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The voxl-tflite-server is a GPU-optimized TensorFlow Lite environment that can run as a a background systemd service. It processes standard TensorFlow Lite models in real-time using the GPU on VOXL.


Table of contents

  1. voxl-configure-tflite
  2. TFlite Server Configuration File
  3. Visualization Options
  4. Demo
  5. Using Your Own Models
  6. Source


Like all MPA services, voxl-tflite-server has a basic configure script to enable/disable the service as well as to reset the config file back to default for factory resets. This specific configuration script also allows you to select a default input pipe: tracking(grayscale) or hires(color).

yocto:/$ voxl-configure-tflite -h

Start wizard with prompts:

Shortcut configuration arguments for scripted setup.
factory_enable will reset the config file to factory defaults
before enabling the service.

voxl-configure-tflite-server factory_disable
voxl-configure-tflite-server disable
voxl-configure-tflite-server factory_enable
voxl-configure-tflite-server enable

show this help message:
voxl-configure-tflite-server help
yocto:/$ voxl-configure-tflite
Starting Wizard

Do you want to reset the config file to factory defaults?
1) yes
2) no
#? 1
wiping old config file
Creating new config file: /etc/modalai/voxl-tflite-server.conf
The config file was modified during parsing, saving the changes to disk

do you want to enable or disable voxl-tflite-server
1) enable
2) disable
#? 1

do you want to run the tflite server with:
 (1) Mobilenet + Hires camera
 (2) Mobilenet + Tracking camera

1) 1
2) 2
#? 1
enabling  voxl-tflite-server systemd service
Created symlink from /etc/systemd/system/ to /etc/systemd/system/voxl-tflite-server.service.
starting  voxl-tflite-server systemd service
Done configuring voxl-tflite-server

TFlite Server Configuration File

The default configuration file has recommended settings for a background service. If the output rate is too slow, try decreasing the skip_n_frames parameter.

yocto:/$ cat /etc/modalai/voxl-tflite-server.conf
 * This file contains configuration that's specific to voxl-tflite-server.
 * skip_n_frames -   how many frames to skip between processed frames. For 30hz
 *                   input frame rate, we recommend skipping 5 frame resulting
 *                   in 5hz model output.
 * model         -   which model to use. Currently only support mobilenet for
 *                   object detection.
 * input_pipe    -   which camera to use (tracking or hires).
	"skip_n_frames":	5,
	"model":	"/usr/bin/dnn/ssdlite_mobilenet_v2_coco.tflite",
	"input_pipe":	"/run/mpa/hires/"

Visualization Options

You can view either the MobileNet output stream as another normal camera pipe. As such, it can be viewed with voxl-portal, converted to ROS with voxl_mpa_to_ros, and logged to disk with voxl-logger.

See the image at the top of this page for an example.


Using Your Own Models

This server can run both CPU and GPU accelerated models but in order to utilize the GPU, models must be float16 quantized. See the Tensorflow Guide for more instructions.

Once you have a model ready, use our MobileNet code as an example of how to get started!

NOTE: The current version of Tensorflow Lite is 2.2.3 and only supports the TFLITE_BUILTINS and custom opsets.


Source code is available on Gitlab