Edge TPU Object Tracker Example
This repo contains a collection of examples that use camera streams together with the TensorFlow Lite API with a Coral device such as the USB Accelerator or Dev Board and provides an Object tracker for use with the detected objects.
First, be sure you have completed the setup instructions for your Coral device. If it's been a while, repeat to be sure you have the latest software.
Importantly, you should have the latest TensorFlow Lite runtime installed (as per the Python quickstart).
Clone this Git repo onto your computer:
mkdir google-coral && cd google-coral git clone https://github.com/google-coral/example-object-tracker.git cd example-object-tracker/
Download the models:
These models will be downloaded to a new folder
Further requirements may be needed by the different camera libraries, check the README file for the respective subfolder.
gstreamer: Python examples using gstreamer to obtain camera stream. These examples work on Linux using a webcam, Raspberry Pi with the Raspicam, and on the Coral DevBoard using the Coral camera. For the former two, you will also need a Coral USB Accelerator to run the models.
This demo provides the support of an Object tracker. After following the setup instructions in README file for the subfolder
gstreamer, you can run the tracker demo:
cd gstreamer python3 detect.py --tracker sort
For the demos in this repository you can change the model and the labels
file by using the flags flags
--labels. Be sure to use the models labeled _edgetpu, as those are
compiled for the accelerator - otherwise the model will run on the CPU and
be much slower.
For detection you need to select one of the SSD detection models and its corresponding labels file: