Inference Time about ssd-tensorflow HOT 1 OPEN

Thanks for your feedback.
For inference time benchmark, the Caffe implementation is purely C++, so clearly better optimized. If you want to compare, it could be better to use the SSD notebook with numpy post-processing: the problem with the test script is that it is purely TF-based, in order to be able to record everything for TensorBoard. But TF tends to be slower than pure Numpy implementation for the post-processing pipeline, which is loop based.

For the memory aspect, I think it is unfortunately one of TF drawback, it uses more memory than some other more optimized framework. I guess it is part of the trade-off to get more flexibility. I'll try to see if I can improve a bit on that aspect by moving more elements of the pipeline to the CPU.

from ssd-tensorflow.