We’ve been hard at work adding support for various network architectures through our Python API.
First up, now working, are most/all object detectors. We now have 6x fully tested object detector models (and more are likely to ‘just work’):
*ADAS = Advanced Driver Assistance System
These are all now working through our DepthAI Python API, available on our Github.
Converting your own object detection models to run on DepthAI is also now possible, via the simple one-line conversion.
We have also been able to successfully run the following neural model types, and are now working to integrate parsing of these models’ output formats in Python via the DepthAI API.
In all of these cases, we have tested to find these to run properly through initial/prototype parsing/display of the results from DepthAI. We’re now cleaning up these and writing the example Python code to parse the output these types of models. These cleaned up examples will be added to our Github when complete.
Below is an example trying out facial landmark detection:
Brandon & the Luxonis team