Real-time AI Person Detection on Edge Devices: Testing SSD Models on Raspberry Pi

Sergey L. Gladkiy

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9 Oct 2020CPOL3 min read

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In this article, we’ll test the accuracy and the performance of the MibileNet and SqueezeNet models on the Raspberry Pi device.

Here we'll create the Python code for detecting humans in images using SSD DNN models.

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This article is part of the series 'Realtime AI Person Detection on Edge Devices ◁ Prev View All Next ▷

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Written By

Sergey L. Gladkiy

Team Leader VIPAKS

Russian Federation

EDUCATION:

Master’s degree in Mechanics.

PhD degree in Mathematics and Physics.

PROFESSIONAL EXPERIENCE:

15 years’ experience in developing scientific programs
(C#, C++, Delphi, Java, Fortran).

SCIENTIFIC INTERESTS:

Mathematical modeling, symbolic computer algebra, numerical methods, 3D geometry modeling, artificial intelligence, differential equations, boundary value problems.

Real-time AI Person Detection on Edge Devices: Testing SSD Models on Raspberry Pi

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