RUNNING ML
DEMOS
To run ML Demos we have created run_ml_demo.sh shell script. This script ask for user
preferences like demo type, camera types, camera node entry, desired MIC etc and based on
that run ML demos.
In this section, we discuss how to run each demo. Details description of Demo is in next section.
1. Crowd Counting Demo
This is a demo application using Python, QT, and Tensorflow to be run on embedded
devices for Crowd counting. In this demo, we count the heads/persons in the crowd.
Therefore, it is useful in human flow monitoring or traffic control.
This demo run on either pre-captured Image mode or in Live Camera mode. In pre-captured
image mode, we took few sample images and find head counts in those images. In live
camera mode we capture live frame through webcam or D3 mezzanine camera and try to
find head count from it. User can select any mode by clicking on GUI.
Pre-requisite:
•
Webcam or D3 Mezzanine camera
•
USB mouse
•
HDMI Display having minimum 1080p resolution
Steps to run Demo:
Figure 6: Run Crowd Count Demo