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Hi, I have a question about the performance benchmarks section. The best performaing model from your benchmarks, ssd_mobilenet_v1, has a prediction time in seconds of 0.72 -- Is that the total runtime of the script? I'm wondering if I could achieve ~1 FPS running in realtime (basically looping as fast as possible against the camera input), or is there more overhead? (edit -- made question more specific)

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Yeah its total runtime of script. However you can get upto 3-4 FPS with more optimizations. We are going to try more quantization options soon with release of tensorflow 1.7 and will report our findings (Will post updates in blog). Also pi camera code needs to be optimized which will further increase FPS. One big advantage of this method is just by collecting ~200 images for any use case, you can have detector ready in couple of hours.

One advantage of using API based approach is you can get much higher FPS without compromising accuracy and is also independent of pi CPU power and heating etc.

Curious, have you looked at any other embedded platforms besides the Pi? The Tegra might be an interesting comparison point, I wonder what kind of FPS the onboard GPU would buy you.

Hey, good suggestion to benchmark against other SOC's as well. I heard raspberry pi recently added support for external graphics card. Haven't tried yet.

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