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I followed the tutorial here and was able to successfully run a caffe based SSD Mobilenet model trained on the COCO Dataset on my Raspberry Pi 3,
I attempted to train my own 2 class (3 with background) Mobilenet SSD model and converted it to the NCS format (without any errors while conversion). However, when I run this model on my Raspberry Pi my output looks like such:
I have used this version of caffe:
I have used this repo to get the demo for mobilenet SSD model running as well as followed the instructions on it to train my own:
The python code I use to run the real time inference is from the tutorial linked above, but I am linking it again here for easy viewing:
Finally here is my caffemodel model and prototxt that I try to deploy:
And I convert the graph using the following:
mvNCCompile models/MobileNetSSD_deploy.prototxt \
-w models/MobileNetSSD_deploy.caffemodel \
-s 12 -is 300 300 -o graphs/mobilenetgraph
Kindly advice on what I am missing here, how can I get my custom model to run just as seamlessly as the example model runs on the Mobilenet repo above.