Keypoint Detection on Jetson Board?

Autonomous Machines Jetson & Embedded Systems Jetson TX2
1

So I understood it is good to inference a model trained by DIGITS on Jetson.

But here, I feel like Jetson TX2 is optimized for 3 tasks; classification, detection, and segmentation because Deep Vision Runtime Inference API ([url]https://rawgit.com/dusty-nv/jetson-inference/master/docs/html/index.html[/url]) states those 3 nets.

Then what should I do if I want to do something like keypoint detection? I cannot even find proper option for dataset creation on DIGITS.

Maybe is it the best way to utilize those 3 nets provided by jetson-inference ([url]https://github.com/dusty-nv/jetson-inference[/url])?
(BTW, I Tensorflow object detection was very very slow…)

2

Deep Vision Inference also has the tensorNet base class which can be used as a generic model. This mirrors the DIGITS approach which allows users to create Image Classification, Object Detection, Segmentation, or “Other” datasets and models:

In addition to using tensorNet directly, you can create your own subclass for keypoints like detectNet or segNet. These subclasses can be useful for containing any of the pre- or post-processing required by the network.

Here is an example of using DIGITS “other” type option creation: [url]https://github.com/NVIDIA/DIGITS/blob/016d7c080cdf9d17e3317331ad911f52a20e13c2/examples/siamese/README.md[/url]
[url]https://github.com/NVIDIA/DIGITS/blob/320046c952cf97f742ff60692805dbb7ca7dd337/examples/autoencoder/README.md[/url]

The other way, if DIGITS doesn’t fit your type of processing, is to use Caffe directly for training. Meanawhile TensorRT provides the fastest inference.

3

You might also want to consider the traditional image feature detection functions, which are available as part of the visionworks and visionworks-sfm packages. This is CUDA optimized code that returns image “feature points” and can run in real time on high-resolution imagery on the Jetson with capacity to spare.

4

Is Vision Works CUDA enabled by default when installing JetPack 3.3?

5

YES.

You can also check the GPU utilization with tegrastats.

sudo ~/tegrastats

Thanks.