Frigate is a popular open-source video surveillance software that uses computer vision algorithms to detect and classify objects in video footage. While Frigate is designed to run on low-powered devices such as Raspberry Pi, its processing power can be limited. GPU acceleration can greatly improve Frigate’s performance, allowing it to process high-resolution video feeds and multiple cameras more efficiently. NVIDIA GPUs are currently supported, and you’ll need to have the CUDA toolkit installed to use GPU acceleration. By enabling GPU acceleration in Frigate and monitoring its performance using NVIDIA System Management Interface, users can enjoy faster and more accurate video surveillance capabilities. Techpotamus is providing a comlete guide on Frigate GPU Acceleration to help you maxing out your GPU performance.
Why use Frigate with GPU Acceleration?
While Frigate can run on a Raspberry Pi, it’s limited by the hardware’s processing power. Using GPU acceleration can greatly improve Frigate’s performance, allowing it to process video footage faster and more accurately. This is especially useful for high-resolution video feeds or when using multiple cameras. If you are facing errors while doing Frigate GPU Acceleration like Error Occurred On GPUid: 100 then you can use some precautionary measures like cleaning you GPU and others to get rid of it.
What hardware do I need for Frigate GPU Acceleration?
To use Frigate with GPU acceleration, you’ll need a device with a compatible GPU. NVIDIA GPUs are currently supported, and you’ll need to have the CUDA toolkit installed. You can check if your GPU is compatible by visiting the NVIDIA website.
How to install CUDA Toolkit for Frigate GPU Acceleration?
To install the CUDA toolkit on your device, follow these steps:
- Visit the NVIDIA website and download the CUDA toolkit that corresponds to your operating system.
- Run the installer and follow the prompts to install the toolkit.
- Once the installation is complete, open a terminal window and verify that the toolkit is installed by running the command ‘
nvcc --version.
How to enable Frigate GPU Acceleration?
Once you have the CUDA toolkit installed, you can enable GPU acceleration in Frigate by following these steps:
- Open the Frigate configuration file (‘
config.yml‘) in a text editor. - Look for the
camerasection and find the camera you want to enable GPU acceleration for. - Add the
detectorsection to the camera configuration, and set the ‘type‘ to ‘yolo‘. - Set the ‘
model‘ to the path of the YOLO model file you want to use (e.g., ‘yolov4-tiny-416‘). - Set the ‘
device‘ to ‘GPU’. - Save the configuration file and restart Frigate.
How to monitor Frigate GPU Acceleration performance?
You can monitor Frigate’s GPU acceleration performance by using the NVIDIA System Management Interface (nvidia-smi) tool. This tool displays real-time information about GPU usage, temperature, and power consumption.
To use nvidia-smi, open a terminal window and run the command ‘watch -n 1 nvidia-smi‘. This will display the GPU usage information in real-time.
Conclusion
Using GPU acceleration can greatly improve Frigate’s performance, allowing it to process video footage faster and more accurately. By following the steps outlined in this guide, you can enable GPU acceleration in Frigate and monitor its performance using the NVIDIA System Management Interface tool. While maxing out GPU performance, GPU heats up sometimes and in some cases GPU thermal throttling occurs, so you can also get rid of it through simple steps.