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Davis King 2016-06-22 22:30:45 -04:00
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commit 87493f4971
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examples/dnn_imagenet_ex.cpp
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@ -4,6 +4,9 @@
using the deep learning tools from the dlib C++ Library. We will use the pretrained
ResNet34 model available on the dlib website.
The ResNet34 model is from Deep Residual Learning for Image Recognition by He, Zhang,
Ren, and Sun.
These tools will use CUDA and cuDNN to drastically accelerate network
training and testing. CMake should automatically find them if they are
@ -100,7 +103,9 @@ int main(int argc, char** argv) try
{
std::vector<string> labels;
anet_type net;
// get this file from http://dlib.net/files/resnet34_1000_imagenet_classifier.dnn.bz2
// Get this file from http://dlib.net/files/resnet34_1000_imagenet_classifier.dnn.bz2
// This pretrained model has a top5 error of 7.572% on the 2012 imagenet validation
// dataset.
deserialize("resnet34_1000_imagenet_classifier.dnn") >> net >> labels;