I’m trying to use the pre-trained Faster RCNN in PyTorch. I found that the torchvision package has the Faster R-CNN ResNet-50 FPN pre-trained network. Seeing that it uses ResNet as its feature extractor, I assumed the preprocessing was the same as if I used the ResNet models in torchvision: which is to use the ImageNet preprocessing below
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
                                 std=[0.229, 0.224, 0.225])

However, I’m getting very poor predictions from the ResNet, very few cars are being detected and many of the obvious elements in the scene are not captured. What is the correct preprocessing for the Faster RCNN?