Close

Dog Detector

A project log for Autonomous Agri-robot Control System

Controlling autonomous robots the size of a small tractor for planting, weeding and harvesting

capt-flatus-oflahertyCapt. Flatus O'Flaherty ☠ 10/13/2018 at 08:490 Comments

Obviously, we're not going to be detecting dogs in the field, but there is not a publicly available ready made inference model for detecting vegetable seedlings - yet.

A lot of Ai models were trained on cats and dogs, so not wanting to break with tradition, I thought it relevant to test the Jetson TX2 object recognition system on my dog. Actually, the correct term is 'inference' and searching the net for 'object recognition' is fairly useless.

The demo used is found on the Nvidia GitHub page: https://github.com/dusty-nv/jetson-inference and the best thing to do is scroll right down to about 3/4 down and run this:

$ cd jetson-inference/build/aarch64/bin

$ ./detectnet-camera coco-dog                           # detect dogs in the camera

in the terminal  (see video):


Next thing to do is to try and get the bounding box coordinates exported into the real world via the I2C bus, then, sometime next year, train some models with plant images that represent what is actually grown here in the fields.

Building the image set for the vegetables is not easy task and requires thousands of photos to be taken in different lighting conditions. Previous experience using the Pixy2 camera shows that bright sunlight causes relatively dark and sharp shadows which were a bit of a problem. With Ai, we can incorporate photos with various shadow permutations to train the model. We need to do some research to make sure that we do it properly.

Discussions