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ML-TN-002 - Real-time Social Distancing estimation

195 bytes added, 16:32, 27 January 2021
Step #1
==== Step #1 ====
The first step was conducted using the official evaluation kit (EVK) by NXP. Its The goal was to make the Social-Distancing project to work on the new this platform maintaining the core functionalities. In essence, the code was modified in order to replace the [https://github.com/CMU-Perceptual-Computing-Lab/openpose OpenPose library] with [https://github.com/tensorflow/tfjs-models/tree/master/posenet PoseNet]. This was required to cope with the operations actually supported by the [https://www.nxp.com/design/software/development-software/eiq-ml-development-environment:EIQ NXP eIQ] software stack and the NPU. For those who are familiar with embedded software development, this should be unsurprising. When porting applications from PC-like platforms to embedded platforms, in fact, handling such hardware/software constraints is a common practice.
The resulting processing pipeline is shown in the following figure.
[[File:Social-distancing-screenshot2.png|center|thumb|600x600px|The step 1 application running on the EVK (2/2)]]
 
It is worth remembering that, even though OpenPose was replaced, the software interface between high-level layers and PoseNet was not altered. This allowed to keep untouched these layers.
==== Step #2 ====
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