.1_510.47.03_linux.run
```

--------------------------------

### Install CUDA Toolkit 12.2.2

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download and silently install CUDA Toolkit 12.2.2. This command installs the toolkit without user interaction.

```bash
wget https://developer.download.nvidia.com/compute/cuda/12.2.2/local_installers/cuda_12.2.2_535.104.05_linux.run
sudo sh cuda_12.2.2_535.104.05_linux.run --silent --toolkit
```

--------------------------------

### Install TensorRT

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install TensorRT and its associated libraries using apt-get. This command adds the NVIDIA CUDA repository, updates package lists, and installs specific versions of TensorRT and cuDNN.

```bash
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/3bf863cc.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ "
sudo apt-get update
sudo apt-get install libnvinfer8=8.5.2-1+cuda11.8 libnvinfer-plugin8=8.5.2-1+cuda11.8 libnvparsers8=8.5.2-1+cuda11.8 libnvonnxparsers8=8.5.2-1+cuda11.8 libnvinfer-bin=8.5.2-1+cuda11.8 libnvinfer-dev=8.5.2-1+cuda11.8 libnvinfer-plugin-dev=8.5.2-1+cuda11.8 libnvparsers-dev=8.5.2-1+cuda11.8 libnvonnxparsers-dev=8.5.2-1+cuda11.8 libnvinfer-samples=8.5.2-1+cuda11.8 libcudnn8=8.7.0.84-1+cuda11.8 libcudnn8-dev=8.7.0.84-1+cuda11.8 python3-libnvinfer=8.5.2-1+cuda11.8 python3-libnvinfer-dev=8.5.2-1+cuda11.8
sudo apt-mark hold libnvinfer* libnvparsers* libnvonnxparsers* libcudnn8* python3-libnvinfer*
```

--------------------------------

### Install Meson and Ninja for GLib Migration

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/README.md

Install Meson and Ninja build tools, which are prerequisites for migrating GLib to a newer version. It is recommended to use a Python virtual environment.

```bash
pip3 install meson
pip3 install ninja
```

--------------------------------

### Build and Install GLib 2.76.6

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/README.md

Clone the GLib repository, checkout version 2.76.6, and build/install it using Meson and Ninja. This resolves issues with older GLib versions.

```bash
git clone https://github.com/GNOME/glib.git
cd glib
git checkout 2.76.6
Meson build --prefix=/usr
ninja -C build/
cd build/
ninja install
```

--------------------------------

### Install DeepStream 8.0 Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Installs GStreamer, SSL, and other libraries required for DeepStream 8.0.

```bash
sudo apt-get install dkms
sudo apt-get install libssl3 libssl-dev libgles2-mesa-dev libgstreamer1.0-0 gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav libgstreamer-plugins-base1.0-dev libstrtspserver-1.0-0 libjansson4 libyaml-cpp-dev libjsoncpp-dev protobuf-compiler libmosquitto1
```

--------------------------------

### Download NVIDIA Driver for TITAN, GeForce, RTX, Quadro

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download the NVIDIA driver run file for desktop GPUs.

```bash
wget https://us.download.nvidia.com/XFree86/Linux-x86_64/560.35.03/NVIDIA-Linux-x86_64-560.35.03.run
```

--------------------------------

### YoloLayer TensorRT Plugin Build Instructions

Source: https://context7.com/marcoslucianops/deepstream-yolo/llms.txt

Instructions for building the YoloLayer TensorRT plugin for Darknet models. Demonstrates how to handle multiple simultaneous YOLO GIEs by assigning unique plugin versions and rebuilding.

```bash
# Plugin is registered automatically when the .so is loaded.
# Plugin name / version used internally:
#   YOLOLAYER_PLUGIN_NAME    = "YoloLayer_TRT"
#   YOLOLAYER_PLUGIN_VERSION = "1"   (increment for multiple GIEs)

# For multiple simultaneous YOLO GIEs, each GIE's nvdsinfer_custom_impl_Yolo
# must have a unique plugin version to avoid TensorRT registry conflicts.
# Edit nvdsinfer_custom_impl_Yolo/yoloPlugins.h line 43:
#   gie1: const char* YOLOLAYER_PLUGIN_VERSION {"1"};
#   gie2: const char* YOLOLAYER_PLUGIN_VERSION {"2"};
#   gie3: const char* YOLOLAYER_PLUGIN_VERSION {"3"};

# Then rebuild each GIE independently:
export CUDA_VER=12.8
make -C gie1/nvdsinfer_custom_impl_Yolo clean && make -C gie1/nvdsinfer_custom_impl_Yolo
make -C gie2/nvdsinfer_custom_impl_Yolo clean && make -C gie2/nvdsinfer_custom_impl_Yolo
```

--------------------------------

### Add CUDA Keyring and Update Repositories

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Downloads and installs the CUDA GPG key and updates the package list to include CUDA repositories.

