title: How did Pytorch process images in ImageNet when training resnet pretrained models in torchvision.models.resnet34?
body: <p>I downloaded the pretrained parameters of resnet34 in <code>torchvision.models</code> and put them to a tensorflow1.X network, but just get 58% accurary testing on the ImageNet2015 Validation set (50,000 picture).</p>
  
  <p>I guess it may be caused by the different precessing method to the data set. The Validation I am using is in TFRecord format processed by my friend.</p>
  
  <p>So I am wondering how Pytorch process images of ImageNet when training resnet34 pretrained models? Turn RGB to BGR? Scale pictures values to 0--1?</p>