Classic computer vision operations using NVIDIA GPUs
Using only computer vision techniques (edge detection, thresholding, blurring, etc.) a developer can put together useful applications without having to use computational expensive machine learning algorithms. For example using background subtraction a developer could create an application that counts people going in and out of a store, or an application that counts cars entering and exiting a parking garage, or a motion detection application for use in security cameras. If developers wish to track the objects detected from background subtraction they simply apply contours to them. To speed up these applications a developer can use CUDA APIs to offload computer vision algorithms from the CPU to the GPU.
| Folder | Description |
|---|---|
| background_subtraction | Program use MOG2 background subtractor to track people in a video frame using either CUDA or CPU to execute the algorithm |
| color_space_cuda | Program demonstrate how to optimally use CUDA in your application to move from one color space to another and simultaneously display them to the screen in real time. |
This app requires an alwaysAI account. Head to the Sign up page if you don't have an account yet. Follow the instructions to install the alwaysAI tools on your development machine.
Once the alwaysAI tools are installed on your development machine (or edge device if developing directly on it) you can run the following CLI commands:
To set up the target device & install path
aai app configure
To install the app to your target
aai app install
To start the app
aai app start