Hi! We've downloaded your pretrained inception models for Tensorflow (one example is https://deepdetect.com/models/tf/inception_resnet_v2.pb) .However, the output layer (softmax) has one extra class. (1001 instead of 1000). I also checked the mapping against Imagenet dataset and the output corresponds to 1 index shifted version of the original imagenet mapping. What does class 0 correspond to in these models?
@beniz Does DeepDetect support multiple models in a single 'predict' call? I.e. if there are two models A and B loaded up, could you use a single predict call on one or more URIs to hit both model A and model B?
huh interesting, I'll have to go back and look at the logs again. occasionally I saw it (re)loading the network into memory through the course of processing numerous requests for a while, and I couldn't quite figure out why....
ahah - right, forgot about that distinction. it was numerous calls to the same multiple services, so inevitably the same service would get multiple calls at some point. would it ever reload a model due to memory usage? I doubt that's the reason in this case as I had plenty of memory available, just curious if/how that'd affect it. I know on gpu is a different situation.
:thumbsup: I think we're pre-TF v1 still, so we will see. At some point once we've organized some of our things, we may be able to contribute some Dockerfiles as well. We're currently on Ubuntu 16.04 with and without CUDA support, with TF support.