Hello
I have a Mask RCNN using ResNet50, that works fine, except that it very slow and very big.
It runs out of GPU Memory as soon as I set the batch_size to more than 2(!).
Since I do not have 1000 different classes to detect & classify (like ImageNet), but only 50, I was wondering if a smaller backbone would not be a better fit!?
So I want to test different backbones.
In the pedestrian tutorial I find a part that explains how to exchange the backbone:
https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html#modifying-the-model-to-add-a-different-backbone 33
This sample does the modification for FasterRCNN (doc error?), but it seems works fine for Mask RCNN.
But doesn’t it need a mask_roi_pooler too? If so how?
I tried the same adaptations for AlexNet and VGG16, but I failed.
Could anyone help me to get AlexNet or VGG in there?
Regards,
Bernd