```bash
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/cuda-keyring_1.0-1_all.deb
sudo dpkg -i cuda-keyring_1.0-1_all.deb
sudo apt-get update
```

--------------------------------

### Install DKMS

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Installs the Dynamic Kernel Module Support package, which is required if using the default Ubuntu kernel.

```bash
sudo apt-get install dkms
```

--------------------------------

### Add CUDA Keyring and Update Repositories

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Downloads and installs the CUDA GPG key and updates the package list to include CUDA repositories.

```bash
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.0-1_all.deb
sudo dpkg -i cuda-keyring_1.0-1_all.deb
sudo apt-get update
```

--------------------------------

### Install DeepStream Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install necessary dependencies for DeepStream, including dkms, OpenSSL, GStreamer components, and other libraries.

```bash
sudo apt-get install dkms
sudo apt-get install libssl1.1 libgstreamer1.0-0 gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav libgstrtspserver-1.0-0 libjansson4 libyaml-cpp-dev
```

--------------------------------

### Install YOLO-NAS Requirements

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/YOLONAS.md

Clone the YOLO-NAS repository and install its dependencies. It is recommended to use a Python virtual environment.

```bash
git clone https://github.com/Deci-AI/super-gradients.git
cd super-gradients
pip3 install -r requirements.txt
python3 setup.py install
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Install DeepStream 5.1 Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install necessary dependencies for DeepStream 5.1, including dkms and various gstreamer plugins.

```bash
sudo apt-get install dkms
sudo apt-get install libssl1.0.0 libgstreamer1.0-0 gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav libgstrtspserver-1.0-0 libjansson4=2.11-1
```

--------------------------------

### Install DeepStream Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Installs essential libraries for DeepStream, including SSL, GStreamer components, RTSP server, and Jansson.

```bash
sudo apt-get install libssl1.0.0 libgstreamer1.0-0 gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav libgstrtspserver-1.0-0 libjansson4
```

--------------------------------

### Download NVIDIA Driver (TITAN, GeForce, RTX/Quadro)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Downloads the NVIDIA driver runfile for compatible GPU series.

```bash
wget https://us.download.nvidia.com/XFree86/Linux-x86_64/570.195.03/NVIDIA-Linux-x86_64-570.195.03.run
```

--------------------------------

### Install DeepStream 6.1.1 Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install essential dependencies for DeepStream 6.1.1, including dkms and various gstreamer plugins and libraries.

```bash
sudo apt-get install dkms
sudo apt-get install libssl1.1 libgstreamer1.0-0 gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav libgstreamer-plugins-base1.0-dev libgstrtspserver-1.0-0 libjansson4 libyaml-cpp-dev
```

--------------------------------

### Download YOLOv12 Model Weights

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/YOLOv12.md

Download the pre-trained YOLOv12 model weights in .pt format. This example uses yolov12s.pt, but custom models can also be used.

```bash
wget https://github.com/sunsmarterjie/yolov12/releases/download/turbo/yolov12s.pt
```

--------------------------------

### Install DeepStream 7.0 Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install essential dependencies for DeepStream 7.0, including GStreamer, SSL libraries, and JSON/YAML parsers.

```bash
sudo apt-get install dkms
sudo apt-get install libssl3 libssl-dev libgles2-mesa-dev libgstreamer1.0-0 gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav libgstreamer-plugins-base1.0-dev libstrtspserver-1.0-0 libjansson4 libyaml-cpp-dev libjsoncpp-dev protobuf-compiler
```

