I am currently working on tensorflow object detection models.
I downloaded SSD MobileNet V1 COCO* from
Then I used model optimizer to convert it with its supported json file, pipeline config etc. Everything is just fine until this step. I got xml and bin files.
I send these files to my Upcore Plus. While I am running python- sample object detection I faced with low FPS on MYRIAD. When I choose -d CPU I got about 1.2 FPS. However in -d MYRIAD I got 0.26 FPS.
I did everything in your documentations. What I missed here?
Thank you for your answering.
I am beginner in these fields. I do not have a roadmap. Do you have any suggestion for this problem. I need around 10 FPS on Upcore Plus X. Should I use different model, library or optimizer? Should I focus on CPU optimization?
The easiest would be to change the model to something else that is less compute heavy.
The popular yolo model (some versions are available as Intel pretrained model) is one of the alternative for a fast model.
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