Object Detection Using Mobilenet Single Shot Detector

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Made by nilutpolk

About the project

The Google Coral Camera attached to the NavQ board is able to detect objects like cat, dog, car, etc.

Project info

Difficulty: Moderate

Platforms: NXPPython

Estimated time: 4 days

License: MIT license (MIT)

Items used in this project

Hardware components

NXP 8MMNavQ Kit Starter Kit NXP 8MMNavQ Kit Starter Kit x 1

Hand tools and fabrication machines

Python 3.0 Python 3.0 x 1


By using SSD, we only need to take one single shot to detect multiple objects within the image, while regional proposal network (RPN) based approaches such as R-CNN series that need two shots, one for generating region proposals, one for detecting the object of each proposal. Thus, SSD is much faster compared with two-shot RPN-based approaches.

I used the dnn module (Deep Neural Networks) of OpenCV for loading the caffe and prototxt files.

I found the MobileNetSSD_deploy.prototxt.txt and MobileNetSSD_deploy.caffemodel pre-trained weight files from the https://awesomeopensource.com/project/chuanqi305/MobileNet-SSD

Schematics, diagrams and documents





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