--------------------------------

### Install NVIDIA Driver (Desktop)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the NVIDIA driver on a desktop, disabling nouveau, using DKMS, and running nvidia-xconfig. Remove --dkms if using kernel 5.11.0.

```bash
sudo sh NVIDIA-Linux-x86_64-470.129.06.run --silent --disable-nouveau --dkms --install-libglvnd --run-nvidia-xconfig
```

--------------------------------

### Install DeepStream 7.1 Dependencies

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install essential packages required for DeepStream 7.1, including dkms and various GStreamer libraries.

```bash
sudo apt-get install dkms
sudo apt-get install libssl3 libssl-dev libgles2-mesa-dev libgstreamer1.0-0 gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav libgstreamer-plugins-base1.0-dev libgstrtspserver-1.0-0 libjansson4 libyaml-cpp-dev libjsoncpp-dev protobuf-compiler
```

--------------------------------

### Download YOLOv7 Model Weights

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/YOLOv7.md

Download pre-trained YOLOv7 model weights from the official releases. This example downloads the default YOLOv7 weights.

```bash
wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt
```

--------------------------------

### Download NVIDIA Driver Installer (Tesla)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Downloads the NVIDIA driver installer for Tesla series GPUs. Use the appropriate version for your hardware.

```bash
wget https://us.download.nvidia.com/tesla/525.125.06/NVIDIA-Linux-x86_64-525.125.06.run
```

--------------------------------

### Download YOLO-Master Model

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/YOLOMaster.md

Download a pre-trained YOLO-Master model in .pt format from the official releases. This example downloads the YOLO-Master-N model.

```bash
wget https://github.com/Tencent/YOLO-Master/releases/download/v0.0.0/yolo-master-v0.1-n.pt
```

--------------------------------

### Install DeepStream 8.0

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Download and install the DeepStream 8.0 deb package. This also includes steps to set the CUDA symbolic link.

```bash
wget --content-disposition 'https://api.ngc.nvidia.com/v2/resources/org/nvidia/deepstream/8.0/files?redirect=true&path=deepstream-8.0_8.0.0-1_amd64.deb' -O deepstream-8.0_8.0.0-1_amd64.deb
sudo apt-get install ./deepstream-8.0_8.0.0-1_amd64.deb
rm ${HOME}/.cache/gstreamer-1.0/registry.x86_64.bin
sudo ln -snf /usr/local/cuda-12.8 /usr/local/cuda
```

--------------------------------

### Install Python Dependencies for YOLOR

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/YOLOR.md

Installs necessary Python packages for YOLOR model conversion. It's recommended to use a virtual environment.

```bash
git clone https://github.com/WongKinYiu/yolor.git
cd yolor
pip3 install -r requirements.txt
pip3 install onnx onnxslim onnxruntime
```

--------------------------------

### Set Model Engine File (Batch Size 2, Network Mode 0)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/customModels.md

Example for specifying the model engine file when batch size is 2 and network mode is 0 (FP32).

```properties
model-engine-file=model_b2_gpu0_fp32.engine
```

--------------------------------

### Set Model Engine File (Batch Size 1, Network Mode 2)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/customModels.md

Example for specifying the model engine file when batch size is 1 and network mode is 2 (FP16).

```properties
model-engine-file=model_b1_gpu0_fp16.engine
```

--------------------------------

### Download PP-YOLOE Model Weights

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/PPYOLOE.md

Download the pre-trained model weights in .pdparams format from the PaddleDetection releases. This is an example for PP-YOLOE+_s.

```bash
wget https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_80e_coco.pdparams
```

--------------------------------

### Install NVIDIA Driver (Laptop)

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Silently install the NVIDIA driver on a laptop, disabling nouveau and enabling DKMS. This step will disable the nouveau drivers.

```bash
sudo sh NVIDIA-Linux-x86_64-460.32.03.run --silent --disable-nouveau --dkms --install-libglvnd
```

--------------------------------

### Install DeepStream SDK 6.2

Source: https://github.com/marcoslucianops/deepstream-yolo/blob/master/docs/dGPUInstalation.md

Install DeepStream SDK 6.2 from a local .deb package. This command also creates a symbolic link for CUDA.

```bash
sudo apt-get install ./deepstream-6.2_6.2.0-1_amd64.deb
rm ${HOME}/.cache/gstreamer-1.0/registry.x86_64.bin
sudo ln -snf /usr/local/cuda-11.8 /usr/local/cuda
```