Hi,
I need some help.
I would like to use the pre-trained model Faster from pytorch package :
import torchvision
import torch
from torchvision.models.detection import fasterrcnn_resnet50_fpn
model = fasterrcnn_resnet50_fpn(pretrained=True)
Faster RCNN has 2 outputs : (label, bbox) for each Region that it has selected. I would like to extract, for each region, the vector from the last fully connected layer. The vector where I can find all the probabilities of belonging to the different possible categories. So the vector just before the softmax …
For example, with Coco dataset (91 categories), I would like to have one vector [1,91] for each region.
I have read a lot of solution for VGG, Resnet … but nothing about pre trained faster model.
Can someone help me ?
Thanks