The SK-AM62A-LP is built around TI's AM62A AI vision processor, which includes an image signal processor (ISP) supporting up to 5 MP at 60 fps, a 2 teraoperations per second (TOPS) AI accelerator, a quad-core 64-bit Arm® Cortex®-A53 microprocessor, a single-core Arm Cortex-R5F and an H.264/H.265 video encode/decode. SK-AM62A-LP is an ideal choice for those looking to develop low-power smart camera, dashcam, machine-vision camera and automotive front-camera applications.
Looking to connect different sensors? Our Linux SDK lets you easily send data from any sensor and any programming language (with examples in Node.js, Python, Go and C++) into Edge Impulse.
5. Deploying back to device
To run your impulse locally run on your Linux platform:
This will automatically compile your model with full hardware acceleration, download the model to your local machine, and then start classifying. Our Linux SDK has examples on how to integrate the model with your favourite programming language.
If you have an image model then you can get a peek of what your device sees by being on the same network as your device, and finding the 'Want to see a feed of the camera and live classification in your browser' message in the console. Open the URL in a browser and both the camera feed and the classification are shown:
Live feed with classification results
Projects that can run on the AM62A!
Some of these projects were first developed for the TDA4VM, but will run on the AM62A as well!
Texas Instruments provides models that are optimized to run on the AM62A. Those that have Edge Impulse support are found in the links below. Each Github repository has instructions on installation to your Edge Impulse project. The original source of these optimized models are found at Texas Instruments EdgeAI Model Zoo.