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Hi, I successfully ran ncs-fullcheck example and used it to inference several pictures. The performance of Alexnet is around 200ms and GoogLeNet is around 550ms. However, when I ran the profiling from tool kit (make example), it shows both AlexNet and GoogLeNet inference is around 90ms. There seem to be a gap between profile data and real inference time. Does anyone know where is this gap comes from (transfer image to the stick and retrieve result out, i.e.), and how do I get the performance the same as profiled?
Another question is the inference result seems different from caffe running on the same caffemodel (using cpp classifier), how do I get same result as using caffe?
0.3094 - "n02124075 Egyptian cat"
0.1761 - "n02123159 tiger cat"
0.1221 - "n02123045 tabby, tabby cat"
0.1132 - "n02119022 red fox, Vulpes vulpes"
0.0421 - "n02085620 Chihuahua"
Egyptian cat (69.19%) tabby, tabby cat (6.59%) grey fox, gray fox, Urocyon cinereoargenteus (5.42%) tiger cat (3.93%) hare (3.52%)